Growing use of AI for health presents governments, providers, and communities with opportunities and challenges

Artificial Intelligence (AI) holds great promise for improving the delivery of healthcare and medicine worldwide, but only if ethics and human rights are put at the heart of its design, deployment, and use, according to new WHO guidance published today.

The report, Ethics and governance of artificial intelligence for health, is the result of 2 years of consultations held by a panel of international experts appointed by WHO.

“Like all new technology, artificial intelligence holds enormous potential for improving the health of millions of people around the world, but like all technology it can also be misused and cause harm,” said Dr Tedros Adhanom Ghebreyesus, WHO Director-General. “This important new report provides a valuable guide for countries on how to maximize the benefits of AI, while minimizing its risks and avoiding its pitfalls.”

Artificial intelligence can be, and in some wealthy countries is already being used to improve the speed and accuracy of diagnosis and screening for diseases; to assist with clinical care; strengthen health research and drug development, and support diverse public health interventions, such as disease surveillance, outbreak response, and health systems management.

AI could also empower patients to take greater control of their own health care and better understand their evolving needs. It could also enable resource-poor countries and rural communities, where patients often have restricted access to health-care workers or medical professionals, to bridge gaps in access to health services.

However, WHO’s new report cautions against overestimating the benefits of AI for health, especially when this occurs at the expense of core investments and strategies required to achieve universal health coverage.

It also points out that opportunities are linked to challenges and risks, including unethical collection and use of health data; biases encoded in algorithms, and risks of AI to patient safety, cybersecurity, and the environment.      

For example, while private and public sector investment in the development and deployment of AI is critical, the unregulated use of AI could subordinate the rights and interests of patients and communities to the powerful commercial interests of technology companies or the interests of governments in surveillance and social control.

The report also emphasizes that systems trained primarily on data collected from individuals in high-income countries may not perform well for individuals in low- and middle-income settings.

AI systems should therefore be carefully designed to reflect the diversity of socio-economic and health-care settings. They should be accompanied by training in digital skills, community engagement and awareness-raising, especially for millions of healthcare workers who will require digital literacy or retraining if their roles and functions are automated, and who must contend with machines that could challenge the decision-making and autonomy of providers and patients.

Ultimately, guided by existing laws and human rights obligations, and new laws and policies that enshrine ethical principles, governments, providers, and designers must work together to address ethics and human rights concerns at every stage of an AI technology’s design, development, and deployment. 

Six principles to ensure AI works for the public interest in all countries

To limit the risks and maximize the opportunities intrinsic to the use of AI for health, WHO provides the following principles as the basis for AI regulation and governance:

Protecting human autonomy: In the context of health care, this means that humans should remain in control of health-care systems and medical decisions; privacy and confidentiality should be protected, and patients must give valid informed consent through appropriate legal frameworks for data protection.

Promoting human well-being and safety and the public interest. The designers of AI technologies should satisfy regulatory requirements for safety, accuracy and efficacy for well-defined use cases or indications. Measures of quality control in practice and quality improvement in the use of AI must be available.

Ensuring transparency, explainability and intelligibility. Transparency requires that sufficient information be published or documented before the design or deployment of an AI technology. Such information must be easily accessible and facilitate meaningful public consultation and debate on how the technology is designed and how it should or should not be used.

Fostering responsibility and accountability. Although AI technologies perform specific tasks, it is the responsibility of stakeholders to ensure that they are used under appropriate conditions and by appropriately trained people. Effective mechanisms should be available for questioning and for redress for individuals and groups that are adversely affected by decisions based on algorithms.

Ensuring inclusiveness and equity. Inclusiveness requires that AI for health be designed to encourage the widest possible equitable use and access, irrespective of age, sex, gender, income, race, ethnicity, sexual orientation, ability or other characteristics protected under human rights codes.

Promoting AI that is responsive and sustainable. Designers, developers and users should continuously and transparently assess AI applications during actual use to determine whether AI responds adequately and appropriately to expectations and requirements. AI systems should also be designed to minimize their environmental consequences and increase energy efficiency. Governments and companies should address anticipated disruptions in the workplace, including training for health-care workers to adapt to the use of AI systems, and potential job losses due to use of automated systems.         

These principles will guide future WHO work to support efforts to ensure that the full potential of AI for healthcare and public health will be used for the benefits of all.

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These Artificial Intelligence Companies, Now have the Funding to Innovate

The rate at which artificial intelligence is advancing is shaping the world around us. From automation to drug development and diagnosis, there is no industry that AI has not taken over. Like the silver lining to a dark cloud, the chaos created by COVID-19 pandemic has made organizations realize the power of artificial intelligence and are gearing up to invest heavily. Many renowned investors and Fortune 500 companies are also backing up budding AI companies that show promising growth potential. For the month of June in 2021, these are the AI companies that received heavy funding. For information on AI investments in April and May, check out this link.  

Top AI funding in June

CoffeeMug.ai

Transaction type: Pre-seed

Key investor(s): Paradigm Shift Capital and AngelList India

Singapore based AI professional networking platform, CoffeeMug.ai has raised US$625,000 in pre-seed funding round. Govind Mundhra, Founding General Partner of Paradigm Shift Capital, one of the key investors, will be joining the board of directors of CoffeeMug.ai. As per official reports, CoffeeMug will use these funds to accelerate its efforts to improve its AI-based matchmaking algorithm, double its user base and connect them with leadership level business opportunities.

Upside AI

Transaction type: Seed money

Key investor: Endiya Partners

Mumbai-based investment management startup, Upside AI, raised US$1.2 million in seed funding. Led by venture capital fund Endiya Partners, Upside AI plans to use the funds to fill up leadership positions and other senior roles. According to its cofounder Atanuu Agarrwal, the company intends to add 1,000 high net worth individuals, family offices, and institutional clients.

Eightfold AI

Transaction type: Series E

Key investors: SoftBank Vision

Eightfold AI is a talent-based intelligence platform provider based out of California. In the Series E funding round led by SoftBank Vision, with participation from General Catalyst, Capital One Ventures, Foundation Capital, IVP, and Lightspeed Venture Partners, Eightfold AI raised US$220 million. The company intends to use the total funding to promote further growth and development, and expand its partner ecosystem.

Gloat

Transaction type: Series C
Key investor(s): Accel, Eight Roads Ventures, Intel Capital, Magma, PICO

Gloat is an AI-enabled talent marketplace platform. Headquartered in New York, Gloat has expanded its offices globally, with an R&D center in Tel Aviv. The company assists companies in connecting their employees with development opportunities like projects and mentorship programs. In a Series C funding round co-led by Accel, Eight Roads Ventures, Intel Capital, Magma Venture Partners, and PICO partners, Gloat raised US$57 million which will be used to accelerate product innovation.

Cleerly

Transaction type: Series B

Key investor: Vensana Capital

Cleerly is a New York City-based company, that uses AI and machine learning algorithms to diagnose coronary artery disease. The company has developed a software platform that facilitates whole-heart quantification and characterization of atherosclerosis. Unlike traditional techniques that take hours, Cleerly’s software can perform the diagnosis in a matter of minutes, noninvasively. Led by Vensana Capital, Cleerly raised US$43 million in Series B funding, which will be used to scale its commercial reach, expand capabilities, strategic partnerships, and focus on R&D.

The post GLOBAL ARTIFICIAL INTELLIGENCE COMPANIES THAT RECEIVED FUNDING IN JUNE 2021 appeared first on Artificial Intelligence.

Big data and data analytics jobs around the world.

Big Data is a big thing in today’s world with tremendous growth opportunities for professionals. As companies around the world are aggressively hiring data professionals to extract insights for their businesses, data analysis has become a striking career choice. Organizations across industries want to take advantage of big data to stay ahead of the competition.

A big data scientist or a data analyst, if you’re a data professional looking for a big, new project, check out these full-time, big data job openings in renowned companies across the globe. To help you crack the interview stage, check out these popular big data interview questions and answers.

1. Senior Insights Analyst

Company: LinkedIn

Location: Sunnyvale, CA

Job Summary

As a Senior Insights Analyst in the Product Operations organization, you will leverage one of the richest proprietary data sets in the world to create compelling, impactful, and actionable insights for the company, and the product and operations teams. Your expertise will help LinkedIn deepen the intelligence from its member/customer signals, and elevate the quality of the company’s products.

Responsibilities

• Leverage Linkedin’s unique data to drive insights and learnings for product improvement.
• Build and scale insights to help our teams deliver exceptional products and services to all members and customers.
• Partner closely with our Product Operations teams to turn data into action, and provide recommendations to influence and shape the product strategy and roadmap.
• Write SQL/Presto/Spark/Python queries to extract, blend and analyze structured and unstructured data, and present the findings in Tableau and PowerPoint.
• Partner and execute with Data Science, Business Intelligence, Engineering to ensure foundational data are available and accurate for insights tools and analyses.
• Build analytical tools, products, and dashboards to democratize insights and enhance our collective storytelling ability.
• Apply statistical models and causal inference methods to uncover trends, measure impact, and predict the future performance of our product.
• Connect signals we have from our members and customers across, including but not limited to: customer support cases, social media mentions, behavioral data on the platform, and more.
• Help develop the predictive analytics engine in partnership with Data Science to project the impact of friction reduction in products.
• Own the analytical framework, and provide methodology & measurement for new product quality metrics like user success & sentiment.
• Collaborate closely with product, operations, engineering teams to provide analysis, reporting, and tool-building capabilities that inform our key stakeholders.
• Proactively identify opportunities to scale insights through automation and self-serve mechanisms.
• Coach and uplevel our signals and product quality teams on tools, analytics, and insight.

Qualifications

• 5+ years experience in analytics or quantitative role.
• Degree in math, statistics, economics, or related quantitative field.
• 3+ years experience in a role requiring research, data interrogation, analysis, and visualization.
• 5+ years of experience writing and optimizing SQL queries to extract trends.

Preferred Qualifications

• MA/MS/Ph.D. in math, statistics, economics, or related quantitative field.
• Experience in a role requiring influencing R&D and measuring product impact.
• Ability to convert a complex data set into an actionable recommendation.
• Ability to communicate findings clearly to both technical and non-technical audiences.
• Experience in the Technology, Product, and/or Consultative industry providing actionable insights.
• Experience with Hadoop and/or Python for ETL, and working with big data.
• Experience with statistical modeling, Python/R scripts, and packages.
• Experience with experimental design and A/B testing.
• Experience with Tableau, or other data visualization software.
• Experience with working cross-functionally with data services, engineering, product, and operations teams.
• Knowledge of social media and consumer Internet practices.

2. Data Analyst, Globalization

Company: Netflix

Location: Los Gatos, CA

Job Summary

As a Data Analyst, you will collaborate with Netflix’s Analytics Program Manager and other Globalization team members, to support the data and infrastructure that translate business requirements into operational excellence. You will learn everything about Globalization data in order to provide relevant and valuable insights into its performance. You will use your analytical capabilities to create Globalization- and Netflix-ready dashboards to review, measure and manage the business.

Responsibilities

• Track and maintain data integrity across multiple tools and workflows; identify and resolve data inconsistencies.
• Prepare regular business health and insights decks for globalization.
• Build and manage external-facing reporting for the team.
• Build and maintain data ingestion pipelines.
• Perform ad hoc analyses and queries as necessary (for requests that cannot be answered via existing dashboards).
• Provide analytical support for initiatives (that are fairly straightforward but might require complex analytics).
• Collaborate with the Analytics Program Manager to create an optimized business operations framework against which the Globalization team can perform and support translation at scale.
• Develop and maintain effective communication tools to report business performance and drive business decisions both internally (vendor QBRs and newsletters) and externally (dashboards) for globalization.

Qualifications

• BA/BS degree in Data Analytics, Business, Finance, or Operations.
• 3+ years of experience in consulting, business operations, or data analytics at a global scale.
• Required Skills: advanced SQL, advanced python (pandas & NumPy, data visualization libraries), ETL, Tableau (or similar dashboard platforms); experience with Jupiter notebooks preferred.
• Excellent analytical skills with experience managing and utilizing large data sets to drive performance and process improvement.
• Strong communication skills with the ability to effectively communicate risks and dependencies, and to distill complex concepts into simple, actionable recommendations at the leadership level.
• Drive decisions and change management through data analysis, collaboration, and leadership.

3. Data Analyst

Company: Twitch

Location: San Francisco, CA

Job Summary

Twitch’s Viewers Analytics team is looking for a product data analyst. The Viewers team develops customer-facing products that connect viewers and streamers, such as Browse, Search, Notifications, and Recommendations. As part of the Viewers Analytics team, you will improve the quality and velocity of product decisions made in the Viewers team. You will instrument tracking events, gather data, suggest metrics, design AB tests, build dashboards, and produce insights for your product partners. You will report to the Viewers Analytics Lead.

Responsibilities

• Become a domain expert at the product surface your support, building trust with your product partners.
• Ensure your product, engineering, and design partners understand and use the insights you produce.
• Automate data monitoring requests and frequently asked questions in dashboards.
• Troubleshoot data quality issues, communicate their impact, and propose solutions or workarounds.
• Distill complex problems and highlight trade-offs between solutions, with the help of product partners and analyst mentors.

Qualifications

• Great SQL skills, so you can quickly tap into our data sources.
• A clear understanding of hypothesis testing, p-values, and bootstrap methods, so you can explain them to product partners unfamiliar with statistics.
• At least 6 months of experience transforming data into insights in a related industry, or equivalent data analytics experience. Internships count!
• Experience using Python data libraries like pandas, NumPy, or scipy.

Preferred Qualifications

• Experience designing and analyzing AB tests in a tech company.
• Product analytics experience with signup funnels, engagement metrics, and retention analysis.
• Python programming experience beyond data or analytics.
• Experience developing Tableau dashboards.
• Familiarity with Git or other version control tools.
• Passion about online communities and games, frequent Twitch user.

4. Senior Data Analyst and Modeler

Company: JPMorgan Chase & Co.

Location: Glasgow, Scotland

Responsibilities

• Analyze and catalog files and processes which are currently sources of data specific to the domain of interest of transactions & positions.
• research, design, document, and modify data specifications throughout the production life cycle. Data will be available in diverse formats ranging from Text files, databases, JSON, Kafka messages, etc.
• Analyze the requirements from the consumers based on your understanding of the Conformed model, model source data to the model enhancing the same where necessary.
• Take into account the limitations of the underlying tech infrastructure and cater the solution so that it can be implemented and is maintainable.
• Develop productive business relationships and integrate activities with IT team members, Quality Assurance, Software Development, and Database Administration teams, to ensure successful deployment and support of Production issues and various Projects/Assignments handled in the Applications domain.
• Work collaboratively with stakeholders to facilitate and positively influence solution development and ongoing support. Maintains confidentiality of the information and uses information appropriately.
• Exhibits sound judgment when making decisions and recommendations and serve as the conduit between the customer community (internal clients) and the software development team through which requirements flow.

Qualifications

• Bachelor’s Degree with specialized coursework in Computer Science or Management Information Systems.
• Significant years of experience as a data analyst and/or modeler.
• Knowledge of Wealth Management & associate accounting is a must.
• Extremely proficient with SQL and using SQL to analyze data.
• Knowledge of Big Data and Hadoop platforms, Kafka, Cassandra are a plus
• Ability to operate effectively in ambiguous situations.
• Ability to learn quickly, manage work independently, and is a team player.
• Ability to engage with developers & stakeholders including – consumers, project management, upstream, senior management & peer group.

5. Senior Analyst

Company: eBay

Location: London, United Kingdom

Job Summary

eBay is looking for a senior analyst to join the UK Analytics team with significant responsibility for delivering business Analytics. The London-based team specifically manages the UK Trading businesses and supports the EU Marketplace Businesses by creating and delivering actionable analytics insights to support UK business performance and develop a deeper understanding of business drivers and opportunities mainly focused on Seller Performance, Customer Insights, Promotions, and Pricing.

Responsibilities

• Support Business Decision-making through data-driven Actionable Insights.
• Apply your expertise in quantitative analysis and the presentation of data to see beyond the numbers and understand how our users interact with our core products.
• Work with Business Partners to scope analysis to answer key business questions – challenge their thinking and become a trusted business partner. Help the business prioritize analytical deliverables and manage their expectations.
• Measure and interpret the impact of business initiatives and new products and features.
• Develop and deliver the business story from the analysis and effectively communicate this to business and finance partners.
• Providing weekly updates on business performance to finance, cost, and promotional teams.
• Insight Analytics including ad-hoc deep dives, cost estimation, and forecasting, etc.
• Identify, extract and analyze relevant information from multiple data sources (primarily Teradata).
• Assess internal/external factors that may influence customer usage and important metrics.
• Be the Customer: Buy, Sell, and Engage with eBay’s mission of connected commerce.

Qualification

• An established analytical career as a Data Scientist/BI/Insight Analyst preferably within e-commerce, consumer web, retail, media, digital marketing, or consultancy environment.
• Graduate degree (ideally in a quantitative field).
• Proven ability in clearly defining a problem, collating the required information, analyzing the results, and presenting findings and recommendations.
• Ability to initiate and drive projects to completion with minimal mentorship.
• Strong technical and financial modeling skills with commercial business insight.
• Advanced level skills in SQL and Tableau and Excel are a requirement. R Desirable
• Proven experience in the analysis of relational databases e.g. Teradata or Hadoop and strong SQL/SAS/R programming skills.
• Experience in working with big data, including data extraction & optimization techniques, and reporting/visualization, in particular using data visualization tools.
• Experience in web analytics is not essential but useful.
• Fluency in English is a requirement.
• Excellent communication skills.

6. Data Analyst

Company: AXA UK

Location: Glasgow, Scotland

Responsibilities

• Extract data from primary and secondary sources. Format and interpret the data so it can easily be understood, analyze data using statistical techniques.
• Work with a variety of data tools and databases, designing solutions, maintaining data, creating, updating, reading, and deleting records.
• Collect data from multiple sources, handle raw data, cleanse data and convert it into structured formats ready for further analytics and data science.
• Work with big data in a data lake on a cloud platform.
• Work and collaborate with other data professionals; data engineers, MI engineers, data scientists.
• Work with business stakeholders to communicate with data, preparing reports, analyzing KPIs and other metrics.
• Create and maintain business glossary, data dictionaries and classify data according to local priorities.
• Implement data by design processes along with Data Architects, DPO, and other stakeholders.

Qualifications

• Mathematical skills (especially statistics and probability).
• Strong excel skills, experience in working with and manipulating data.
• Experience with visualization tools and reporting packages (e.g. Power BI).
• Experience with relational databases, SQL language, ETL frameworks. Knowledge of Python and R desirable.
• Adept at queries, report writing, and presenting findings.
• Knowledge of data management and data governance practices including data protection.
• Strong oral and written communication skills, autonomy, curiosity, rigorous in execution, team player and able to coordinate a network of stakeholders from various backgrounds, ability to understand business needs.
• Strong problem-solving capability.
• Knowledge of agile methodology/MS Devops desired.
• Desired experience and knowledge of Salesforce.

7. Research Analyst – Technology Advantage

Company: Boston Consulting Group (BCG)

Location: Madrid, Spain

Job Summary

As a Research Analyst within BCG’s Data & Researcher Services team, you would provide secondary research in support of proposals, client cases, and business or IP development initiatives, with specialization in one or more Technology Advantage related topics.

Technology Advantage topics covered by the team on a regular basis include Digital/IT, Big Data, Agile, IT/Tech Infrastructure, Enterprise Architecture, Cloud, AI, and Digital Transformation. You will be responsible for delivering a variety of requests throughout the day.

Responsibilities

• Manage various research requests with a high-level accuracy and organization, primarily on key Technology Advantage topics you have a strong interest in.
• Understand request objectives focussed on Technology and IT industry and proactively suggest the most appropriate and efficient research approach to senior DRS team members and customers, as appropriate.
• Evaluate the source quality and data accuracy, and proactively help to identify and raise research-related issues.
• Engage in thought partnership with consulting teams and knowledge teams to understand, scope, and deliver accurate, timely, and relevant data and information.
• Coaching Research Associates and outsourcing partners, as well as delivering data quality analysis with them.
• Along with collecting, summarizing and synthesizing relevant data and information into appropriate, concise, timely, and highly effective output, you are proficient in Excel, Word, and PowerPoint.
• With guidance, you will develop tools, resources, and training within the Technology Advantage topic, you will be contributing to knowledge capture and documentation.
• Using your strong analytical thinking, you will provide advanced synthesis, and develop deep expertise in specialized research tools, databases and sources.
• In addition to being intellectually curious and being able to work in a fast-paced, deadline-focused environment, you can identify practical, timely, and innovative research approaches.

Qualifications

• 2-4+ years relevant working experience, with some specialization in 1-2 topics in Digital/IT, Big Data, Agile, IT/Tech Infrastructure, Enterprise Architecture, AI, Cloud, and Digital Transformation sectors.
• Bachelor’s degree with a strong preference for analytic programs (e.g. economics, engineering, sciences).
• Excellent English; + fluent in another European language (German preferred, Spanish).
• Hours of operation for DRS will be 9:00 am – 18:00 CET. Your regular full-time work week will be 40 hours a week.

8. Junior Data Analyst

Company: NielsenIQ

Location: Warsaw, Poland

Job Summary

Data Analyst works in the operational part of a global business unit called Retail Direct Data Solution. This global team, present in countries such as France, UK, the US, Australia, Romania, and Poland, provides clients from and outside Europe with stock management solutions aimed at improving on-shelf availability. The key purpose of the job is to develop and maintain key business metrics for Global clients to assess the sales/stocks effectiveness. As a Data Analyst, you will be designing, testing, and validating the logic for new metrics, you will create different excel-based reports associated with the validation of the new logic and cooperate on a daily basis with the Business Analyst.

Responsibilities

• Work on designing, testing, and validating the logic for new metrics solutions to our clients.
• Deep data analysis for various data sets.
• Control the creation and release of analytics internally and to our clients (this involves scheduling work with offshore resources).
• Maintain documentation for solutions.
• Mentor junior members of the offshore and onshore teams.
• Create efficiencies in the way we manage our global analytics requirements by establishing global ways of working.
• Organize and support a library of solutions available to provide information to other departments and to make it easier to support.

Qualifications

• 1+ years of analytical experience, working with data/databases in a large company.
• Proficiency in Excel (Advanced level).
• Fluent command of English.
• Proven track record of being detail-oriented, client service driven, and committed to the timely execution of tasks.
• Experience with R/Python language usage in regular work will be a plus.
• Experience in cooperation with off-shore resources will be a plus.

9. Senior Analyst – FP&A

Company: Spotify

Location: Stockholm, Sweden

Job Summary

The FP&A team is responsible for owning and managing the company’s financial forecasting process as well as partnering with business stakeholders to enable and drive financially informed decision-making. As a Senior Analyst, you will have the exciting opportunity to grow and develop your skills as a finance business partner through various responsibilities, including financial modeling and analysis, forecasting and budgeting, management reporting, and data analytics.

Responsibilities

• Build and maintain detailed and dynamic financial models that are powered by big data to inform quarterly forecasts, budgeting/planning across the P&L, investment evaluation and prioritization, and commercial decision-making.
• Partner closely and regularly with both business and support teams to track business performance, exercise expenditure and investment controls, and identify risks and opportunities to our financial outlook.
• Manage and deliver on operational and analytical processes connected to each accounting period close, including accruals, variance analysis, management reporting, and/or model recalibrations as necessary.
• Use your communication and storytelling skills to frame issues effectively and translate the outputs of your financial analysis into impactful insights and compelling business recommendations.

Qualifications

• 5+ years of relevant, applied experience in finance/accounting, operations, strategy, consulting, or banking roles (exposure to SaaS, advertising, and/or content business models is preferred).
• Strong grasp of the 3 financial statements, with a high aptitude and enthusiasm for problem-solving through quantitative modeling and analysis.
• Advanced Excel / Google Sheets skills with a deep understanding of model architecture, formula efficiency, pivot tables, and macros.
• Savvy and experienced with forecasting, reporting, and procurement software (e.g., Adaptive, NetSuite, Coupa, etc.).
• Prior experience with SQL/BigQuery and BI/data visualization tools (Looker, Tableau) is a plus – you will be required to eventually learn and apply these skills on the job.
• Experience forming relationships across all levels of an organization and comfortable presenting to a broad range of audiences.
• Self-starter who is proactive, intellectually curious, and not afraid to seek out projects independently.
• Structured thinker with the ability to frame and reason through sophisticated business problems, even in the face of ambiguity or imperfect information.
• Strong communication and influencing skills, both verbal and written, as well as a collaborative mindset and approach to work.

10. Big Data Lead

Company: BARC India

Location: Mumbai, India

Job Summary

Manage Developments, Releases, and DevOps of high volume and complex data Processing Engine processing millions of rows every day using multiple processing algorithms and models. The chosen candidate should be able to handle multiple projects and be able to manage development cycles over multiple technology stacks.

Responsibilities

• Draft Understanding of big data requirements for providing solution design and managing development sprints.
• Documenting pipelines and strategizing automation.
• Document and manage end-to-end development, testing, and deployment tasks.
• Responsible for reviewing and optimizing existing ETL processes.
• Documentation and production support.
• Release management across multiple projects.
• Responsible for developing and managing workflows of various modules in the data validation pipeline.
• Delivery of big data reports over different data structures and transformation tools for resolving Ad-hoc business queries/reported bugs within SLAs.
• Delivering presentations to management on the team updates.
• Working knowledge for setting up cloud infrastructure and managing the same.

Qualifications

• Tech (Comp. Sc), BCA/MCA, or equivalent
• Minimum/Relevant Experience
• Total 10+ year experience
• 5+ years of experience in managing big data projects, and reports.
• 5+ years of experience in managing projects across technologies.
• 10 years of industry experience.
• Very strong and demonstrable hands-on experience managing Big Data Projects.
• Deep Knowledge of Hadoop, Spark, and Job Server Environment.
• Strong knowledge of Performance Tuning and Advanced Optimization.
• Knowledge of SQL / query languages and working with SQL as well as NoSQL databases.
• A good understanding of data structures and database management required.
• Analytical skills over Advanced SQL.
• Good knowledge of different technology stacks should be able to manage/mentor the development cycles.
• Expertise in High Volume Data Processing Production environment (not pilots or POCs).
• Knowledge of Git, SVN, and JIRA.
• Working knowledge on Jenkins.
• Good knowledge of AWS, EMR, and management of servers.
• Other programming languages like Java, C#, Kotlin, Objective C.
• Java Script frameworks like Angular/Vue/React.
• Good hold on Programming concepts like MVC, MVVC, Functional programming, OOP.
• Databases PostgreSQL and MongoDB

All the above information is taken from credible sources. To apply for the jobs above, visit the company’s official website and head over to the career section.

The post NOW HIRING! TOP BIG DATA JOB OPENINGS IN RENOWNED GLOBAL ORGANIZATIONS appeared first on Artificial Intelligence.

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Hadoop And Big Data Analytics Industrial Analysis: By Applications

Banking, Telecommunication, Healthcare, Transportation, Information Technology, Gaming and Public Organizations, Weather Forecasters

Hadoop And Big Data Analytics Business Market Trends: By Product

Hadoop Packaged Software, Hadoop Application Software, Hadoop Management Software, Hadoop Performance Monitoring Software

Hadoop And Big Data Analytics Market Segment : By Region

Asia Pacific

• China
• Japan
• India
• Southeast Asia
• Rest of Asia Pacific

North America

• U.S.Canada
• Rest of North America

Europe

• UK
• Germany
• France
• Italy
• Spain
• Rest of Europe

Latin America

• Brazil
• Argentina
• Rest of Latin America

The Middle East and Africa

• GCC Countries
• South Africa
• Rest of Middle East & Africa

TOC of 15 Key Chapters Covered in the Global Hadoop And Big Data Analytics Market: 

• Chapter 1::Industry Overview of Global Hadoop And Big Data Analytics Market;
• Chapter 2::Classification, Specifications and Definition of Hadoop And Big Data Analytics Market Segment by Regions;
• Chapter 3::Industry Suppliers, Manufacturing Process and Cost Structure, Chain Structure, Raw Material;
• Chapter 4::Specialized Information and Manufacturing Plants Analysis of Hadoop And Big Data Analytics, Limit and Business Production Rate, Manufacturing Plants Distribution::R&D Status and Technology Sources Analysis
• Chapter 5::Complete Market Research::Capacity::Sales and Sales Price Analysis with Company Segment
• Chapter 6::Analysis of Regional Market that contains the United States::Europe::India::China::Japan::Korea & Taiwan
• Chapter 7 & 8::Hadoop And Big Data Analytics Market Analysis by Major Manufacturers::The Hadoop And Big Data Analytics Segment Market Analysis (by Type) and (by Application)
• Chapter 9::Regional Market Trend Analysis, Market Trend by Product Type and by Application
• Chapter 10 & 11::Supply Chain Analysis, Regional Marketing Type Analysis::Global Trade Type Analysis
• Chapter 12::The Global Hadoop And Big Data Analytics industry consumers Analysis;
• Chapter 13::Research Findings/Conclusion, Hadoop And Big Data Analytics deals channel, traders, distributors::dealers analysis
• Chapter 14 and 15::Appendix and data source of Hadoop And Big Data Analytics market.

Key Highlights & Touch Points of the Hadoop And Big Data Analytics Market Worldwide for the Forecast Years 2020-2026:

•     CAGR of the market during the forecast period of 2020-2026
•     Extensive information on factors that will amplify the growth of the Hadoop And Big Data Analytics market over the upcoming seven years
•     Accurate estimation of the global Hadoop And Big Data Analytics market size
•     Exact estimations of the upcoming trends and changes observed in the consumer behavior
•     Growth of the global Hadoop And Big Data Analytics industry across the North & South America, Asia Pacific, EMEA, and Latin America
•     Information about Hadoop And Big Data Analytics market growth potential
•     In-depth analysis of the industry’s competitive landscape and detailed information vis-a-vis on various vendors
•     Furnishing of detailed information on the factors that will restrain the growth of the Hadoop And Big Data Analytics manufacturers

If you want Special Requirement or any other report Requirement, let us know about it, we will give you data as per your RESEARCH need sales@syndicatemarketresearch.com

About Syndicate Market Research:

At Syndicate Market Research, we provide reports about a range of industries such as healthcare & pharma, automotive, IT, insurance, security, packaging, electronics & semiconductors, medical devices, food & beverage, software & services, manufacturing & construction, defense aerospace, agriculture, consumer goods & retailing, and so on. Every aspect of the market is covered in the report along with its regional data. Syndicate Market Research committed to the requirements of our clients, offering tailored solutions best suitable for strategy development and execution to get substantial results. Above this, we will be available for our clients 24×7.

The post Global Hadoop And Big Data Analytics Market Devolopment Strategies by Top Leading Players|Know More| Forecast 2020-2026 appeared first on Artificial Intelligence.

In celebration of International Women’s Day, women data scientists from around the world will gather together virtually on March 7 and 8, 2021, for presentations, workshops and networking at the Women in Data Science (WiDS) Worldwide Conference. The event offers women in data science, a chance to recognize their social, economic, cultural and political achievements.

“Data science is the new gold or the new oil,” WiDS co-founder Dr. Margot Gerritsen said. “Data-driven decision making is in all aspects of our lives. It’s important that all sorts of genders, cultures and backgrounds are represented in this development.”

Like many women working in fields still dominated by men, Dr. Margot Gerritsen remembers the tipping point that inspired her to co-found WiDS with Karen Matthys. Invited to attend a conference by a male colleague, she noted that the event featured no women keynote speakers. Her colleague offered a familiar explanation: There were so few women in the field that he couldn’t find one to present at the event.

Less than a year later, the first WiDS Worldwide Conference proved him wrong: Over 6,000 people from around the world joined the conference livestream. By 2020, over 30,000 participants in more than 50 countries tuned in.

According to conference organizer Judy Logan, the WiDS Worldwide Conference has been global since its start. The initial conference livestream’s popularity showed co-directors Gerritsen, Logan and Matthys the international demand for collaboration and networking among women data scientists around the world.

The virtual nature of the conference allowed women to connect with one another across borders without the elitist registration and travel costs of other conventions. The WiDS Worldwide Conference encourages women in data science to establish their own national and regional networks while participating in a broader global conversation. As advocates recognize, data science needs diverse perspectives to determine the future of data-driven decision making in a world where data collection and analysis are increasingly (and unevenly) penetrating every aspect of peoples’ lives.

The opening presentations for this year’s conference include a fireside chat with Nobel Laureate and physicist Andrea Ghez—only the fourth woman to win the Nobel Prize for Physics—and a presentation by Emily Fox, distinguished engineer (Apple) and professor (University of Washington) on health and machine learning. Additional presentations center the work and research of data scientists working around the world.

For example, Dr. Kalinda Griffiths, a scientist at the Centre for Big Data Research in Health at the University of New South Wales, will discuss her research addressing health disparities among indigenous peoples, including how they have been defined and how identifications are operationalized in government data collections.

Dr. Fatima Abu Salem, associate professor of computer science at the American University of Beirut (AUB), will discuss “Doing Data Science in Data Deserts,” a presentation that looks at how grassroots initiatives are facilitating data collection efforts in countries where data is less abundant and accessible.

This year’s conference features the fourth incarnation of WiDS datathon, an event in which participants are given a dataset and a problem for which they must use their ingenuity and data science skills to explore solutions. This year’s datathon reflects WIDS’ commitment to solving problems with global ramifications: Datathon participants have been asked to create models to determine whether patients have been diagnosed with a certain type of diabetes that might improve ICU treatment.

The WiDS Worldwide Conference is open to all interested in ensuring that the future of data science is diverse and inclusive. Information about registration fees and platform can be found on the WIDS website.

The post Women in Data Science Initiative Holds Global Conference to Celebrate International Women’s Day appeared first on Artificial Intelligence.

*The retail industry has been one of worst-hit industries by the global pandemic.

*India is going to take a leadership role in AI for the world.

*There has never been a better time for AI ecosystem players and especially startups offering AI solutions.

The McKinsey Global Institute has recently studied economic statistics from the United Nations, the World Bank, and the World Economic Forum and estimated that by 2030, AI can add 16 percent—or around $13 trillion—to the global economy and AI will boost global GDP by $15.7 billion. Since 2000, AI venture investments have risen six times and McKinsey also estimates that by 2030, at least 70 percent of businesses are likely to have implemented at least one type of AI technology.

In India comparatively, Artificial Intelligence is a growing industry sector, as a report by Computer Vision Market reveals and stands at $6.4 billion as of 2030.  36.2 percent of this demand is coming from MNCs, GICs, and Captive firms with a market valuation of $2.3 billion. The future will see a vast number of other industries such as healthcare, high-tech manufacturing, and semiconductor companies adopting AI making it one of the most attractive and fastest-growing technology sectors over the next decade.

The retail industry has been one of worst-hit industries by the global pandemic and after an initial knee-jerk pause during the lockdowns, we see a sudden spike in retail brands (across categories of products) globally wanting to adopt and embrace digital transformation initiatives. The age-old model of customer service via call-centre’s has been disrupted permanently by Covid-19 and moving to AI solutions that can help retail businesses manage both exponential rise in call volumes while maintaining very high service level quality is the new emerging opportunity. It is, therefore, not a surprise that the conversational AI market alone is expected to grow at 32 percent CAGR to $9.4 billion by 2024 according to market research company markets & markets.

The Indian Government is playing a significant role as well and recently joined a Multinational Alliance on Artificial Intelligence that includes big nations such as the United States, the UK and Australia. Also, India has launched a Nationwide Artificial Intelligence Plan to bring the best of ideas and expertise from all fields and industries together making it one of the most happening and promising technology ecosystems to watch out for.

The National policymakers substantially expanded public AI funding through promises, such as increased R&D spending, the creation of industrial and construction funds by startups, network and technology investments, and public procurement relevant to AI. The government is also creating and fostering AI through numerous variations of public-private academies; the creation of technology parks and the connection between big companies and startups.

NASSCOM estimates that by 2022, 46% of the Indian workforce will be employed in completely new industries, which do not exist, or jobs that have drastically changed skill sets. NITI Ayog reports estimate that in India demand for AI and computer learners increased 60 percent in 2018. An Independent study has also stated that in 2020 India faced a demand-supply gap of 2,00,000d data analytics experts.

While global businesses have been at the forefront of adopting emerging technologies such as AI, blockchain, and IoT, Indian businesses have been traditionally late technology adopters. Owing to an in general risk-averse mindset culturally, only once a technology has been proven and tested at scale, Indian businesses are willing to adopt it and we see a similar trend even in AI and AI-based solutions.

However, the COVID-19 pandemic and subsequent lockdowns have reversed this trend completely and we see Indian businesses realize that adopting emerging technologies in today’s world is no longer an option that can be delayed any further. In many cases it can be the deciding factor between thriving, surviving, or perishing for the business. For example, at AskSid, where we offer a digital shopping assistant that help retail brands sell more, we have seen a drastic increase in demand in the last 6 months leading to a 3X-5X jump in our opportunity pipeline.

This increased adoption within businesses is being driven by the rapid usage and adoption of AI by consumers in their daily life. Alexa, Siri, Google as voice assistants are house-hold names today both in India and outside and the expectations to get served instantly in a personalized manner is considered totally normal by today’s consumers. Any business which fails to deliver on this high standard of customer experience which consumers demand carries the serious threat of becoming redundant very fast and therefore embracing digital transformation using emerging technologies such as AI is no longer an option for Indian businesses.To conclude the overall scenario, one thing that is evident in the global vs. Indian AI debate is that India is now no longer a laggard,

• India is going to take a leadership role in AI for the world. Indeed, through zealous technological advances and consistent R&D India can be the next artificial intelligence superpower. Indian firms and AI entrepreneurs must begin to invest more in research and to grow AI products and solutions from India.
• There has never been a better time for AI ecosystem players and especially startups offering AI solutions. There lie a huge market and humongous opportunity for budding entrepreneurs to tap into.

The post Artificial Intelligence: Global scenario versus Indian landscape appeared first on Artificial Intelligence.

“A SWOT Analysis of Data Science Platform, Professional Survey Report Including Top Most Global Players Analysis with CAGR and Stock Market Up and Down.”

The global “Data Science Platform market” research report is crafted with the concise assessment and extensive understanding of the realistic data of the global Data Science Platform market. Data collected cover various industry trends and demands linked with the manufacturing goods & services. The meticulous data gathered makes the strategic planning procedure simple. It also helps in creating leading tread alternatives. In addition, it also highlights the dominating players in the market joined with their market share. The well-established players in the market are Dataiku, IBM, Datarobot, Wolfram, Feature Labs, Google, Cloudera, Rexer Analytics, Continuum Analytics, Domino Data Lab, Datarpm, Rapidminer, Bridgei2i Analytics, Alteryx,Microsoft.

Click here to access the report

Most of the data is presented in the form of graphical demonstration with accurately intended figures. The performance of the related key participants, suppliers, and vendors is furthermore explained in the global Data Science Platform report. It also underscores the restraints and drivers keenly from the prudent perceptive of our specialists. Additionally, the global Data Science Platform market report covers the major product categories and segments On-Premises, On-Demand along with their sub-segments Marketing, Sales, Logistics, Risk, Customer Support, Human Resources, Operations in detail.

The perfect demonstration of the most recent improvements and latest technologies offers the user with a free hand to grow ultramodern products and procedures to update the service offering. This ultimately helps to work with perfect business options and apply smart implementations. The global Data Science Platform report highlights the latest trends, growth, new opportunities, and dormant tricks to provide an inclusive view of the global Data Science Platform market. Demand proportion and development of innovative technologies are some of the key points explained in the global Data Science Platform market research report.

The research report also highlights the in-depth analysis of various decisive parameters such as profit & loss statistics, product value, production capability, and many more. The report showcases back-to-back parameters such as application, improvement, product growth, and varied structures & processes. It also highlights a variety of modifications done to improve the process functioning of the global Data Science Platform market.

A well-crafted Data Science Platform market research report is based on the primary and secondary source. It is presented in a more communicative and expressed format that allows the customer to set up a complete plan for the development and growth of their businesses for the anticipated period.

The additional geographical segments are also mentioned in the empirical report.

North America: U.S., Canada, Rest of North America
Europe: UK, Germany, France, Italy, Spain, Rest of Europe
Asia Pacific: China, Japan, India, Southeast Asia, North Korea, South Korea, Rest of Asia Pacific
Latin America: Brazil, Argentina, Rest of Latin America
Middle East and Africa: GCC Countries, South Africa, Rest of Middle East & Africa

Impact Of COVID-19

The most recent report includes extensive coverage of the significant impact of the COVID-19 pandemic on the Heated Jacket division. The coronavirus epidemic is having an enormous impact on the global economic landscape and thus on this special line of business. Therefore, the report offers the reader a clear concept of the current scenario of this line of business and estimates the aftermath of COVID-19.

There are 15 Chapters to display the Global Data Science Platform market

Chapter 1, Definition, Specifications and Classification of Data Science Platform, Applications of Data Science Platform, Market Segment by Regions;
Chapter 2, Manufacturing Cost Structure, Raw Material and Suppliers, Manufacturing Process, Industry Chain Structure;
Chapter 3, Technical Data and Manufacturing Plants Analysis of Data Science Platform, Capacity and Commercial Production Date, Manufacturing Plants Distribution, R&D Status and Technology Source, Raw Materials Sources Analysis;
Chapter 4, Overall Market Analysis, Capacity Analysis (Company Segment), Sales Analysis (Company Segment), Sales Price Analysis (Company Segment);
Chapter 5 and 6, Regional Market Analysis that includes United States, China, Europe, Japan, Korea & Taiwan, Data Science Platform Segment Market Analysis (by Type);
Chapter 7 and 8, The Data Science Platform Segment Market Analysis (by Application) Major Manufacturers Analysis of Data Science Platform ;
Chapter 9, Market Trend Analysis, Regional Market Trend, Market Trend by Product Type On-Premises, On-Demand, Market Trend by Application Marketing, Sales, Logistics, Risk, Customer Support, Human Resources, Operations;
Chapter 10, Regional Marketing Type Analysis, International Trade Type Analysis, Supply Chain Analysis;
Chapter 11, The Consumers Analysis of Global Data Science Platform ;
Chapter 12, Data Science Platform Research Findings and Conclusion, Appendix, methodology and data source;
Chapter 13, 14 and 15, Data Science Platform sales channel, distributors, traders, dealers, Research Findings and Conclusion, appendix and data source.

Reasons for Buying Data Science Platform market

• This report provides pin-point analysis for changing competitive dynamics
• It provides a forward looking perspective on different factors driving or restraining market growth
• It provides a six-year forecast assessed on the basis of how the market is predicted to grow
• It helps in understanding the key product segments and their future
• It provides pin point analysis of changing competition dynamics and keeps you ahead of competitors
• It helps in making informed business decisions by having complete insights of market and by making in-depth analysis of market segments

Thanks for reading this article; you can also get individual chapter wise section or region wise report version like North America, Europe or Asia.

About Syndicate Market Research:

At Syndicate Market Research, we provide reports about a range of industries such as healthcare & pharma, automotive, IT, insurance, security, packaging, electronics & semiconductors, medical devices, food & beverage, software & services, manufacturing & construction, defense aerospace, agriculture, consumer goods & retailing, and so on. Every aspect of the market is covered in the report along with its regional data. Syndicate Market Research committed to the requirements of our clients, offering tailored solutions best suitable for strategy development and execution to get substantial results. Above this, we will be available for our clients 24×7.

The post Global Data Science Platform Market Size, Share & Trends Analysis Report 2021-2027 appeared first on Artificial Intelligence.

The Deep Learning Market size is expected to grow at an annual average of 38.2% during 2021-2027. DC control tools are systems used to hold torque and automation processes and provide accurate, accurate and repeatable torque control. Torque fixing system manufacturers can optimize the assembly area due to their high performance, reduce labor costs and increase productivity.

(Get 15% Discount on Buying this Report)

A full report of Deep Learning Market is available at:
https://www.orionmarketreports.com/deep-learning-market-market/46630/

The following segmentation are covered in this report:

By Application
• Image recognition
• Voice recognition
• Video surveillance & diagnostics
• Data mining

By Solution
• Hardware
• Software
• Service

By End-use
• Automotive
• Aerospace & defense
• Healthcare
• Manufacturing
• Others

Company Profiles
• Facebook Inc.
• Google
• Amazon Web Services Inc
• SAS Institute Inc
• Microsoft Corporation
• IBM Corp

Reasons to Buying From us –
• We cover more than 15 major industries, further segmented into more than 90 sectors.
• More than 120 countries are for analysis.
• Over 100+ paid data sources mined for investigation.
• Our expert research analysts answer all your questions before and after purchasing your report.

Scope of the report
The research study analyses the Deep Learning Market industry from 360-degree analysis of the market thoroughly delivering insights into the market for better business decisions, considering multiple aspects some of which are listed below as:

Recent developments
• Market overview and growth analysis
• Import and export overview
• Volume analysis
• Current market trends and future outlook
• Market opportunistic and attractive investment segment

Geographic coverage
• North america market size and/or volume
• Latin america market size and/or volume
• Europe market size and/or volume
• Asia-pacific market size and/or volume
• Rest of the world market size and/or volume

Key questions answered by lighting control system market report
• What was the Deep Learning Market size in 2018 and 2019; what are the estimated growth trends and market forecast (2019-2025).
• What will be the cagr of lighting control system market during the forecast period (2019-2025)?
• Which segments (product type/applications/end-user) were most attractive for investments in 2018? how these segments are expected to grow during the forecast period (2019-2025).
• Which manufacturer/vendor/players in the lighting control system market was the market leader in 2018?
• Overview on the existing product portfolio, products in the pipeline, and strategic initiatives taken by key vendors in the market.

The post Deep Learning Market – Global Industry Analysis, Size, Share, Growth, Trends and Forecast 2021-2027 appeared first on Artificial Intelligence.

Dublin, Feb. 04, 2021 (GLOBE NEWSWIRE) — The “Machine Learning Market – Global Industry Analysis, Size, Share, Growth, Trends, and Forecast, 2020-2030” report has been added to ResearchAndMarkets.com’s offering.

A latest study collated and analyzes the historical and present-day scenario of the global machine learning market to accurately gauge its potential future development. The study presents detailed information about the important growth factors, restraints, and key trends that are creating the landscape for the future growth of the machine learning market, to identify the opportunistic avenues of the business potential for stakeholders. The report also provides insightful information about how the machine learning market will progress during the forecast period, 2020 – 2030.

The report offers intricate dynamics about the different aspects of the machine learning market, which aids companies operating in the market in making strategic development decisions. This study also elaborates on the significant changes that are highly anticipated to configure the growth of the machine learning market during the forecast period. It also includes impact analysis of COVID-19 on the machine learning market. The global machine learning market report helps to estimate statistics related to the market progress in terms of value (US$ Bn).

The study covers a detailed segmentation of the machine learning market, along with key information and a competitive outlook. The report mentions the company profiles of key players currently dominating the machine learning market, wherein various developments, expansions, and winning strategies practiced and executed by leading players have been presented in detail.

Key Questions Answered in this Report on Machine Learning Market

The report provides detailed information about the machine learning market on the basis of comprehensive research on various factors that play a key role in accelerating the growth potential of the market. Information mentioned in the report answers path-breaking questions for companies that are currently functioning in the market and are looking for innovative ways to create a unique benchmark in the machine learning market, so as to help them formulate successful strategies and take target-driven decisions.

• How are key market players successfully earning revenue out of machine learning?
• What will be the Y-o-Y growth of the machine learning market between 2020 and 2030?
• What are the winning imperatives of market frontrunners in the machine learning market?
• What are the major drivers and restraints of the market?
• What will be the size of the machine learning market from 2020 to 2030?
• Which will be the fastest growing segment in the machine learning market?
• Which are the leading companies in the machine learning market?
• What are the strategies of companies operating in the market?

Key Topics Covered:

1. Preface
1.1. Market Introduction
1.2. Market Segmentation
1.3. Key Research Objectives

2. Assumptions and Research Methodology
2.1. Research Methodology
2.2. Key Assumptions for Data Modelling

3. Executive Summary – Global Machine Learning Market

4. Market Overview
4.1. Market Definition
4.2. Market Factor Analysis
4.3. Market Opportunity Assessment
4.4. Competitive Scenario and Trends
4.5. Impact Analysis of COVID-19 on the Machine Learning Market
4.6. Analysis of Machine Learning Market, By Application
4.7. Market Outlook

5. Global Machine Learning Market Analysis and Forecast

6. Global Machine Learning Market Analysis, by Component
6.1. Key Segment Analysis
6.2. Machine Learning Market Size (US$ Bn) Forecast, by Component, 2018 – 2030

7. Global Machine Learning Market Analysis, by Enterprise Size
7.1. Key Segment Analysis
7.2. Machine Learning Market Size (US$ Bn) Forecast, by Enterprise Size, 2018 – 2030

8. Global Machine Learning Market Analysis, by End-user
8.1. Key Segment Analysis
8.2. Machine Learning Market Size (US$ Bn) Forecast, by End-user, 2018 – 2030

9. Global Machine Learning Market Analysis and Forecast, By Region
9.1. Key Findings
9.2. Machine Learning Market Size (US$ Bn) Forecast, by Region, 2018 – 2030

10. North America Machine Learning Market Analysis
10.1. Regional Outlook
10.2. Machine Learning Market Size (US$ Bn) Analysis and Forecast (2018 – 2030)
10.3. Machine Learning Market Size (US$ Bn) Forecast, by Country, 2018 – 2030

11. Europe Machine Learning Market Analysis and Forecast
11.1. Regional Outlook
11.2. Machine Learning Market Size (US$ Bn) Analysis and Forecast (2018 – 2030)
11.3. Machine Learning Market Size (US$ Bn) Forecast, by Country & Sub-region, 2018 – 2030

12. Asia Pacific Machine Learning Market Analysis and Forecast
12.1. Regional Outlook
12.2. Machine Learning Market Size (US$ Bn) Analysis and Forecast (2018 – 2030)
12.3. Machine Learning Market Size (US$ Bn) Forecast, by Country & Sub-region, 2018 – 2030

13. Middle East & Africa Machine Learning Market Analysis and Forecast
13.1. Regional Outlook
13.2. Machine Learning Market Size (US$ Bn) Analysis and Forecast (2018 – 2030)
13.3. Machine Learning Market Size (US$ Bn) Forecast, by Country & Sub-region, 2018 – 2030

14. South America Machine Learning Market Analysis and Forecast
14.1. Regional Outlook
14.2. Machine Learning Market Size (US$ Bn) Analysis and Forecast (2018 – 2030)
14.3. Machine Learning Market Size (US$ Bn) Forecast, by Country & Sub-region, 2018 – 2030

15. Competition Landscape
15.1. Market Competition Matrix, by Prominent Players
15.2. Market Revenue Share Analysis (%), by Prominent Players (2019)

16. Company Profiles
16.1. Amazon Web Services, Inc.
16.2. BigML Inc.
16.3. DeepL GmbH
16.4. Ersatz Labs Inc.
16.5. Featurespace Limited
16.6. FICO
16.7. Formulate AB
16.8. German Auto Labs GAL GmbH
16.9. Google LLC
16.10. H2O.ai
16.11. Heuritech
16.12. Hewlett Packard Enterprise Development LP
16.13. IBM Corporation
16.14. InstaDeep Ltd
16.15. Microsoft Corporation
16.16. MySales Labs Ltd
16.17. Oracle Corporation
16.18. SAP SE
16.19. SAS Institute Inc.
16.20. understandAI GmbH

The post Global Machine Learning Market (2020 to 2030) – Industry Analysis, Size, Share, Growth, Trends, and Forecasts appeared first on Artificial Intelligence.

This market report plots an intentional review of macroeconomic signs, parent affiliations, and new startup adventures. The report gives the customers data identified with classes, for instance, augmentation, divisions, and locales, expose type, and applications. This market report exhibits the rapidly creating conditions, the top dimension appearing at do genuine execution and settle on worthwhile decisions for advancement and prospering ahead. This market report speaks to a precise methodology of key data that would be given to customers who are searching for it. This report can guide the client to choose the correct strides in basic leadership and key plans that can be useful in the market.

This market research report joins the latest mechanical overhauls and new releases to interface with the clients to design, settle on smart business decisions, and complete their future required executions. The report focuses more on current business and developments, future framework changes, and opportunities and trends that the market is experiencing or going to experience. The report additionally portrays the primary players and how they perform in the market all through. It reveals insight into their financials, SWOT analysis, review, significant and late improvements, developments, and so on

Cloud microservices market is expected to grow at a CAGR of 21.7% in the forecast period of 2020 to 2027. Data Bridge Market Research report on cloud microservices market provides analysis and insights regarding the various factors expected to be prevalent throughout the forecasted period while providing their impacts on the market’s growth.

The global cloud microservices market accounted for USD 631.1 million in 2017 and is projected to grow at a CAGR of 24.1% forecast to 2025.

The renowned players in cloud microservices market are

• Amazon Web Services, Inc.,
• CA Technologies.,
• IBM,
• Microsoft,
• Infosys Limited,
• NGINX Inc.,
• Oracle,
• Pivotal Software, Inc.,
• Syntel, Inc.,
• Gurock,

Marlabs Inc., RapidValue Solutions, Kontena, Inc., Macaw Software Inc.,  UNIFYED.,  Idexcel, Inc. and among others.

The titled segments and sub-section of the market are illuminated below:

• The global cloud microservices market is based on component, organization size, deployment mode, vertical and geographical segments.
• Based on component, the global cloud microservices market is segmented into platform and services. Service is sub segmented into consulting services, integration services, training, support, and maintenance services.
• Based on organization size, the global cloud microservices market is segmented into large enterprises  and small and medium-sized enterprises.
• Based on Deployment Mode, the global cloud microservices market is segmented into public cloud, private cloud and hybrid cloud.
• Based on vertical, the global cloud microservices market is segmented into retail and ecommerce, healthcare, media and entertainment, banking, financial services, and insurance, IT AND ITes, government, transportation and logistics, manufacturing, telecommunication and others).

The regions that have been considered in the study are:

North America

Europe

Asia Pacific

Latin America

Middle East and Africa

The report is inclusive of all the information that is valuable for market entrants. This will enhance the ability of the user to foresee trends and make beneficial and informed decisions. The report is also available for customization according to the requests of the user. These help in detailing the report around the regions or participants that comes under the users’ concern and targets.

Key Coverage of Report:

Total addressable market

Regional analysis [North America, Europe, Asia Pacific, Latin America, Middle East & Africa]

Country-wise market segmentation

Market size breakdown by the product/ service types

Market size breakdown by application/industry verticals/ end-users

Market share and revenue/sales of the key players in the market

Production capacity of prominent players

Market Trends like emerging technologies/products/start-ups, SWOT Analysis, Porter’s Five Forces, and others.

Pricing Trend Analysis

Brand wise ranking of the key market players worldwide

Sales Forecast:

The report contains historical revenue and volume that backing information about the market capacity, and it helps to evaluate conjecture numbers for key areas in the Cloud Microservices market. Additionally, it includes a share of each segment of the Cloud Microservices market, giving methodical information about types and applications of the market.

Reasons for Buying Cloud Microservices Market Report

This report gives a forward-looking prospect of various factors driving or restraining market growth.

It renders an in-depth analysis for changing competitive dynamics.

It presents a detailed analysis of changing competition dynamics and puts you ahead of competitors.

It gives a six-year forecast evaluated on the basis of how the market is predicted to grow.

It assists in making informed business decisions by performing a pin-point analysis of market segments and by having complete insights of the Cloud Microservices market.

This report helps the readers understand key product segments and their future.

Which emerging technologies are believed to impact the Cloud Microservices market performance?

Which regulations that will impact the industry?

Who are the most prominent vendors and how much market share do they occupy?

What are the latest technologies or discoveries influencing the Cloud Microservices market growth worldwide?

(**NOTE: Our analysts monitoring the situation across the globe explains that the market will generate remunerative prospects for producers post COVID-19 crisis. The report aims to provide an additional illustration of the latest scenario, economic slowdown, and COVID-19 impact on the overall industry.)

About Data Bridge Market Research:

An absolute way to forecast what future holds is to comprehend the trend today!

Data Bridge set forth itself as an unconventional and neoteric Market research and consulting firm with unparalleled level of resilience and integrated approaches. We are determined to unearth the best market opportunities and foster efficient information for your business to thrive in the market. Data Bridge endeavors to provide appropriate solutions to the complex business challenges and initiates an effortless decision-making process. Data bridge is an aftermath of sheer wisdom and experience which was formulated and framed in the year 2015 in Pune.

The post Global Cloud Microservices Market Recent Study of Business Strategies and Latest Rising Trend appeared first on Artificial Intelligence.