Artificial intelligence is playing a vital role in processing the big data sets of industrial companies.

Artificial intelligence is being used by large industrial companies to analyze their long array of unstructured datasets and put them into smart use. AI is creating analytics models that are creating accurate operating strategies based on variables like pump speed or weather. To be successful in this process, the big industries must know how to create an amenable environment for AI to work properly with their big datasets.

The Making of Smart Data

There is a five-step approach that can be adapted to process the big datasets into smart data. First of all, the steps of the process must be outlined, along with addressing the physical and chemical changes like grinding, heating, oxidation, and polymerization. The process flow of the operation should be labeled using paint schematics or engineering drawing. In the next step, the non-standard operating regimes should be removed. A common data science approach should be used to engineer input combinations to produce new features. When combined with the sheer number of sensors available in modern plants, this demands a massive number of observations. Instead, teams should prepare the features list to include only those inputs that describe the physical process, and then they should apply deterministic equations to create features that intelligently combine sensor information.

The sensor calibrations should be addressed and a high-quality dataset should be built. The next phase of the process would be to leverage the engineering formulas to combine the sensor data in an intelligent manner.

In the next step, advanced analytic models should be overlaid on engineered data for capturing the stochastic variability. Teams should evaluate features by inspecting their importance and therefore their explanatory power. Ideally, expert-engineered features that capture, for example, the physics of the process should rank among the most important. Overall, the focus should be on creating models that drive plant improvement, as opposed to tuning a model to achieve the highest predictive accuracy. Teams should bear in mind that process data naturally exhibit high correlations. In some cases, model performance can appear excellent, but it is more important to isolate the causal components and controllable variables than to solely rely on correlations. The last step includes checking casualties and ensuring the facts that the results are physical.

The Making of Analytics Team

The team responsible for the implementation of AI must have a variety of members from operators to data scientists, automation engineers, and process experts. Companies that are looking to implement AI generally need to rebuild their expert pipeline initially. Knowing the skills is the most important factor when it comes to choosing the perfect process expert. Planning out the model development can be a good exercise to solidify a way of working and avoid linear approaches that include exhaustively completing one stage before proceeding to the next. Later the team can decide what to invest in for the next stage.

Industrial companies are looking to AI to boost their plant operations, reduce downtime, proactively schedule maintenance, improve product quality, and so on. However, achieving operational impact from AI is not easy. To be successful, these companies will need to engineer their big data to include knowledge of the operations. The cross-functional data science teams should include employees who are capable of bridging the gap between machine learning approaches and process knowledge. Once these elements are combined with an agile way of working that advocates iterative improvement and a bias to implement findings, a true transformation can be achieved.

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The Beijing International Big Data Exchange, which was set up in the capital city on Wednesday with a registered capital of 200 million yuan ($30.46 million), is expected to play a key role in China’s digital economy promotion efforts and facilitate more data-based transactions in the country.

Established by Beijing Financial Holdings Group and government agencies like the Beijing Municipal Bureau of Economy and Information Technology, the exchange will become critical infrastructure for data security, data operations and cross-border data transactions.

“It will play an important role in cultivating a sound data exchange market to unleash the value of data and drive digital economy. It will be first applied in Beijing, Tianjin and Hebei province and expanded nationwide and globally later,” said Yin Yong, vice-mayor of Beijing.

A data transaction system using blockchain and security computing technology was also launched, which will offer a series of services including data cleaning and data evaluation.

Fan Wenzhong, Party secretary and chairman of Beijing Financial Holdings Group, said: “The new exchange will strive to make the purchase and use of data more standardized and safer.”

The digital economy is a key focus for China in the 14th Five-Year Plan period (2021-25). Core industrial output is expected to account for 10 percent of the country’s GDP by 2025.

China’s digital trade has grown rapidly in the last few years. According to the Ministry of Commerce, the country’s digital trade, including exports and imports, surged by 6.7 percent to $203.6 billion in 2019, accounting for 26 percent of the total service trade volume.

“In this increasingly digital era of globalization, countries led by the US are striving to seize the high ground of digital trade,” said Liu Yingkui, head of international trade at the Academy of China Council for the Promotion of International Trade.

According to a report published by global consultancy firm McKinsey&Co, large gaps exist between a handful of leading countries and the rest of the world. The report ranked 139 countries on the basis of inflows and outflows of goods, services, finance, people and data. Singapore led the rankings, followed by the Netherlands, the United States and Germany.

China has grown more connected, reaching seventh place globally, but advanced economies in general remain more connected than developing countries.

Liu said China has accumulated a huge amount of data and data streams in a group of areas, including trans-border e-commerce and superfast 5G development. These are valuable foundations for the development of the digital economy.

“Once more companies join, the platform can leverage data and artificial intelligence to optimize industrial software and fill the gaps in industrial development with developed countries,” he said.

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BOSCH Sensortec has released the first gas sensor with artificial intelligence. The BME688 is an innovative four-in-one air quality measurement solution that combines gas, humidity, temperature, and barometric pressure sensing with artificial intelligence.

The BME688 is a MEMS gas sensor with artificial intelligence, integrated high-linearity, and high accuracy pressure, temperature, and humidity sensors. It has been specially designed for applications where small size and low power consumption are essential. Therefore, the gas sensor is a compact 3.0 x 3.0 x 0.9 mm³ package.

The gas sensor can detect most volatile compounds and many other gases which pollute indoor air. It also features a gas scanner function that enables the customization of the sensor’s sensitivity, selectivity, data rate, and power consumption.

Artificial intelligence is commonly known as being used in large system applications, such as autonomous vehicles and building management. With this new development, BOSCH has incorporated artificial intelligence into a compact system which opens it up to many more applications.

The BME688 has been designed for the BME AI-studio tool. This machine-learning system allows users to train the gas scanner for their specific application.

BOSCH Sensortec develops and markets MEMS sensors and solutions for various applications, including smart devices, AR/VR devices, drones, and robots. The first gas sensor with artificial intelligence is a unique and innovative product to add to its portfolio.

An In-depth Look at the BME688

The BME688 has a broad sensitivity and can accurately measure gases, humidity, temperature, and barometric pressure.

The gas sensor can detect Volatile Organic Compounds (VOCs), Volatile Sulfur Compounds (VSCs), and other gases such as carbon monoxide and hydrogen. The signal intensity typically scales with the chemical reactivity of the gas.

While other gas sensors are selective for a single specific component, the BME688 can measure the sums of contaminants in the air, giving a more accurate picture of the surroundings.

At room temperature, the temperature sensor has an absolute accuracy of ±0.5 °C. It can be used for temperature compensation of the gas, humidity, and pressure sensors, as well as estimating ambient temperature. 

The pressure sensor has exceptionally high accuracy and very low noise resolution, with a sensitivity error of ±0.25%. The humidity sensor is also highly accurate, with an accuracy tolerance of ±3%, and has a fast response time of eight seconds.

The BME668 supports an array of operating modes, making it easy to optimize for different uses. Various power modes add to the product’s customization further as each one is designed with a specific application in mind.

BOSCH Sensortec’s proven BME680 model progression, the BME688 gas sensor, has been updated to offer an extended measurement range along with innovative artificial intelligence features. Both models are in a compact package made up of an 8-pin Land Grid Array (LGA) with metal.

Being the first gas sensor with artificial intelligence, the BME688 is a novel product that is ideal for developing new applications. Not only can it collect data on the concentration of gases, but artificial intelligence also allows for the determination of possible causes based on programs users can build in the BME AI-studio.

BME AI-studio makes the product’s customization easily accessible, as the system does not require data scientists or specialists. It can be programmed by specifying the recognition outcomes for each sample of sensor data collected. This makes the BME688 optimal for the rapid development of custom solutions for specific cases and applications.

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Over the past twenty years, Eyebeam has provided robust professional and financial support to nearly five hundred artists to engage society’s relationship with technology.

To advance this mission, the organization is inviting applications for its Rapid Response For A Better Digital Future program. In light of current circumstances related to the COVID-19 pandemic, Eyebeam seeks to help artists positioned to create new ways of interacting through the Internet, new ways of engaging with each other, and more equitable relationships with  respect to sustainable arts practices and creative economies. The program is based on the fundamental notion that radical imagination, led by artists, is a key step in building for the long term and, to that end, invites artists to submit ideas for actionable projects that enact solutions for the of rebuilding digital systems and improve the overlap and interplay between those systems and lived social experience. The guiding question for this call is: How do we begin to exit surveillance capitalism as the dominating form of digital life and what can replace it?

The program will unfold two phases: in phase 1, a dozen planning/idea stage grants of $5,000 each will be awarded; in phase 2, the project/development phase, three of those recipients, based on the potential of their ideas to have real-world impact, will be awarded up to an additional $20,000 to build their ideas into actionable projects.

Eyebeam will prioritize work that addresses new, online public spheres; ethical or values-driven technology; health and well-being; the development of public policy; efforts to create space for imagination; individual autonomy, borders, and immigration; new and necessary skills; democratic engagement and fortification; the impacts of Covid-19; the accessibility of online platforms; and artificial and natural intelligence.

Individuals and collaborative projects are eligible to apply. A single person (21 years or older) must be responsible for committing for the term of engagement and serve as the point person for communications and payments. International applicants are welcome and encouraged to apply and are not required to live or work in the United States during the grant period. (Note: the program is being run virtually.)

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VentureBeat’s AI event of the year for enterprise decision-makers, Transform 2020, is shifting to an online-only event to protect our community amid concerns around the coronavirus.

Transform 2020 will be held online July 15-17, expanding to three days from two. Each day is dedicated to a big theme in AI, including the Conversational AI Summit, and the Technology & Automation Summit. The third day will focus on IoT & AI at the Edge, and Computer Vision.

VentureBeat is providing a way for the AI business community to experience virtually the same engaging experiences of in-person events. For example, we’re adding digital equivalents for networking, one-to-one meetings, match-making, and live Q&A with speakers.

VentureBeat is the leading publisher of AI content coverage, and brings its AI expertise, reach and network to bear at Transform. VB’s AI channel receives 20 million page views a year, and has a social reach of 1.5 million. News coverage from Transform alone generates more than a million page views. Transform gathers together 750 executives who are director and above to discuss the best practices in applied enterprise AI. Transform also offers invite-only experiences for the VP level-and-above executives who come every year.

The event features keynote speakers from companies like Google, Intuit, Walmart, Pinterest, Salesforce, Adobe, AWS, Chase, Goldman Sachs, PayPal, Doordash, Visa, and Disney — plus from a growing list of sponsors, including Intel, Dataiku, Capital One, Booz Allen Hamilton, and Two Hat Security. Other speakers include leading AI professors from academia, including Stanford and Berkeley. Transform will also host its popular Women-in-AI breakfast, sponsored by Intel and Capital One. Transform will include a focus on diversity and inclusion topics, reflecting how ethics has become an important part of smart AI practice, and host its 2nd annual AI Innovation Awards.

VentureBeat’s virtual event will allow AI innovators and leading executives from around the world to partake despite ongoing challenges surrounding the outbreak. We expect the digital options we’re planning may allow even more people to participate than had it been offline — expanding the experience to an even wider group of businesses and executives.

As part of our digital offering, attendees will be able to view live sessions with AI leaders, join networking sessions, engage in digital roundtables, take part in our AI expo and Tech Showcase online, and participate in 1:1 meetings with world-class AI providers.

“With Transform being the only significant digital AI event for business executives on the map for 2020, it’s important we take leadership in the community, and support dialogue and networking for decision-making around AI,” said Matt Marshall, founder and CEO of VentureBeat. “We’ve created a virtual event platform for networking and 1:1 meetings to happen — so that we can bring thought leaders in AI together.”

Interested investors, vendors, and business executives can register here to join the event online. For companies interested in partnerships, we have innovative and high impact custom solutions in place for all the components for our strategic sponsors.

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Bank Mandiri is acting on ambitions to embrace digital transformation in Indonesia through the deployment of cloud and artificial intelligence (AI) technologies in partnership with Microsoft.

Alongside increasing market competitiveness, the collaboration is designed to enhance customer satisfaction, risk management, employee collaboration and business processes across the organisation.

“With the aspiration to be Indonesia’s best and ASEAN’s prominent financial services company, Bank Mandiri sees this collaboration as a strategic initiative to deal with more complex needs of our clients, and to tap into the fast-paced growth of digital financial services in Indonesia,” said Royke Tumilaar, president director of Bank Mandiri.

Revealed on the sidelines of DevCon – Digital Economy Summit 2020 in Jakarta – headlined by Satya Nadella as CEO of Microsoft – the adoption of cloud, AI and machine learning solutions will help analyse millions of records and data points at the country’s largest banking institution.

The aim is to provide a knowledge graph of related information for better decision making, including credit risk evaluation and shortening the process for data processing, preparation and governance.

“Microsoft is pleased to help Bank Mandiri accelerate its digital transformation journey with our AI and intelligent cloud solutions,” added Haris Izmee, president director of Indonesia at Microsoft.

As a long time customer of Microsoft, Izmee said Bank Mandiri represents “one of many visionary adopters” of digital workplace solutions as part of plans to enhance workforce productivity and competitiveness.

“Industries like financial institutions will need to look at emerging technologies to find success in this new landscape, and we look forward to enable the transformation across every line of their business,” Izmee added.

As reported by Channel Asia, Nadella addressed more than 2500 developers, start-ups and entrepreneurs in Jakarta, as Microsoft made its partner priorities clear in Indonesia. In delivering the keynote in Jakarta, Nadella outlined the vendor’s strategy for driving developer success in Southeast Asia, with enhanced Azure capabilities featuring heavily.

The appearance also triggered speculation that the technology giant was exploring the option of building data centres in Indonesia, potentially joining fellow cloud giants Amazon Web Services (AWS) and Google Cloud in an increasingly competitive Southeast Asia market.

That was according to Joko Widodo – president of Indonesia – who claimed that “simple regulation” will be created to facilitate such a move in the country.

“Microsoft wants to invest immediately in Indonesia,” said Widodo, when addressing media during the conference. “So within a week we will decide a new, simple regulation to support the investment.”

The increased collaboration with Bank Mandiri also follows Microsoft’s recent partnership with Telkomsel to provide outlying regions in Indonesia with enhanced connectivity and solutions, underpinned by cloud and network technologies.

As reported by Channel Asia, the alliance is designed to emulate the digital offerings currently available in major cities across the country, aligned to Industry 4.0 priorities in Indonesia.

Specifically, the agreement is centred around “technical collaboration” between Microsoft’s cloud capabilities – including cloud edge, AI, Internet of Things (IoT) and data hubs – coupled with Telkomsel’s network solutions to offer lower latency between devices and the cloud, at both consumer and business levels.

According to IDC findings, commissioned by Microsoft in 2019, Indonesian companies using AI can expect to increase innovation rates by 1.7 times, alongside boosting employee productivity by 1.9 times within the next three years.

The top five business drivers of AI adoption in Indonesia rank as improved customer engagement (40 per cent); higher competitiveness (17 per cent); higher margins (14 per cent); accelerated innovation (11 per cent) and productive employees (six per cent).

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Petrofac has chosen Microsoft Azure’s Internet of Things for its Connected Construction platform designed to accelerate digital transformation at its project worksites.

“Microsoft’s mission is to empower every individual and organisation on the planet to achieve more,” said Sayed Hashish, general manager, Microsoft UAE. “Petrofac serves some of the largest oil, gas and renewable energy companies in the world and is known as a leader in its segment. The company is well underway with its digital transformation journey. Its potential to engage customers, empower employees and optimize operations for assured and ultra-efficient service delivery has been accelerated by the power of the intelligent cloud and the intelligent edge.”

In conjunction with Accenture Industry X.0, Petrofac developed Connected Construction on Azure and combined it with Azure IoT Edge analytics and PaaS cloud components to create a scalable ecosystem capable of accommodating many different types and sizes of project.

“Petrofac designs, builds, operates and maintains energy facilities, supporting our customers to unlock more value across the life cycle of an asset,” said Fady Sleiman, chief digital officer, Petrofac. “We’re future-proofing our business, combining technology with our engineering, construction and operations know-how to find new solutions to today’s challenges. With Microsoft and Accenture, we’ve created Connected Construction which tracks people, equipment and materials on site, enabling real-time insights and decision making which, in turn, improves performance.”

Azure’s IoT platform allows innovators to build visual Internet of Things applications that connect, manage, and monitor devices securely and at scale. With the options to run SaaS or PaaS deployment models, solutions builders can deliver real edge intelligence to field operatives that allows data-driven decisions through machine learning and advanced analytics. Azure IoT Edge moves cloud analytics and custom business logic to devices for organisations that prioritise business insights over data management, allowing them to scale out solutions by packaging heuristics into standard containers, deploying them to edge devices and monitoring everything from the cloud.

Following a significant surge in the demand for its cloud services in the region, Microsoft earlier this year launched its intelligent cloud to regional customers through two dedicated cloud data centres, one in Dubai and one in Abu Dhabi. These facilities will cater specifically to enterprises in the Middle East. 

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Oil and gas assets are increasingly fitted with a multitude of Internet of Things (IoT) sensors, causing exponential growth in data. This, in turn, is increasing the need for adoption of data management solutions for improved operational visibility. This approach also helps identify bottlenecks in operations and uncover patterns and relationships across diverse entities, says GlobalData, a leading data and analytics company.

GlobalData’s latest thematic report, ‘Big Data in Oil & Gas’, discusses how growing dependence on data from oil and gas operations is compelling the industry to adopt big data solutions.

Ravindra Puranik, Oil and Gas Analyst at GlobalData, comments: “The oil and gas industry has always generated huge volumes of data daily across the value chain. However, despite being awash with money it has been poor at data management. It is only when profits drop that the industry starts to investigate how to use data to improve operational efficiency. However, this laissez-faire approach is less prevalent now. Many players, across the value chain, are taking an enterprise-wide view to data, and applying analytics to improve existing business processes and to develop new revenue streams.”

Data management is a very complex process, particularly given that much of an oil company’s upstream data is created on remote assets and often stored in disparate, disconnected infrastructure. Moreover, there is a paucity of data scientists with a working knowledge of the oil and gas industry.

Puranik continues: “Big data in the oil and gas industry will experience incremental growth once it overcomes these barriers. The growth will be further accelerated by concerns such as falling profit and future uncertainty from renewables.

“The oil and gas industry traditionally relied on paper-based data collection for maintaining records from daily operations. This approach has largely been digitalized now. Effective data management is essential for this approach to succeed so that companies can make better use of their data.”

GlobalData’s thematic research identifies ADNOC, BP, Chevron, ConocoPhillips, Equinor, ExxonMobil, Gazprom, Rosneft, Repsol, Royal Dutch Shell and Woodside as among the major oil and gas players present in the big data theme.

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While today’s operating environment puts businesses under pressure to innovate, the workforce can feel left out and wonder where they fit in. While there’s no denying how digitisation is allowing efficiencies in business that were not possible before, Human Intelligence (HI) is still a great commodity for businesses today, and in the future.

The big question then is, what moves can we expect to see in the market as businesses look to leverage digital transformation with people in mind?

A good place to start is examining how digital technologies, such as automation and Artificial Intelligence (AI) have not only benefited businesses in driving efficiency but also benefits the human workforce – by cutting out tasks that may be seen as repetitive and mundane.

According to Deloitte’s recent Global Human Capital Trends survey, 41% of respondents are already investing in automation extensively, across multiple functions, to empower their workers to create more value by enabling them to produce better results, and focus on higher-value tasks.

So, here are some trends that we can expect to see in the market in the coming year:

1. Empowered people – the biggest misconception is that the digital era is only catered for the digitally skilled.
   
   While digital skills will increasingly be on-demand – if we look at the lead generation scenario, for instance, where understanding what products and services people want is key – this means that while digital tools can process data efficiently, it still takes people to come up with the strategy of how to stoke the lead generation project to apply to people.
   
   As a result, the market will begin to see digital solutions not only augment technical roles, but also drive efficiency in areas like call centres where the typical scenario will be that of an AI-backed chatbot handing over the conversation to the right consultant.
   
   
2. New business opportunities – the reality is that many companies are still struggling to reap the benefits of digital transformation, given that becoming a digital enterprise is no small undertaking.
   
   The required strategic approach simply cannot be implemented without people in mind.
   
   As a result, the broader business scenario will only begin to see true transformation if their digital strategies and initiatives bring new opportunities for staff. Everything from data curation and monitoring; IT systems management; cybersecurity; cultivating and engaging with an eco-system of technology partners; the implementation of automated and intelligent workflows all needed to be adapted with training programmes that focus on digital competencies.
   
   As a result, businesses will begin to understand the technologies available to them, they will also begin to see how HI can truly drive successful adoption and expand on its revenue streams.
   
   After all, these technologies are created and managed by people.
   
   
3. Rise of the digital workforce – for the younger generations coming into the workplace, many who are viewed as the ‘digital natives’, will of course find it easier to form part of the digital eco-system in business – especially as institutions of higher learning also begin to offer digital learning.
   
   So, going into 2020, businesses will begin to assume far more flexible and contingent talent models to rapidly access in-demand skills to allow them to deliver a better and stronger customer experience – all while leveraging HI according to the industries’ demands.

As digital transformation continues to bring exciting changes to the workplace, Human Intelligence is still invaluable and will continue to be – as business offerings are tailored for humans.

Trends will come and go just like industrial revolutions, but people and what they can offer for business will continue to stand the test of time – in 2020 and beyond.

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The 1994 fan-favourite film, The Santa Clause, taught us that seeing isn’t believing, believing is seeing. Well, it turns out little elf Judy was wrong on that when it comes to future-proofing a digital enterprise. Faith alone simply doesn’t cut it for NetOps and SecOps pros responsible for making sure their infrastructure is as robust and secure as it needs to be. In fact, harnessing the power of sight couldn’t be more important to digital infrastructure design strategy.

Holiday whimsy aside, this lesson has major significance for the 87 per cent of senior business leaders who believe digitisation is a top priority, a journey arguably as challenging as dropping gifts through chimneys across the globe. Among the goals of digital transformation (DX) are streamlining business processes, cutting costs, improving productivity and introducing new business models that redefine industries — or build new ones. These are ambitious goals, and they’re ultimately realised through new digital applications built on intricate microservices-based architectures.

For examples of successful DX applications look no further than ride sharing apps like Uber and Lyft, or home sharing apps like Airbnb. In the financial world, consider robo-advisors, peer-to-peer lending services, crowdfunding campaigns and cryptocurrencies — these are all DX innovations. Applications built around connected Internet of Things (IoT) devices can also fit into the DX category, as can industry-specific solutions, such as Industrial Control Systems (ICS), Supervisory Control and Data Acquisition (SCADA) and medical systems protocols.

Digital transformation (DX) spending is predicted to reach nearly $2 trillion in 2022, while organisations grapple with public, private, and hybrid cloud infrastructure and multi-tier applications that need to be managed and secured. Seeing – in the form of application-centric visibility – is key to understanding application interaction and usage patterns, in order to accelerate DX.

Like Christmas songs playing on a loop, it bears repeating that seeing to believe the current state of your environment, and its network and application layers, is critical for guiding DX efforts, and reducing risks, costs and complexity along the way. Here are five reasons why seeing is believing for DX success:

Metadata matters

1. At the heart of DX are new digital applications—These applications are powering the transformation. They are typically built leveraging a microservices architecture and deployed over hybrid infrastructure (physical, virtual, cloud), and are consumed on a myriad of mobile devices.

2. Digital applications introduce increased complexity into the infrastructure—A key challenge that arises when dealing with this new breed of digital applications is their complexity, which ultimately manifests as challenges in securing the applications, as well as ensuring consistent performance and user experience. In fact, a recent survey by Forrester of 1,000 CISOs worldwide, found that IT complexity is their number one challenge.

3. You need a clear vantage point from which to see these applications—Only with a clear view, and the right kind of data, can you then understand the applications’ interactions, performance, and security characteristics. The only way to get to this view is to look at the data in motion on the network. Deploying agents across the complex hybrid infrastructure is not feasible (for example, you can’t deploy an agent to a third-party microservice or to an industrial control system). And this visibility must stretch across on-premise, private, public and multi-cloud environments because, as the saying goes, ‘if you can’t see it, you can’t secure it.’

4. Isolating communication streams allows for deeper inspection—Once you understand what applications and microservices are running across your hybrid infrastructure, it’s fair to assume that in deployment, something at some point is bound to go awry. You need to figure out what’s happening and quickly course correct, but when you’re scaling microservices, it’s hard to troubleshoot just through application instrumentation. The ability to isolate specific applications or microservices communication streams for deeper inspection allows SecOps teams to easily understand access patterns and put in place effective micro segmentation strategies. Application developers too can benefit from this by better understanding communication bottlenecks between applications and microservices, as well as troubleshoot applications and microservices.

5. Application metadata matters—The ability to extract metadata pertaining to those applications or services of interest can then fill gaps from a compliance, risk and performance perspective. Specifically, application metadata intelligence offers contextual data needed to quickly pinpoint potential threats and resolve network or application performance issues that can impact the user experience.

Accelerating secure deployment of digital applications is equivalent to catching the Christmas spirit for NetOps and SecOps pros tasked with complex infrastructure development, implementation, maintenance and security. While these modern, multi-tiered DX applications bring agility and innovative capabilities, their complexity makes monitoring and securing them difficult, if not impossible, with ineffective network visibility. This puts the success of these applications in particular — and digital transformation projects in general — at risk. It’s that Rudolph-grade vision into the organisation’s network and application layers that’s necessary to enable you to visualise your infrastructure, what’s running on it, and how applications are performing and interacting with each other and if they’re secure. Once you can truly see the data in motion on your hybrid infrastructure, believe me, the path to digital innovation becomes a whole lot easier.

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