Enterprises and organizations always work to improve and mitigate how they respond to challenges and make their businesses agile at the center of every business organization that aims to remain relevant. Big data is transforming how enterprises are viewing and responding to problems they face daily. Consequently, big data plays a critical role in shaping businesses’ strategic policy for the short term and future. 

Business entities, like a company that sells glass barn doors, have already embraced big data. The capabilities this technology brings to the table get better positioned to make well-informed decisions, allowing such organizations to gain a competitive edge in the challenging market. On average, businesses have recorded improved performance and their bottom-line performance has been boosted.

I’m sure currently, you might be wondering what big data for business refers to. In short, we can define big data as a set of digital information and data that organizations and businesses entities use in the analysis. 

Big data provide such organizations with patterns, trends, and associations that directly relate to the customers and products they work with. The data reveals behavior and interactions your organization has with those sets of data. Big data is not intuition-based, but rather a fact-based method backed up with evidence organizations can use to transform and digitize the process. Gaining insights on ascertain targets is the goal of any business organization and having an improved performance is the end goal that big data offer.

Big data is playing a critical role in strengthening business processes. Organizations are now better positioned to access data sets from multiple sources such as mobile devices, websites, and social media. The data collected is critical in assisting businesses in making critical decisions to improve and better customer engagements through real-time data interactions. Consequently, big data is essential in enhancing efficiency and sealing loopholes in business operations. 

Similarly, big data integration in business processes has a ripple effect on the cost of business investments. Big data reduces the cost and resources required to perform the same job it does with efficiency.

For instance, one department that is critical to any organization is the customer service department, and organizations achieve tremendous results when this department is fully optimized. Integrating big data in real-time in this department’s operations have an overall positive effect on achieving the overall organization objectives. Big data allows organizations to personalize each client and offer a personalized service that targets each client’s needs.

Sale is a fundamental aspect of any business entity. Planning on a sales strategy revolves around combining several factors and processes that enhance a successful result. Big data plays a vital role in sales and marketing. Business analytics has proved to be an effective ingredient in achieving the desired results in a short period. Also, enhancing sales and marketing efficiency had improved tremendously when big data gets used to power these processes.

Organizations should strive to develop a better roadmap for compilation and data collection. Consequently, analyzing this data should be done professionally to allow companies to reap the desired results out of this gold mine. Improving brand value, better customer engagement, and delivering the impossible have been made easy by integrating big data into this process.

The process of analyzing big data for business decision-making requires the organizations to follow the laid down procedure that include these steps.

1. Goal Identification

Any aspiring organization to integrate big data in their processes must first identify why they need to have this technology integrated. Organizations must lay down their business goals and operations and related decisions that they make out of these operations. Big data requires that the analytics techniques that will get employed follow the laid business processes for each enterprise. 

2. Creation and Improvisation

Business organizations are working to improve their organizational goals and their performance metric as well. Avoiding non-significant data or any other non-related data sets in your collection and analysis will save time and resources.

During the staging period, organizations must eliminate any non-related data. It allows business entities to plan and stay focused on the goal as outlined in their business plan and objective of integrating big data in their processes. Data cleaning allows quicker and easier goal optimization to take place, and it should be data before the big data analysis process gets started. Once creation and improvisation are in place, organizations can now kick start the data collection process.organizations

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AI can exploit the vulnerabilities of a person’s decision-making habits and patterns.

A new study by researchers from the Commonwealth Scientific and Industrial Research Organisation’s (CSIRO) Data61, in partnership with the Australian National University and researchers from Germany, has revealed that artificial intelligence (AI) can influence human decision-making.

Spearheaded by CSIRO scientist Amir Dezfouli, the study [PDF] involved running three experiments where participants played games against a computer.

The first two tests involved participants clicking on red or blue coloured boxes to win a fake currency. In the third experiment, participants were given two options as to how they could invest some fake currency. In the scenario, participants played the role of the investor while the AI played the role of the trustee.

As all three games went on, the AI learned the participants’ choice patterns that eventually saw it guide the players towards specific choices. For instance, by the third game, the AI was learning how to get participants to give it more money.  

Dezfouli said the study highlighted that AI could influence human decision-making by exploiting the vulnerabilities of an individual’s habits and patterns.

“Although the research was theoretical, it advances our understanding of how people make choices. This knowledge is valuable because it allows us to mitigate our vulnerabilities so we can better detect and avoid flawed choice as a result of potential misuse of AI,” he said.

He added that the way future AI operates will be dependent on its creators.

“Ensuring AI and machine learning are used as a force for good — to improve outcomes for society — will ultimately come down to how responsibly we set them up in the first place,” Dezfouli said.

The study has been published in the Proceedings of the National Academy of Sciences journal.

At the end of last year, Data61 researchers developed an implantable artificial intelligence monitoring and seizure detection helmet system designed to prevent seizure disorders for patients who have undergone decompressive brain surgery.

The detection system was developed and trained using traumatic brain injury data from Monash University to monitor brain activity for seizures while in standby mode before it is reactivated when a seizure is detected.

“Monitoring brain activity post-surgery is especially critical to a patient’s recovery as seizures can regularly occur, often leading to patients developing epilepsy,” CSIRO’s Data61 researcher Dr Umut Guvenc said at the time.

“These seizures are often difficult to detect, with current monitoring techniques only able to be used in a hospital using bulky devices for less than 24 hours, providing a brief snapshot of brain activity during that time only.

“This new method can continuously monitor brain activity wirelessly, allowing the patient to be mobile, comfortable, and more socially active.”

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