Will Sensationalizing AI Help Save Your Business Analytics Job!

If you are yet to find your dream job, you should read this blog on the role of Artificial Intelligence (AI) in business analytics. As we approach the end of another year and a prolific decade, we are constantly fed with the fodder of myth and sensationalism of AI snatching a bulk of jobs and human reliability. While nobody can deny the impact of having AI as a supporting tool, an allied platform to improve human endeavor, we are yet to find the true blue solution to replace human intelligence used in Business Analytics. However, we can’t take things lying as is — AI can actually take out BI jobs by 2027, if leading research studies are to be believed?

But, what could change in the next 5 years, if not now?

Enterprises are ruled by data, and their ability to extract, mine and analyze data in real time scenario makes them almost ‘invincible’. Thanks to rapid advancements in the fields of Augmented Intelligence, Data Visualization, Self-learning Big Data analytics, and Deep Learning, business analytics team are in far better point of advantage to forecast accurately how the business will shape up in the coming weeks, if not days.

Things for BI teams are turning from Predictive to Prescriptive. More and more BI tools are hitting the shelf with their top end Automation and Data storytelling capabilities. Platforms such as Looker, Sisense, Tableau, SAS, Experian, and Dun and Bradstreet tell a whole new narrative on how data can make things happen really fast for businesses that may not have the force or resource to hire business analytics teams.

So, by 2025, enterprise BI teams would largely consist of AI engineers and Big Data Forecasters who use reactive analytics to extract real-time insights on Strengths, Weaknesses, Opportunities and Threats in the marketplace.

Why Enterprise Could Risk Blowing it All Away with BI Myths

Enterprises relying on age old BI concepts risk losing their once shiny edge to new age start-ups who come with brighter ideas, sharper teeth and powerful data mining models– all enabled by a team created from Business Analytics courses in India.

Big companies are developing their own ML-based BI teams. For example, companies like Oracle are investing heavily in transforming BI models. Oracle Machine Learning (OML) consist of an ensemble of Business Analyst features that help segment data and partition it into multiple sub-models for training, testing, and classification and regression models.

By 2025, BI teams would lose their identity to more edgy AI ML Analysis professionals who can create self-learning AI Ops combined with the BI Ops teams built on high performance computing platforms. Heard about Edge? That’s where we are heading to in BI revolution…

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