AI-powered augmented analytics: capabilities and benefits for business

Traditional BI and data analytics solutions. far too many organizations have in place today do not work for the new normal, although they offer a whole lot of essential capabilities. For instance, cleaning up raw data so that it can be properly analyzed by BI tools still remains a manual process, which naturally eats up too much time. On top of that, this opens up the possibility of human error, which only slows down the whole process and creates a roadblock to receiving timely and relevant insights.

Data sources may number in the hundreds and it takes a good deal of time for enterprise software development companies to merge multiple sources and bring petabytes of siloed data together into a single view to leverage them for insights. Beyond that, there is always a risk of human bias when it comes to the analytics process. The point is that traditional BI systems respond exactly to the queries business users make. Such systems surface only those insights that decision-makers are querying, leaving no room for hidden insights and unexpected results. The result: bad business decisions and missed market opportunities. To top it all, traditional BI and analytics solutions lack self-service capabilities compelling business users to depend on IT specialists for data ingestion, analysis and insight generation. This heavily undermines effective and timely decision making. Such tools aren’t capable of scaling to organize and analyze volumes of unstructured data growing at breakneck speed. And it seems that businesses are working for analytics rather than the other way around. So why waste precious time and resources if everything can be done automatically, flawlessly and at a much faster rate? AI-assisted augmented analytics is here to change the game. Once and for all. Here is how.

On a larger scale, augmented analytics is designed to automate and accelerate the process of insight generation. More fundamentally, modern data analytics companies harnesses machine learning automation to revolutionize the user experience across the entire BI process from data ingestion to analysis to insights visualization. So, what are those key revolutionary augmented analytics capabilities that help businesses speed up the flow from raw data to meaningful insight to informed decisions?

They provide an opportunity to perform predictive analysis on large volumes of data in real-time, thereby allowing business users to make confident, future-oriented decisions at the point of need. Leveraging statistical and machine-learning algorithms, augmented analytics has proven critical in making educated guesses, predicting future events or outcomes, forecasting upcoming trends and getting instantaneous and reliable recommendations on what steps to take next.

Augmented analytics is well on its way to revolutionizing the BI landscape. By combining Artificial Intelligence, Machine Learning, and Natural Language Processing, it sets the stage for real-time drill-down data exploration and analysis at speed and scale. Through augmenting human intelligence across the entire analytics life-cycle and democratizing data science, advanced analytics allow making smart, confident and informed decisions at the speed of business. No manual intervention and hence errors. No dependency on tech experts. No decision-making biases. No more second-guessing. Augmented analytics is going to do away with this. Once and for all.