Augmented Analytics & Business Intelligence

We live in an era of data. Data is ever-increasing and the business intelligence system is having a hard time processing such humongous amount of information which is complex and fast-moving. To thrive, any organization not only needs to process the data but also uncover the insights hidden in those reports. With traditional business intelligence systems failing profusely to cater to the ever-changing requirements of business organizations, Augmented Analytics comes to the rescue. Augmented analytics is the emerging trend in the data analytics market, and more enterprises should be opting for it for its mature and superficial capabilities with the disruptive advances in pervasive computing and industry.

But does that mean Augmented analytics is posing a threat to the generic business intelligence systems?

Let us first discuss what Augmented analytics is.

A term coined by Gartner, “Augmented analytics uses machine learning/ artificial intelligence (ML/AI) techniques to automate data preparation, insight discovery and sharing and it also automates data science and ML model development, management and deployment.”

In other words, Augmented Analytics has the power to automate data science steps and machine language involved in an advanced analytics process giving business people unprecedented freedom to guide machines in terms of right insights in right business context while validating machine or the human mind generated hypothesis along the way.

It is on the wishlist of IT vendors as they are on a rush to incorporate these capabilities into their Business Intelligence platforms top makes it easier to democratize analysis for enterprise customers.

It is a cost-effective alternative for the resource of data scientists and analysts who lack a business approach. It lets people involved in the business, get data insights directly by asking questions using natural language instead of having to ask experts to prepare custom reports that are may come too late to be of any use and usually won’t be used again. Since it automates all processes, it eliminates any risk of manual errors.

The bottom line on augmented analytics is that AI will change everything about the analytics and business intelligence process, simplifying or eliminating some steps and radically changing and improving others.

Augmented Analytics complements rather than replaces existing enterprise Business Intelligence, data science platforms and self-service Business Intelligence. Augmented analytics can be embedded additionally into a different line of business applications to improve the process of decision making.

That Augmented analytics is now providing widespread access to data and insights, business people increasingly want to gain more competence in applying data insights to improve their performance.

To sum up:

Augmented analytics is compelled to transform the manner business intelligence processes are undertaken completely in the upcoming years. Augmented analytics has transformed how the entire analytics workflow works and the way data analysts access data and work on its insights.

Thus, modern business intelligence analytics that works with automated insights, automated data preparation, data science platforms will be embedded in the conversational analytics and enterprise applications in the future. This trend is bound to reach beyond data scientists and thus transform businesses significantly for the better.

Co-Author : Trishita Chatterjee, Lead - Content Creation and Development, CodeBinary Initiatives (https://community.codebinary.in/)