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Published On: Fri, Nov 8th, 2019

The truth behind Augmented Analytics & is it really a threat to Business Intelligence?

This is an era of data. Not just data, but everything around is about Big Data. Data sets have become so complex and sophisticated that traditional BI tools and solutions cannot handle them. Static reporting and dashboards aren’t enough to stay competitive anymore. The ever growing demand for data makes data analytics a key component of business development. To stay ahead of the competition, it is important to stay abreast with the changes in business analytics. 

But what does all of this have to do with Augmented Analytics. Let us look at how Augmented Analytics and Business Intelligence help users determine the right solution to handle the future needs of businesses.

Business Intelligence

Business Intelligence is not something that came into existence recently. It has been around for longer than most people realize. In 1958, a white paper “A Business Intelligence System” was published by Hans Peter Luhn, an IBM researcher. He placed that because, “information is now being generated and utilized at an ever-increasing rate because of the accelerated pace and scope of human activities” (IBM Journal, October 1958).”

photo/ Gerd Altmann via pixabay

When it comes to making better decisions for their respective organisations, users required new technological tools to process the information at their disposal and make some sense out of it. Thus started the traditional BI approach. Initially, traditional BI started with general-usage tools that were used by organisations to make better decisions based on their data. Focusing primarily on connecting to single/individual databases and generating reports (basic), the analysis was not complex, less time consuming and required bunch of dedicated analysts and data professionals. 

With the competition growing, businesses focused more on being data-driven, looking to utilise the data they collected. As a result, it was no wonder that the Business Intelligence market saw a massive growth! The Modern BI era introduced solutions that were capable of handling multiple disparate sources: in-house databases, cloud storage, live data streams, app APIs, CSVs, and more, and pull it together to perform complex analyses.

However, users crave for more. With the data getting more complex in nature, users wanted easy options to analyze the data and share results. The interface had to be seamless and the platform had to be capable of offering multiple ways of accessing the data. Especially in an era where mobile apps where the “shiny apple” that everybody wanted to have, users did not want to be tied down to their desks. They wanted solution on the go. 

This is when the next wave of analytics and BI tools came into the picture. “Augmented Analytics”, as it is known to the modern world, integrates Artificial Intelligence to the traditional analytics and BI procedures to allow users more control over their data. Augmented analytics offers to help users analyse, understand and prepare their data in an efficient manner. The subtle integration of AI and Natural Language Processing (NLP) elements changes the concept of user experience in data, and the way users interact with data. 

photo/ Gerd Altmann

What is Augmented Analytics?

In their 2017 edition of the “Hype Cycle for Emerging Technologies”, Gartner introduced the concept of Augmented Intelligence, an overarching concept to Augmented Analytics. 

Describing the integration of NLP, natural language generation and automated data processing capabilities with AI into BI processes, Augmented Analytics is “defined” as the use of Machine Learning (ML) and natural language processing (NLP) to improve data analytics, data exchange and business intelligence. 

What Can Augmented Analytics Do? 

Over the years, AI, NLP and various other modern computational technologies have improved the performance of Augmented Analytics tremendously. Apart from the usual capabilities of simple forecasting of the results, visualising and clustering data, the next-gen augmented analytics deal with more complex functionalities like providing historical reports, dashboards, and automated predictions for better guidance. 

Augmented analytics play a key role in analyzing complex data, which otherwise would have consumed a huge amount of time and money to be handled manually. Augmented Analytics prepares the data automatically, interprets and presents insights to take suitable action. It allows enterprises to test different hypotheses and theories with access to crucial information using various statistical algorithms. Augmented analytics offers ways to explore new data sets, identify leads, predict customer behavior and analyse the results to deliver an effective performance. 

Impact of Augmented Analytics on BI

A self served Augmented Analytics solution helps data scientists, analysts and other IT staff to focus more towards supporting strategic issues rather than focusing on the day-to-day analytical needs of the business community. It also empowers users and provides critical information to handle the advance interests of the business by allowing them to focus on their goals by offering objective metrics. 

Augmented Analytics integrates with the modern BI tools to provide complex, sophisticated techniques and tools in an easy-to-use interface. This helps in bringing together data from various data sources, allowing the users to make accurate decisions to improve ROI and TCO

Integrating with BI ensures accurate business forecasting and predictions by improving user adoption, data sharing, the advancement of data popularity and the integration of BI within the organization & data and metrics literacy. 

Conclusion

Augmented Analytics has already transformed the entire workflow of analytics and how data analysts access data and work on insights. The world is constantly changing and so is data. Countless devices and users are creating new digital records every second of every day, and more powerful and analytics system and AI assistance is a must in order to make sense of it all. Every company, organization, and government will need an augmented analytics platform to connect to these databases from various data sources, find the links within the data, create visualizations, and help users share their findings across the entire organization. The mainstream adoption of augmented analytics is not far from reality for global enterprises. 

Author Bio:

Working as a Marketing Manager at Specbee(Top Drupal Development Company) since 2016, Shriganesh Hegde loves drafting digital strategies and creating content for the company blog & various other global platforms. An avid follower of the latest technology trends, he covers the good & bad of tech in his blogs.

 

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