5 Major Trends in Analytics and Business Intelligence by Gartner

5 major trends in data analytics and business intelligence by gartner

"As intelligence is at the core of all digital businesses, IT and business leaders continue to make analytics and BI their top innovation investment priority," said Jim Hare, research vice president at Gartner. "This Hype Cycle helps data and analytics leaders make the transition to augmented analytics, to build a digital culture and operationalizing and scaling analytics initiatives."

These are the 5 major trends, as revealed by Gartner in their press release, which would shape the evolution of Analytics and Business Intelligence.

5 major trends in data analytics and business intelligence by gartner
Source: Gartner (October 2019)

1. Augmented Analytics
Augmented Analytics uses ML to automate data preparation, insight discovery, data science, and machine learning model development and insight sharing for a broad range of business users, operational workers and citizen data scientists.

As it matures, augmented analytics will become a key feature of modern analytics platforms. It will deliver analysis to everyone in an organization in less time, with less of a requirement for skilled users, and with less interpretative bias than current manual approaches.

2. Digital Culture
Developing an effective digital culture may be the first and most important step an organization takes in its digital transformation journey. "Data literacy, digital ethics, privacy, enterprise and vendor data-for-good initiatives encompass digital culture," said Mr. Hare.

Gartner predicts that, by 2023, 60% of organizations with more than 20 data scientists will require a professional code of conduct incorporating ethical use of D&A.

3. Relationship Analytics
The emergence of relationship analytics highlights the growing use of graph, location and social analytical techniques to understand how different entities of interest — people, places and things — are connected.

For example, relationship analytics based on graph techniques can identify illegal behavior and criminal activity. By analyzing formal and informal networks of people, law enforcement agencies can identify money laundering and other criminal activities. It becomes easier for them to distinguish between malignant and benign behavior within networks.

4. Decision Intelligence
D&A leaders draw on a wealth of data from ecosystems that are in constant motion. This requires them to use a multitude of techniques to manage data effectively. The unpredictability of the outcomes of today's decision models often stems from an inability properly to capture and account for the uncertainty factors linked to these models' "behavior" in a business context.

Decision intelligence provides a framework that brings together traditional and advanced techniques to design, model, align, execute, monitor and tune decision models.

5. Operationalizing and Scaling
The number of use cases at the core of a business, on its edges and beyond is exploding. More people want to engage with data, and more interactions and processes need analytics in order to automate and scale. Analytics services and algorithms are increasingly activated whenever and wherever they are needed. Whether to justify the next big strategic move or to optimize millions of transactions and interactions gradually, analytics tools and the data that powers them are showing up in places where they rarely existed before. This is adding a whole new dimension to the concept of "analytics everywhere."

Gartner Data & Analytics Summits

Gartner analysts will provide additional analysis at the Gartner Data & Analytics Summit 2019, taking place from November 19-20, 2019 in Frankfurt, Germany, from February 17-18, 2020 in Sydney, Australia, from March 9-11, 2020 in London, U.K., and from March 23-26, 2020 in Grapevine, Texas, U.S. Follow news and updates from the events on Twitter using #GartnerDA.