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TigerGraph 2020 Predictions: Five Forward Looking Thoughts on Data Analytics

VMblog Predictions 2020 

Industry executives and experts share their predictions for 2020.  Read them in this 12th annual series exclusive.

By Dr Yu Xu, CEO, TigerGraph

Five Forward Looking Thoughts on Data Analytics

The phrase "2020 vision" implies that someone is able to see clearly. In this article I examine five technologies that have the potential to have a profound impact on business leaders' ability to see the future clearly and make better-informed decisions in 2020.

Automation of Data Analysis

Industry analyst firm Gartner predicts that 40% of data science tasks will be fully automated by 2020. This automation will help business leaders to efficiently plan ahead and use the appropriate analytics to make favorable business decisions. This will be good news for data scientists and analysts who will be freed up from mundane tasks and more able to focus on higher-value activities. 

Better Data Lineage

The California Consumer Privacy Act of 2018 (CCPA) goes into effect on the first day of 2020. In combination with the General Data Protection Regulation (GDPR), this will further motivate organizations to handle consumers' personal information more mindfully. Data lineage is the ability to trace information back to its source and enhance compliance with CCPA, in addition to making better and more informed decisions. 

Conversational Queries

Gartner also forecasts that as much as 50% of analytical queries will be generated automatically using voice technology and augmented by Natural Language Processing (NLP). This development will allow any employee in a company the opportunity to analyze complex data combinations by utilizing user-friendly, widely adopted analytics platforms.

Data Analytics on IoT

Before the end of 2020, we can expect to have over 20 billion devices on the Internet of Things (IoT) collecting data. Organizations worldwide which depend heavily on these devices, such as utilities and telecoms, business leaders are leveraging assistive technologies to enable more responsive and real-time data analytics. 

Graph Analytics

Last, but definitely not least, I believe graph will become mainstream in 2020. Gartner estimates that the application of graph processing and graph databases will grow at 100% annually and be embraced by businesses wanting to accelerate data preparation and enable more complex and adaptive data science.

Smarter business leaders are going to embrace these technologies in 2020, if they haven't already done so, and, be empowered by a more crystal clear vision of the future, accelerating away from their competition in the pursuit of revenues.


About the Author

Dr. Yu Xu 

Dr. Yu Xu is the founder and CEO of TigerGraph, the world's first native parallel graph database. Dr. Xu received his Ph.D in Computer Science and Engineering from the University of California San Diego. He is an expert in big data and parallel database systems and has 26 patents in parallel data management and optimization. Prior to founding TigerGraph, Dr. Xu worked on Twitter's data infrastructure for massive data analytics. Before that, he worked as Teradata's Hadoop architect where he led the company's big data initiatives.
Published Tuesday, January 14, 2020 7:29 AM by David Marshall
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