Big Data Industry Predictions for 2021

Sending
User Review
0 (0 votes)

Big-Data-Industry-2021

Big Data Industry 2021- 2020 has been year for the ages, with so many domestic and global challenges. But the big data industry has significant inertia moving into 2021. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming. We were very encouraged to hear such exciting perspectives. Even if only half actually come true, Big Data in the next year is destined to be quite an exciting ride. Enjoy!

Daniel D. Gutierrez – Editor-in-Chief & Resident Data Scientist

Analytics

The “analytic divide” is going to get worse. Like the much-publicized “digital divide” we’re also seeing the emergence of an “analytic divide.” Many companies were driven to invest in analytics due to the pandemic, while others have been forced to cut anything they didn’t view as critical to keep the lights on – and a proper investment in analytics was, for these organizations, analytics was on the chopping block. This means that the analytic divide will further widen in 2021, and this trend will continue for many years to come. Without a doubt, winners and losers in every industry will continue to be defined by those that are leveraging analytics and those that are not. – Alan Jacobson, Chief Data and Analytics Officer, at Alteryx

Likely gone are the days of piecemeal analytics and reporting solutions that are likely fulfilling niche business use cases. This is unsustainable. Companies cannot have highly departmentalized analytics implementations that have the effect of localized problem solving and the larger business not seeing the full benefit. This current situation will change into one where analytics will be done on all data that the company has access to, with the capability of these analytics be implemented in a collaborative manner by a variety of interest groups with different skills sets (e.g., data science, lines of business leaders) and with a full-on focus towards operationalizing analytics insights in near real time. In other words, no more piecemeal and no more just science experimentation. – Sri Raghavan, Director, Data Science and Advanced Analytics Product Marketing at Teradata

Prescriptive analytics will be a key component for digital transformation success: Advanced analytics are becoming mainstreamed as businesses increasingly collect and analyze data across their organizations, with 35% of U.S. manufacturers deploying advanced analytics in the past three years. For AI to have a significant impact across the value chain, prescriptive analytics will be the catalyst to optimize performance. Prescriptive analytics will become an essential piece for scaling AI within organizations, by leveraging product and customer data to advise AI models on how to improve processes, adjust production and increase efficiency. Prescriptive analytics enables constant improvement with an AI model by continuously monitoring and adjusting based on evolving conditions. Prescriptive models can then enable decision automation, where the models can take the best course of action based on prescriptions. Going beyond predictive analytics to prescriptive analytics will ultimately enable digital transformation success for manufacturers in 2021. – George Young, Global Managing Director of Kalypso

Read more at Inside Big Data