Justin Borgman
Justin Borgman is the co-founder, Chairman and CEO of Starburst. Prior to founding Starburst, Justin was Vice President and General Manager at Teradata (NYSE: TDC), where he was responsible for the company’s portfolio of Hadoop products. Prior to joining Teradata, Justin was co-founder and CEO of Hadapt, the pioneering “SQL-on-Hadoop” company that transformed Hadoop from file system to analytic database accessible to anyone with a BI tool. Hadapt was acquired by Teradata in 2014.

X Analytics, a term recently coined by the Gartner research firm, is the ability to run any type of analytics on all of an organization’s structured and unstructured data, no matter where or in what format that data resides. Today, this capability is more important than ever. The pandemic has altered customer and organizational behavior dramatically, forcing accelerated digital transformation across every industry.

Microsoft CEO Satya Nadella said his company had seen two years of digital transformation in just two months, undoubtedly something most business leaders can relate to this year. In most cases, this is an acceleration of digital trends that predated COVID-19 and are now critical to business success and survival.

Industries like commercial banking, entertainment and retail have all experienced massive growth in online traffic and mobile app usage. This dramatic shift in behavior has created an insight gap when it comes to tracking data and trends around the globe.

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The Insight Gap Is a Data Access Problem

Data gathered prior to the pandemic is no longer seen as a good predictor of future behavior. The world is fundamentally different, and we need to adapt. According to a recent piece in Harvard Business Review, organizations need to recognize that their existing predictive models, forecasts, and dashboards may all be unreliable, or even obsolete, and that their analytic tools need recalibrating. I couldn’t agree with this more.

The data that drove past insights isn’t entirely irrelevant now, but companies need to be able to analyze it alongside data collected in the last six months, and the data that is streaming into warehouses or cloud data lakes right now. This is the promise of X Analytics and it’s what is going to help organizations stay afloat after this year and beyond. It’s about giving Business Intelligence (BI) analysts and data scientists the chance to extract value from all enterprise data, matching the newer data against core, foundational data to understand how behavior has changed, what patterns have remained, and how to capitalize on these shifts to drive new business.

Data Analytics Will Define How Companies Adapt

The businesses that find a way to mine all of their data for insights — especially the newest data — are more likely to adapt and even thrive. Data analytics have driven changes in strategic and financial decisions for industries around the world, enabling a more efficient way to manage things like usage trends, customer demands, supply chain inventory and more.

Ideally, business leaders will leverage this newer data in context, and develop both short and long-term strategic and operational plans. You want to give your data analysts the opportunity to analyze all of your data, no matter where it resides, whether it’s foundational or brand new. Better data access will lead to deeper insights and better business decisions. The challenge that many organizations will look to solve in 2021 is how to access that distributed data in a secure, efficient and cost-effective way.

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How Enterprises Leverage X Analytics Today

Organizations are already benefiting from the X Analytics approach. This transformative access to data and new way of thinking is being applied across industries. For example, retailers are more quickly predict new customer behavior, manufacturers are bringing greater transparency to their production and supply chain decisions, government agencies are marrying geospatial data and contact tracing information to assess COVID-19 exposure risk, and cybersecurity firms are identifying unfamiliar hacker patterns and training new models to detect them.

All of these examples depend on the ability to interact with more than one data set, in more than one place. By weaving in the idea of X Analytics, organizations can solve the age-old data silo problem. Even better, it’s also a future-proof solution. If you migrate all your data to the cloud, those backend storage systems will change, but your data consumption layer will remain the same. That means your end users won’t be impacted, and your BI and data science teams can go on working as they always have. This is an unprecedented time, and as Gartner, McKinsey, and so many others have pointed out, it will require extraordinary and creative efforts to thrive in our ever-changing economy.

Feature image via Pixabay.