ThoughtSpot elements such as search, Liveboards, and data connections are all defined in a JSON-based metadata definition called ThoughtSpot Modeling Language, or TML. Recently, I blogged about how you can use Postman to access platform APIs to import/export TML as part of your devops processes; for example, to check in TML definitions and push to another environment via a continuous integration process. The TML export is pretty straightforward.

When I was working at Google back in the mid 2000’s, we dealt with tens of billions of ad impressions a day, trained several machine learning models on years worth of historic data, and used frequently-updated models in ranking ads. The whole system was an amazing feat of engineering and there was no system out there that was even close to handling this much data. It took us years and hundreds of engineers to make this happen, today, the same scale can be achieved in any enterprise.

We’re entering the defining decade of data. While every aspect of our lives have been changed by data in recent years, the next ten will see data rebuild the world around us. Every business, in every industry, needs a plan to adapt to this new world if they want to thrive. But how? That’s a question in the minds of data leaders, CEOs, and board members. The right approach is critical if companies want to dominate this new era. The wrong decision can spell disaster.

Gaining an accurate view of revenue intelligence for B2B markers is challenging. With disconnected and dirty data residing in many systems, customers need a solution that collects, normalizes, and aggregates information into reports that answer the questions B2B marketers should have a handle on. And let’s face it, no matter how great a set of standard reports might be, every customer wants to see their data a little differently.