Google BigQuery is a fully managed, enterprise-scale, cloud data warehouse that helps you store, manage, and analyze your data. This article will take you through the fundamentals of Google BigQuery. I’ll also share optimization opportunities to improve performance when you’re using both BigQuery and ThoughtSpot.
Data modeling is not about creating diagrams for documentation sake. It’s about creating a shared understanding between the business and the data teams, building trust, and delivering value with data. It’s also an investment. An investment in your data systems' stability, reliability, and future adaptability. Like all valuable initiatives, it will require some additional effort upfront.
With the recent announcement of ThoughtSpot Sage, we launched a number of enhancements to our search capabilities including AI-generated answers, AI-powered search suggestions, and AI-assisted data modeling. In this article we will walk you through the steps we take to secure your data during the LLM interaction.
In a world where user experience and IT support can mean the difference between hitting or missing your ARR marks, businesses have to find smarter ways to build workflows and support their IT departments. That’s where companies like ServiceNow come into play. A few years back, we created our ServiceNow SpotApp, a pre-built analytics template to help companies analyze and understand their data—so they can increase efficiencies across their complex IT environments.
There are millions of data products out there, some successful and others…less so. But the truly standout data products are the ones that change users’ behavior. You know you’ve built something special when your users start forming habits around your product. The question is, how do you create something that stands out in a sea of data products? We believe it comes down to one thing: a relentless focus on delivering user value.
It’s that time of the year again! I’m still buzzing about this year’s Showfloor Showdown at Gartner Data & Analytics Summit in London, where I had the opportunity to showcase ThoughtSpot's AI-Powered Analytics. In the spirit of facilitating a side-by-side comparison, we were all invited to look at global flooding and weather station data, analyze the variables affecting these natural disasters, and present key findings to the crowd.
The GPT euphoria got doused with some reality recently as Samsung employees realized they were sending false information to customers and Italy outright banned ChatGPT. The hype and concerns further accelerated last week with the godfather of AI, Hinton, resigning from Google, President Biden summoning AI leaders to Washington, and several stocks nose-diving on the threats generative AI poses to their business models.
Traditional BI has always been wrought with login friction. It’s very much a “pull” motion. In order to get the answers you need, you have to stop what you are doing “over there” and access the data you need “over here.” To disrupt this old way of thinking we launched ThoughtSpot for Sheets back in October 2022. And of course, the first thing a lot of customers asked was – "this is great, do you have something for Excel?" 🤦
Business is won or lost based on the quality of the experience you deliver to customers, partners, vendors, and employees. These experiences are built entirely on data. Harnessing data to deliver value is the single most powerful way to engage today’s demanding consumers—not to mention capturing market share and accelerating strategic decision-making. But there's a problem.
CIOs are fed up with having a plethora of BI and analytics tools with business units seemingly chasing the shiniest new solution. And although most industry surveys show data and analytics budgets continuing to grow despite a faltering economy, there is closer scrutiny and belt tightening to rid teams of overlapping capabilities. Here’s a look at how BI tool portfolios have become such a mess and how to streamline them.
