When using data to make impactful business decisions, certain doubts may start to arise, like “What does this column exactly mean?” or “Can I trust this data source I want to use?” Questions like these speak to a larger need for increased data literacy and trust in data. ThoughtSpot continually invests in this area, giving users the confidence to build the correct Answers needed for their analysis—and ensuring they can trust the data they are shown.

We’ve talked about the many ways large language models (LLMs) and artificial intelligence (AI) are impacting business efficiency, data and analytics, and even FinOps. But we’ve yet to talk about arguably one of the most important areas of concern: security.

By the end of this two-part series, we will dive into what data warehouse architecture is and how to implement one for your organization. Part one will look at architectural layers and common data warehouse components, while part two dives into multi-tiered data warehouse architecture.

We’re thrilled to announce that both ThoughtSpot and Mode (acquired by ThoughtSpot in July 2023) have been recognized as Leaders in Snowflake's recent Modern Marketing Data Stack report! Given the ever-evolving landscape of modern data analytics products, organizations are looking to ThoughtSpot and Mode when seeking innovative solutions—helping them harness the power of their marketing data.

Semantic layers are a game changer, allowing organizations to define metrics and business logic in one, centralized location. Because business users can trust that their data is built on a single source of truth, the semantic layer also empowers self-service analytics. Looker Modeler has become a leader among semantic layers, allowing users to seamlessly layer on top of their business data.

ThoughtSpot users can easily create content with data using our intuitive, AI-powered search experience. However, business users sometimes find themselves asking a critical question: which content should I trust and use for my specific business use case? For example, if there are ten “Sales Performance” Liveboards created by different authors, you may wonder which is the golden version—the Liveboard that is reviewed, approved, and consistently maintained.

In a survey by the Harvard Business Review, 87% of respondents stated their organizations would be more successful if frontline workers were empowered to make important decisions in the moment. And 86% of respondents stated that they needed better technology to enable those in-the-moment decisions. Those coveted insights live at the end of a process lovingly known as the data pipeline.

I’m calling it now. The next battleground for analytics adoption among business users will be the productivity suite. Let’s unpack that statement by considering these two examples: Traditional BI has always forced you down a one-way street for answers—drop what you are doing, login to the BI tool, and pray to the data deities that you can find the answer you’re looking for.

I recently watched the movie Air. I absolutely loved it. Note: if you don’t want spoilers, you may want to skip the next two paragraphs. Air is a story chronicling how Nike, the underdog in those days, steals Michael Jordan away from Adidas and Converse. With the cards stacked against Nike—they had a much smaller budget than their big-brand competitor, Adidas—it was conventionally assumed that Michael was better off signing with a more established brand.

In the past, it was commonly believed that only administrators or designated support contacts benefited from live product support. But that shortsighted view fails to acknowledge the reality that every user—be you an occasional business user, tenured analyst, or in-the-weeds IT administrator—can encounter roadblocks and require assistance. That's why our new In-App Support is available to all users worldwide, regardless of their role.