ThoughtSpot adds data preparation with Analyst Studio launch
Long focused largely on analytics, the vendor's new data preparation environment marks a foray into data management so users can ready data for informing AI and BI tools.
ThoughtSpot on Wednesday launched Analyst Studio, a new environment where customers can prepare data to properly inform AI and analytics applications.
ThoughtSpot has historically focused on business intelligence, providing a search-based platform for self-service users to analyze data. Now, the vendor is adding depth to its platform with Analyst Studio, by delving beneath the analytics layer into data management.
ThoughtSpot acquired Mode for $200 million in June 2023 to add code-first capabilities that enable the development of models and other data assets. Analyst Studio represents ThoughtSpot's integration and alignment of Mode's capabilities.
Generally available to customers of ThoughtSpot Analytics and ThoughtSpot Embedded, Analyst Studio is targeted at trained analysts, rather than self-service business users. It provides experts with the option to explore and prepare data using various code-first options.
Given that it extends ThoughtSpot's platform beyond BI and addresses a new target audience, Analyst Studio is a significant addition, according to Doug Henschen, an analyst at Constellation Research.
"Analyst Studio fills several gaps that existed in ThoughtSpot's capabilities, leading with data prep but also including data engineering and pipelining capabilities, and advanced analytics and data science capabilities," he said.
Analyst Studio fills several gaps that existed in ThoughtSpot's capabilities, leading with data prep but also including data engineering and pipelining capabilities, and advanced analytics and data science capabilities.
Doug Henschen Analyst, Constellation Research
ThoughtSpot, which is based in Mountain View, Calif., named former Salesforce executive Ketan Karkhanis its new CEO in September. The analytics vendor's platform enables customers to explore and analyze data using natural language rather than code.
In November, ThoughtSpot launched Spotter, an AI agent that enables conversational interactions with data.
Analyst Studio
AI's potential to both make the use of analytics more widespread within organizations through natural language processing and improve the efficiency of experts by automating repetitive tasks has enterprises increasing their investments in the technology.
However, if the data used to develop AI tools isn't properly prepared -- if it isn't complete, accurate and trustworthy -- the applications will similarly be incomplete, inaccurate and untrustworthy.
As a result, with some AI applications trained to act independently and others designed by non-technical users who may not have the expertise to decipher an inaccurate output, data quality has taken on greater importance as AI evolves into the primary interface for BI.
Analyst Studio is ThoughtSpot's foray into helping customers make sure the data used to inform analysis can be trusted, according to Sumeet Arora, ThoughtSpot's chief development officer.
"There is no BI without AI, and there is no AI without data," he said. "Analyst Studio opens the gates for our customers with respect to data. When we speak to customers, the reason desired outcomes are not achieved is because data is not ready. Analyst Studio attacks that problem."
While Analyst Studio extends ThoughtSpot beneath the analytics layer, it also repositions the analyst role by enabling analysts to create data products and help determine their organization's data strategy, according to Donald Farmer, founder and principal of TreeHive Strategy. As a result, it's a noteworthy new offering.
"Analyst Studio is a big move for ThoughtSpot users," he said. "It positions analysts as creators and strategic enablers, rather than just data preparers. I think users will see it as redefining their role in an AI-oriented business."
Specifically, Analyst Studio features the following:
Data preparation capabilities that enable analysts and engineers to combine data from disparate sources with built-in connections to databases and data warehouses.
An AI-assisted SQL-based development environment for preparing data that can be used with AI agents, including Spotter.
A full-featured analytics workflow that includes analytical tools that let users perform quick analyses and deep data science.
The choice to analyze, explore and model data using code-first methods such as SQL editor or R and Python notebooks.
Capabilities aimed at helping customers manage usage costs, such as caches for data and live source data connections that directly link ThoughtSpot with data sources.
Enabling the full analytics lifecycle with a full-featured analytics workflow is a significant feature, according to Farmer. So is the flexibility to work in SQL, Python and R.
"This caters to analysts, data scientists and IT teams with diverse skill sets," he said. "And the AI-assisted SQL development environment is very neat."
While delving into data preparation is new for ThoughtSpot, numerous other analytics vendors have also focused on ensuring that data can be trusted. For example, Qlik, which has built up a full-featured data integration platform, has made trusted data a priority. Likewise, Tableau and Microsoft, which offers Power BI, have added data preparation tools.
Adding Analytics Studio brings ThoughtSpot more in line with its peers. But whether it will enable ThoughtSpot to remain competitive as tech giants and data platform vendors such as Databricks and Snowflake use generative AI to extend their reach into BI remains to be seen, according to Henschen.
"I see the big vendors counting on AI and GenAI capabilities to attract more customers, but it's an open question whether GenAI can truly democratize analytics and data science and whether independents can do just as good a job of harnessing these cutting-edge technologies," he said.
The future
A mix of customer feedback and ThoughtSpot's own long-term plans provided the impetus for developing Analyst Studio, according to Arora.
Looking forward, the vendor's roadmap includes improving Analyst Studio by making it easier to write back data sets and adding support for larger data sets, he continued. In addition, product development plans include expanding Spotter's capabilities.
"The most important thing is to listen to our customers and gain more of their trust," Arora said.
Henschen suggested that ThoughtSpot improve its messaging for Analyst Studio. While SQL-oriented analysts are a potential audience, as the vendor is stressing in its marketing, scientists are another.
Farmer, meanwhile, said the vendor would be wise to add more governance capabilities to ensure that an organization's data can be trusted. In addition, more tools that enable collaboration -- especially if assisted by AI -- would be beneficial to users.
"We should see AI 'teammates' participating in the analytic workflow," he said.
Eric Avidon is a senior news writer for Informa TechTarget and a journalist with more than 25 years of experience. He covers analytics and data management.
