ThoughtSpot introduces the Data Workspace, a series of introductions for technically proficient data professionals.
ThoughtSpot develops a search and AI engine to make the data in data warehouses insightful and approachable for users with or without a technical background. The way there, setting up and managing ThoughtSpot’s solution, remains dependent on technical data proficiency. With the introduction of the ‘Data Workspace’, the organization is launching a suite of tools that aim to make the work of data professionals easier. Before expanding on the contents, a basic understanding of ThoughtSpot’s platform is of importance.
The basics
Using ThoughtSpot starts with a pre-built connection to warehouse services such as Amazon Redshift, Azure Synapse Analytics, Google BigQuery, Databricks and Snowflake. Data moves to ThoughtSpot’s cloud and becomes approachable with ‘SearchIQ’, a low-code search engine for indexing and retrieving data. SearchIQ allows the contents of a data warehouse to be retrieved using intuitive search terms instead of SQL scripts and the data structure knowledge required to use SQL. AI engine ‘SpotIQ’ increases the relevance of search results as the search engine is used, finds notable trends and presents insights.
Search engines and AI analysis tools for warehouse data are not unique. Yet, the 580 employee-strong ThoughtSpot manages to grow successfully. The platform primarily owes its existence to two factors. Firstly, the connection with a warehouse is relatively quick to create and maintain. Secondly, the search functionality of SearchIQ and the insight of SpotIQ can be made available relatively easily in SaaS and proprietary apps.
The news
Now, ThoughtSpot is introducing a ‘Data Workspace’. The organization states that the release further facilitates connecting warehouses like Snowflake and Databricks. At the same time, the organization is launching SpotApps. These ready-to-use analytics applications can be deployed immediately after a connection to apply the connected data for a specific purpose — for example, revenue forecasting or employee retention reporting. In the absence of the new SpotApps, the two exemplary purposes would have to be achieved through manual searches or in-house application development.
In addition, the organization states that the integration of ThoughtSpot and SaaS or proprietary apps has been strengthened. “Business users need live, interactive access to data to make the most impactful decisions,” says Ajeet Singh, co-founder and Executive Chairman of ThoughtSpot. “Instead of relying on data professionals to find insights for them, these front-line decision-makers need to be able to gain the insights themselves.” He refers to ThoughtSpot’s data output in third-party apps, which entails the integration in tools such as Salesforce and Slack. The exact way in which Data Workspace enhances these capabilities is unknown at this time.
Finally, ThoughtSpot reports that the support of custom SQL scripts and dbt (software solution for structuring data, ed.) is effective immediately. Said support makes ThoughtSpot better suited for modelling and managing data. Such processes are normally performed outside ThoughtSpot, indicating ThoughtSpot’s ambition to facilitate more technical work in-house.
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