ThoughtSpot
Overview
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HQ Location
United States
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Year Founded
2012
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Company Type
Private
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Revenue
$10-100m
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Employees
201 - 1,000
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Website
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Twitter Handle
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Company Description
ThoughtSpot is a business intelligence and big data analytics platform that helps anyone explore, analyze, and share real-time business analytics data easily. ThoughtSpot???s AI-Driven analytics platform puts the power of a thousand analysts in every business person's hands. With ThoughtSpot, you can use search to easily analyze your data or automatically get trusted insights pushed to you with a single click. ThoughtSpot connects with any On-Premise, cloud, big data, or desktop data source and deploys 85 percent faster than legacy technologies. Business Intelligence and Analytics teams have used ThoughtSpot to cut reporting backlogs by more than 90 percent and make more than 3 million decisions - and counting. ThoughtSpot???s customers include Amway, Bed Bath and Beyond, BT, Capital One, Celebrity Cruises, Chevron Federal Credit Union, De Beers, Insurethebox and Scotiabank. The company was co-founded in 2012 by its CEO Ajeet Singh and six other technical co-founders from Google, Microsoft, Amazon, and Oracle. It is based in Palo Alto, CA and is currently expanding operations in North America, Europe and Asia-Pacific. ThoughtSpot???s mission is to enable analytics at "human scale" and put search-driven analytics in the hands of 20M users by 2020.
IoT Solutions
Search & AI-Driven Analytics Platform
Use search to get granular insights from billions of rows of data. Or let AI uncover insights from questions you might not have thought to ask.
Use search to get granular insights from billions of rows of data. Or let AI uncover insights from questions you might not have thought to ask.
Key Customers
Hulu, 7 eleven, walmart, Rolls Royce, Amway, Caterpillar Inc., Daimler, J.J Keller Associates
IoT Snapshot
ThoughtSpot is a provider of Industrial IoT platform as a service (paas), and analytics and modeling technologies, and also active in the cities and municipalities, finance and insurance, healthcare and hospitals, and retail industries.
Technology Stack
ThoughtSpot’s Technology Stack maps ThoughtSpot’s participation in the platform as a service (paas), and analytics and modeling IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
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Case Studies.
Case Study
HP Democratizes Access to AI-Driven Business Insights Using Snowflake and ThoughtSpot
HP's partner ecosystem, which generates 80% of its revenue, involves data exchanges with thousands of partners for product tracking, sell-through inventory, and more. As business models evolved, more data and data sources needed to be connected to HP’s data platform. However, HP struggled with an ineffective BI toolset for scaling its business and growing its partner ecosystem. The BI team managed a traditional collection of OLAP cubes, a custom-built .NET user interface, and hundreds of offline reports. The system took 24–48 hours to refresh data and even longer to analyze that data. New data deployments took three months, making the data obsolete by the time it was ready for use. The BI team was a bottleneck, spending too much time on data analysis requests rather than focusing on more-strategic initiatives. The team downloaded data into offline dashboards and reports and distributed it in Excel and PowerPoint documents throughout the organization. End users needed a self-service solution.
Case Study
Accern's No-Code AI and ThoughtSpot Everywhere: A Case Study on Accelerating Financial Decision-Making
Accern, a firm that believes in the power of data and AI, was facing a significant challenge. The development of an AI model typically takes an IT team 12 to 18 months, with 80% of a data scientist’s time spent on finding, cleaning, and reorganizing data. Accern's no-code AI allows users to deploy and customize pre-trained financial services models to extract insights from a vast amount of unstructured data more accurately and efficiently. However, Accern found themselves limited in the customization they could offer customers. They lacked self-service access to data visualizations and were restricted to the single dashboard provided to them. This limitation was hindering their mission to empower customers with data and was a barrier to their growth and customer satisfaction.
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