|Headquarters||Palo Alto, CA|
|Key people|| Ajeet Singh,Shashank Gupta |
Vijay Ganesan, Sanjay Agrawal
Abhishek Rai, Priyendra Deshwal
|Investors|| Khosla Ventures |
Lightspeed Venture Partners
|Number of employees||120 |
|Related Certifications||Certificate in Data Science Industry Overview|
ThoughtSpot is a company that makes an Analytical Search Appliance to combine data from on-premise, cloud and desktop data sources and enables enterprise users to access them through a simple search interface.  The company offers a hardware appliance that comes loaded with software that can connect to a company’s existing data infrastructure — as well as services like Hadoop — from which it can provide users with search capabilities that will supposedly save the time it takes for employees to gather the data they want. 
ThoughtSpot customers include Bed, Bath and Beyond, Batteries + Bulbs, and Nutanix. Companies use ThoughtSpot technology to primarily get business insights faster than traditional SQL based queries. Thoughtspot was founded by Ajeet Singh, who previously co-founded Nutanix, Amit Prakash, and five others. Aaron Levie, co-founder and CEO of Box Inc. was one of the early investors of ThoughtSpot. By May 2016, ThoughtSpot had raised $40 million from Lightspeed Venture Partners and Khosla Ventures. Most of ThoughtSpot’s technology were developed by former Google and Yahoo engineers. 
|June 1, 2012||Thoughtspot was founded in Palo Alto, CA|
|February 5, 2014||ThoughtSpot Raises $10.7M in Series A Funding.|
|June 18, 2014||ThoughtSpot Grabs $30M In Series B Funding.|
|October 21, 2014||ThoughtSpot’s makes it's data analytics hardware available to the public.|
|February 2016||ThoughtSpot Announces Record 810 Percent Year-Over-Year Growth|
Thoughtspot architecture automatically understands a database schema and underlying relationships in order to convert searches into computations
Connects data from multiple sources on-the-fly to compute answers in real-time.
The architecture does not use traditional methodologies of building cubes, aggregate tables, indexes, or materialized views.
Featured Videos and Tweets
|July 07, 2022||BIScorecard||Combine a hackathon with @thoughtspot Liveboards & data is fun! @amitp42 #analytics #moderndatastack https://t.co/DH9JfNvag7|
|July 07, 2022||aciperski||Need → Vision → Incredible Business 🤩 @Harri envisioned a new platform for the hospitality industry's ever-changi… https://t.co/tVBxJL74HY|
|July 07, 2022||ArynnPost||I made a demo video! - Connect to you #dbt model from within #thoughtspot and search on your data! A *very* short p… https://t.co/XB9doSIjHc|
|July 07, 2022||hyperfinity||Cheers! 🍻
We headed to Manchester last night for Data Drinks with @SnowflakeDB, @thoughtspot and @matillion.It w… https://t.co/CoD34qt418
Top 5 Recent News Headlines
Top 5 Lifetime News Headlines
1.ThoughtSpot Grabs $30M In Series B Funding To Modernize Business Intelligence Jun 18, 2014 ThoughtSpot, a startup that hopes to modernize the way companies do business intelligence, announced $30 million in Series B funding led by Khosla Ventures with help from existing investor Lightspeed Venture Partners. The funding brings its total to $40.7 million to date. As part of the deal, Keith Rabois, who is a partner at Khosla Ventures, will join the ThoughtSpot board of directors.The product uses a consumer-like search front end to help find data.
2.ThoughtSpot Eliminates the Need for BI Tools, Introduces Relational Search for Enterprise-Scale Data Analysis Oct 21, 2014 It has brought to market ThoughtSpot Relational Search Appliance -- a first-of-its-kind self-service data analysis solution built for enterprise scale. The appliance combines the custom-built ThoughtSpot Relational Search Engine with ThoughtSpot In-Memory Relational Data Cache to create a solution that eliminates the current trade-off between end-user simplicity and IT departments' needs for scale, security and manageability. ThoughtSpot Relational Search Appliance --The ThoughtSpot appliance is an enterprise-grade solution that combines data from on-premise and cloud data sources and enables enterprise users to access them in a simple-to-use yet secure manner. This is made possible by the following technologies that were custom-built by ThoughtSpot: Browser-based Consumer-class Interface - intuitive, search-based interface that can be used by enterprise workers without the assistance of IT or data analysts. --ThoughtSpot Relational Search Engine - a first-of-its-kind search engine that understands relationships across disparate enterprise data sources and returns instant results from billions of rows of data. --ThoughtSpot In-Memory Relational Data Cache - custom-built relational engine that can cache data from data warehouses, cloud applications, spreadsheets and Hadoop clusters and run in-memory computations on large data volumes. The data cache follows a distributed computing model and can grow incrementally as data volumes grow. --ThoughtSpot Cluster Management - custom-built cluster management framework that provides enterprise-class fault tolerance, manageability and monitoring capabilities to the ThoughtSpot appliance.
Leading analysts and customers see a critical need in the market--"Data discovery capabilities are dominating new purchasing requirements, even for larger deployments, as alternatives to traditional BI tools"