ThoughtSpot Brings Search-Based Analytics to Google Cloud


ThoughtSpot-Brings-Search-Based-Analytics-to-Google-Cloud.

Search and analytics company ThoughtSpot extended its partnership with Google Cloud. It is now certified to run its in-memory calculation engine on Google’s Cloud Platform (GCP). ThoughtSpot also added new integration between its products and the Google Cloud Machine Learning Engine.

While Google Cloud has a number of certified partners in analytics and big data, ThoughtSpot’s Director of Content and Communications Ryan Mattison said it is the first to bring search and artificial intelligence (AI)-driven analytics to GCP. This includes running its AI engine, Falcon, on the cloud platform and leveraging the GCP machine learning engine to make predictions.

Palo Alto, California-based ThoughtSpot was founded in 2012 by engineers from Google, Oracle, Microsoft, Yahoo, and other Silicon Valley companies. Its CEO Ajeet-Singh, joined the company from Nutanix in July 2018, which he co-founded. ThoughtSpot was co-founded by Ajeet Singh, who serves as its executive chairman. ThoughtSpot’s core technology is a next-generation analytics platform that enables search functionality so users can analyze enterprise data.

Falcon automatically performs integration, sorting, filtering, and aggregation work on datasets from the full network stack. ThoughtSpot provides search-driven analytics that rely on in-memory calculation, which Mattison said allows the system “to automatically join relevant data sets across different sources and then running the calculations in-memory [based on the data] provides the performance needed for search at scale.”

By running this engine on GCP it can allow enterprises to analyze data in their multi-cloud environments. It combines data from across public clouds, private clouds, and on-premises environments to run analytics and machine learning workloads at scale.

In extracting and analyzing multiple data sources, ThoughtSpot can extract and analyze multiple data sources that allows an enterprise to choose which infrastructure fits its data needs. By combining all of enterprises cloud data sources into a single source they can analyze the totality of its data. The engine can also integrate new cloud technologies adopted by the enterprise.

The integrations with the GCP Machine Learning Engine is another way to improve the efficiency of data science teams by merging machine learning algorithms and search. Enterprises using ThoughtSpot can now leverage, test, and deploy algorithms from the GCP machine learning engine into their own data models. Users can leverage the search functionality of ThoughtSpot to extract data science insights from these algorithms.

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