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What's new in ThoughtSpot Analytics Cloud 8.8.0.cl

In this release, we’re delighted to launch in beta ThoughtSpot metrics integration with dbt — the quickest way to move from data models to business insights. We’ve also added support for dbt models on Amazon Redshift and Google BigQuery, as well as new live query connectors for Presto and Trino. Check out the highlights in this video.

Demo: Unravel Data - Keep Cloud Data Budgets on Track (Automatically)

Data teams need to be able to set cloud data budgets at a specific scope - and know if your various teams or departments are tracking to those budgets. But today, most data teams only know that the budget was overrun after it’s too late. With Unravel, establishing and tracking budgets to prevent overruns is easy.

Using Apache Solr REST API in CDP Public Cloud

The Apache Solr cluster is available in CDP Public Cloud, using the “Data exploration and analytics” data hub template. In this article we will investigate how to connect to the Solr REST API running in the Public Cloud, and highlight the performance impact of session cookie configurations when Apache Knox Gateway is used to proxy the traffic to Solr servers. Information in this blog post can be useful for engineers developing Apache Solr client applications.

From Data Engineering To Data Science To Producing Results For Today's Top Brands.

The simplicity of Snowflake—especially when it comes to scaling—is described by Nauman Hafiz, CTO of Constellation as a superpower. In this interview, Nauman sits down with Itamar Ben Hemo, CEO of Rivery, to discuss the impact of the data cloud on their business. They discuss moving from data engineering to data science, working with today's top brands, and freeing businesses to get the most value out of their data.

Future of Data Meetup: Enrich Your Data Inline with Apache NiFi

In this meetup, we’ll look at the different options for enriching your data using Apache NiFi. When and why would we prefer using NiFi for enrichment over a potentially more holistic solution, like Flink or Spark? What are the limitations? And how can we get the best of both worlds, performing data enrichment with NiFi when it makes sense and using our CEP engine when that makes the most sense? Join John Kuchmek and Mark Payne to find out!