Systems | Development | Analytics | API | Testing

ThoughtSpot Launches New Editions for Individuals and Teams to Democratize the Modern Analytics Cloud

New edition enables companies of any size to take advantage of the Modern Analytics Cloud and build their business on data, paying only for what they use instead of shelfware licenses sold by traditional analytics vendors.

ThoughtSpot Expands the Modern Analytics Cloud to Help Companies Dominate the Decade of Data

New capabilities empower customers to use insights to drive actions, take advantage of any kind of visualization, and embed Live Analytics seamlessly into products and services to get the most value from the entire Modern Data Stack.

Why Drag and Drop Analytics are Important for Seamless BI Reporting

Drag and drop analytics are more interactive and user-friendly compared to traditional, high code business intelligence (BI) solutions. They allow users without programming experience to easily explore the data and don't require coding knowledge, with a drag and drop user interface to conveniently enhance functionality of any dashboard report. In this post, you will find the importance of drag and drop analytics for more seamless reporting and user experiences when analyzing business-critical data.

A Guide to Free Data Integration Tools

In the 21st-century business world, data reigns supreme. This means that how organizations to store, organize, move, and automate their valuable company data is crucial for overall success. When it comes to data management, having a great data integration solution in place is key. The process of data integration allows users to combine data from multiple sources, creating a data pipeline.

Leadership Tips: Keeping Data Teams Focused & Engaged | Data Legends Podcast

How do you keep your data team focused and build something that people will derive value from? In this episode, we cover team engagement, how to evaluate tech, and the influence of consumer analytics on innovation. Listen to our conversation with Raheem Daya, Sr. Software Development Manager, Envision Engineering at Amazon Web Services: How to set a clear vision and keep your data team engaged How to decide what tech to invest in and build How consumer tech is democratizing data

Improving a day in the life of: Data Scientist - How ClearML is actually used.

ClearML in the real world, without the marketing fluff. Watch along as we show how ClearML integrates with this audio classification use case. Get lots of tips, tricks and inspiration on the use of the experiment manager and remote agents for use in your own day-to-day life as a data scientist. Chapters.

Using Snowpark As Part Of Your Machine Learning Workflow

Teams working on data science initiatives are tasked with deriving new insights from massive amounts of data. To accomplish this, teams work with compute environments that require heavy operational overhead, which means most of their time is spent extracting and processing features for machine learning model training and inference. Pairing Snowflake’s near-unlimited access to data and elastic processing engine with the most popular programming languages can change that, so more time can be spent on model development.

ThoughtSpot supports Amazon Redshift Serverless

As companies go all in on the cloud to dominate the decade of data, agility, flexibility, and ease of use are critical to success. That’s why we’re so excited to announce ThoughtSpot’s support for Amazon Redshift Serverless which allows customers to leverage the Modern Analytics Cloud to run and scale analytics on Amazon Redshift without having to provision and manage any data warehouse infrastructure.

New! Build seamless Live Analytics workflows with ThoughtSpot and dbt

It’s no secret that modern data professionals are under immense pressure to deliver more data and insights to more business users, more quickly than ever before. Data is the lifeblood of your business. And frontline business people need personalized, actionable insights to make data-driven decisions. But before these users even touch a self-service Live Analytics platform like ThoughtSpot, the data must be appropriately modeled by analytics engineers.