Using SQL for Data Analysis Key Takeaways : Advanced SQL techniques are essential for effective data analysis. Understanding the underlying data structure is crucial for analysis.

The core value of conversational BI lies in lowering the threshold for data analysis and promoting "data democratization." Traditional BI requires users to master SQL, OLAP, and possess data thinking ...

Data analytics is the science of analyzing raw data to make conclusions about that information. It helps businesses perform ...

Why write SQL queries when you can get an LLM to write the code for you? Query NFL data using querychat, a new chatbot ...

Customers that already use SQL Server Analysis Services in their private data centers can take the models from that deployment and move them to Azure, too.

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, ...

Ada, the world's first AI data analyst, has secured the #1 Product of the Day ranking on Product Hunt following its official ...

The construction industry from commercial, infrastructure, and renovation projects stands at a transformative crossroads, where traditional project management methodologies converge with advanced data ...

As a data analytics company, innovation for ChaosSearch means finding new ways to streamline the extraction of insights from all kinds of enterprise data — AI is the next frontier in that regard.

Fanruan FineChatBI: Summary of the Conversational BI Innovation Data Analysis Process Report ...