Microsoft recently introduced a comprehensive analytics solution for its enterprise customers, Microsoft Fabric. The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform. Microsoft Fabric offers a unified platform for data engineering, science, and analytics, integrating data from Power BI, Azure Synapse, and Azure Data Factory, and using open storage for accessibility and portability.

Struggling to ensure accurate and efficient data exchange? EDI data mapping is the answer to streamlining your business’s communication pipeline. This indispensable process converts data into universally recognizable formats for seamless transactions with trading partners. Discover how to implement EDI data mapping effectively with our comprehensive guide, designed to give you the edge in today’s data-driven marketplace.

Tech debt is the cost of choosing quick solutions over better ones, requiring future rework. It is a fact of life for developers–when work piles up and deadlines approach, you prioritize what’s most important. In the short term, taking the easy road keeps your release schedule on track and your applications running smoothly, at least on the surface.

In our latest research, conducted this year with AIIA and FuriosaAI, we wanted to know more about global AI Infrastructure plans, including respondents’: 1) Compute infrastructure growth plans 2) Current scheduling and compute solutions experience, and 3) Model and AI framework use and plans for 2024. Read on to dive into key findings! Download the survey report now →

In February, Snowflake released a slew of new features that continue to expand the scope of what you’re able to do with Snowflake, including the public preview of Hybrid Tables. Read on to learn more about everything we announced last month.

Organizations are constantly seeking more efficient ways to extract, transform, and load (ETL) data into their data warehouses. Snowflake, is one of the leaders in cloud data warehousing, has traditionally recommended ETL/ELT processes for data ingestion and extraction. However, for organizations building internal data products, there is a new kid on the block: API generation. Here’s the key things to know from this article.

We’re constantly bombarded by data points and it takes real effort to make sense of them. While having a lot of information is a good thing, it’s easy to get overwhelmed and miss what’s really important. Businesses especially need to be able to sort the wheat from the chaff and assess their data accurately. But, how do you go about this exactly?