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Experts predict that the global enterprise data management market will grow at a compound annual growth rate of 12.1% until 2030. Your organization’s database management system (DBMS) stores all the enterprise data you need for software applications, systems, and IT environments, helping you make smarter data-driven business decisions. Here are the key things to know about database schema design.

Microsoft Excel, a cornerstone in the realm of data management, is extensively utilized across various industries for its robust capabilities in data analysis, storage, and intricate calculation functionalities. However, when it comes to importing Excel files into other Software as a Service (SaaS) applications, users often encounter a range of import errors that can hinder productivity and data accuracy.

Generative AI’s (gen AI) capabilities seemed startlingly novel a year ago, when ChatGPT’s release led to an explosion of public usage and, simultaneously, intense debate about its potential societal and business impacts. That period of initial amazement and suspicion has given way to business urgency, as companies scramble to adopt gen AI in ways that leverage its potential for maximizing workforce productivity and profitability.

Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data—structured and unstructured. It offers several benefits such as schema evolution, hidden partitioning, time travel, and more that improve the productivity of data engineers and data analysts. However, you need to regularly maintain Iceberg tables to keep them in a healthy state so that read queries can perform faster.

With the increasing importance of real-time data in modern businesses, companies are leveraging distributed streaming platforms to process and analyze data streams in real time. Many companies are also transitioning to the cloud, which is often a gradual process that takes several years and involves incremental stages. During this transition, many companies adopt hybrid cloud architectures, either temporarily or permanently.

Imagine your software transforming from merely a tool into a strategic partner that can automatically alert your users to trends, provide explanations of data with a click, and help you ask the right questions of your data-sets - in addition to delivering data-led insights. This is the power of AI analytics solutions for independent software vendors (ISV). Today's users demand more than just functionality. They crave intelligent software that analyzes data, surfaces insights, and empowers them to act.

Snowflake kicked off 2024 with exciting releases, including Snowpark Model Registry, Streamlit in Snowflake for Azure, and new enhancements around security features in Snowflake Horizon. Read on to learn more about everything we announced in January.

In the previous blog post we covered the high availability feature of Cloudera Operational Database (COD) in Amazon AWS. Cloudera recently released a new version of COD, which adds HA support to Microsoft Azure-based databases in the Cloud. In this post, we’ll perform a similar test to validate that the feature works as expected in Azure, too.

From personal AI to the data that’ll train it, browse our bets on how AI develops in 2024 and beyond.

Imagine having the keys to a vault where every piece of data about your business is stored—not just any vault, but one that you built, control, and customize according to your precise specifications! This is the empowering reality of self-hosted analytics. It's like being the captain of your ship, navigating through the vast ocean of digital information with the confidence that comes from knowing every inch of your vessel.