When choosing a modern database, one of the biggest decisions is picking a relational (SQL) or non-relational (NoSQL) data structure. Both systems offer unique advantages and cater to different needs, making the choice between them crucial for optimal data management.

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.

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.

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.

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.

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

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.

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.

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.