Systems | Development | Analytics | API | Testing

Picture this: As you’re analyzing sales data in Qlik or in Power BI, you spot an obvious error in a customer name and think “I wish I could just fix this right here instead of sending another email to IT.” If this sounds familiar, you’re not alone. The good news is that the business intelligence (BI) world is finally listening. Gone are the days when BI platforms were solely for consuming and analyzing historical data.

Data activation maximizes the value of existing data infrastructure by reducing manual work, increasing reach, and enabling data teams to drive more strategic impact.

Every second counts in modern IT. The rise of hybrid environments – with fragmented data, complicated recovery and increasingly high costs – isn’t making things faster or easier. While managing complexity across different infrastructures, ensuring consistent application performance, and maintaining strict compliance standards have all become table stakes, many IT and security leaders still struggle with limited visibility, making risk management difficult.

Fivetran delivers enterprise-grade performance and offers speed and reliability at scale, but Stitch’s free plan is a solid pick for startups with lighter data needs.

When comparing Apache Parquet and Apache Iceberg, we need to first understand the differences between file formats and table formats. Parquet is a file format, whereas Iceberg is a table format. File formats focus on efficient storage and compression of data. They define how the raw bytes representing records and columns are organized and encoded on disk or in a distributed file system such as Amazon S3. The Parquet file format has become the de-facto standard for storing data used in analytics workloads.