Systems | Development | Analytics | API | Testing

Machine learning (ML) enables organizations to extract more value from their data than ever before. Companies who successfully deploy ML models into production are able to leverage that data value at a faster pace than ever before. But deploying ML models requires a number of key steps, each fraught with challenges.

Since we announced the general availability of Apache Iceberg in Cloudera Data Platform (CDP), we are excited to see customers testing their analytic workloads on Iceberg.

Every organization contends with numerous moving parts that drive business forward. But they can be inefficient and convoluted – in fact, Forrester research shows that 71% of organizations use 10 or more applications for a single business process. To make matters worse, only 16% of companies have complete visibility over their own processes. This is where process mining can help. How can you gain more clarity so you can improve efficiency within your organization?

As announced at Snowflake Summit 2022, Iceberg Tables combines unique Snowflake capabilities with Apache Iceberg and Apache Parquet open source projects to support your architecture of choice. As part of the latest Iceberg release, we’ve added catalog support to the Iceberg project to ensure that engines outside of Snowflake can interoperate with Iceberg Tables.