Systems | Development | Analytics | API | Testing

BigQuery federated queries gets SQL pushdown, private IP access, priority queues for Spanner federation, and Spanner-to-BigQuery JSON type mapping.

Seamless and low-latency replication from operational databases, including PostgreSQL, directly to BigQuery, enabling near real-time insights.

With increased applications developed by different engineering teams on Kafka comes increased need for data governance. JSON is often used when streaming projects bootstrap but this quickly becomes a problem as your applications iterate, changing the data structures with add new fields, removing old and even changing data formats. It makes your applications brittle, chaos ensues as downstream consumers fall over due to miss data and SREs curse you.

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?

Data integration is the process of combining data from different sources and formats to create a unified and consistent view of the data. This involves merging data from multiple databases, applications, and other sources into a single repository, and transforming and formatting data so that it can be easily accessed and analyzed. Data assets need quality controls to ensure they are valid and reliable as many teams within an organization leverages the same data for different purposes.

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.

Data fabric might seem like yet another data management technological innovation you have to learn about—but this one is different from the rest. While technology continues to evolve, the data problems that enterprises face are in many cases getting worse over time: data, data, and more data is permeating the business.

In today's data-driven world, businesses are constantly generating vast amounts of data, which can provide valuable insights into their operations and customers. However, before data can be analyzed and used for decision-making, it often needs to be cleaned, transformed, and organized in a way that makes it usable. This is where ETL comes in.