Systems | Development | Analytics | API | Testing

Most organizations spend at least 37% (sometimes over 50%) more than they need to on their cloud data workloads. A lot of costs are incurred down at the individual job level, and this is usually where there’s the biggest chunk of overspending. Two of the biggest culprits are oversized resources and inefficient code. But for an organization running 10,000s or 100,000s of jobs, finding and fixing bad code or right-sizing resources is shoveling sand against the tide.

Retail companies can easily visualize and analyze their geospatial data in BigQuery using the CARTO platform.

Recently, we announced enhanced multi-function analytics support in Cloudera Data Platform (CDP) with Apache Iceberg. Iceberg is a high-performance open table format for huge analytic data sets. It allows multiple data processing engines, such as Flink, NiFi, Spark, Hive, and Impala to access and analyze data in simple, familiar SQL tables.

Unify data from diverse sources and formats using Aiven Kafka's open source streaming. Analyze with BigQuery for swift, accurate insights.

Elements of the Google Data Cloud including BigQuery, DataFlow, and Vertex AI are behind Glean’s personalized enterprise search platform.

To get the most out of any application, a graphical user interface improves your efficiency and data streaming without exception. A UI should help you through the steps of an often-complex flow as the visible layer between your problem and solution. Even the most hardcore back end enthusiasts will admit that its significance is undeniable for a complete product. It has to be well organized and easy to understand, yet be able to provide the right tools in the right place.