Cloudera Data Warehouse
Welcome to the Guru How-To's for Cloudera Data Warehouse!
A modern data warehouse lets you share petabytes of data among thousands of users while maintaining SLAs and keeping cost down. It enables any form of consumption — standard reports, dashboards, or ad hoc queries. It accommodates any type of data — structured or unstructured. It supports any type of deployment — cloud, on-premises, or a hybrid of both. And, it enables any form of analytics — SQL, machine learning, or real-time.
Cloudera's modern Data Warehouse powers high-performance BI and data warehousing in both on-premises deployments and as a cloud service. Business users can explore and iterate on data quickly, run new reports and workloads, or access interactive dashboards without assistance from the IT department. In addition, IT can eliminate the inefficiencies of “data silos” by consolidating data marts into a scalable analytics platform to better meet business needs. With its open architecture, data can be accessed by more users and more tools, including data scientists and data engineers, providing more value at a lower cost.
Use these Cloudera Data Warehouse Guru How-To's to get started transitioning to a modern data warehouse.
|Cloudera Data Warehouse POWERED BY…|
|Apache Impala||Distributed interactive SQL query engine for BI and SQL analytics on data in cloud object stores (AWS S3, Microsoft ADLS), Apache Kudu (for updating data), or on HDFS.|
|Apache Hive on Spark||Provides the fastest ETL/ELT at scale so you can prepare data for BI and reporting.|
|SQL Development Workbench (HUE)||Supports thousands of SQL developers, running millions of queries each week.|
|Workload XM||Provides unique insights on workloads to support predictable offloads, query analysis and optimizations, and efficient utilization of cluster resources.|
|Cloudera Navigator||Enables trusted data discovery and exploration, and curation based on usage needs.|