Get fresh updates from Hortonworks by email

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Sign up for the Developers Newsletter

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Get Started


Ready to Get Started?

Download sandbox

How can we help you?

* I understand I can unsubscribe at any time. I also acknowledge the additional information found in Hortonworks Privacy Policy.
closeClose button
August 01, 2018
prev slideNext slide

Fast Track to Optimize Your Enterprise Data Warehouse

Enterprise Data Warehouse (EDW) is traditionally used for generating reports and answering pre-defined queries, where workloads and requirements for service level are static. The drawback is that the platforms impose rigidity, because the schemas must be modeled in advance for queries that are anticipated. Constrained by this limitation, users cannot freely explore and ask questions from their data to enable timely responses and insights that drive the speed of business required to stay competitive today.


With the supplement of Apache Hadoop®, it not only contains the growing costs of running enterprise data warehouses, but also gives users the flexibility and reusability over the consumption of data with the introduction of schema-on-read. When Hadoop is used to optimize EDW, organizations can get the best of both worlds with the use of the EDW for standard operational queries, and Hadoop for exploratory analytics and workload shift.

Hadoop provides a versatile and extensible analytic platform that uses commodity hardware and open source innovation to deliver economies of scale. Enterprise Data Warehouse (EDW) optimization, where data- and compute-intensive processes are offloaded from the EDW to Hadoop, has proven to be one of the most popular use cases for the open source platform. EDW optimization is often one of the first use cases for Hadoop because it can readily deliver tangible results, thanks to:

  • Cost savings delivered by commodity infrastructure and open source software.
  • Proven capability to perform at scale.
  • Innovations that have brought interactive BI to Hadoop.
  • Productivity gains attributable to more efficient data enrichment and correlation.

However, the flip side is that making the proper configurations can be time-consuming because of the lack of expertise in integrating Hadoop into existing environments.


The Hortonworks solution for EDW optimization addresses the need for an ideal configuration while capitalizing on Hadoop’s versatility. The solution enables customers unfamiliar with Hadoop to gain immediate proof of value with EDW optimization through a guided, fixed term, fixed-scope engagement, for the delivery of a full Hadoop platform that will grow with customer needs.

Beyond that, the one-month jumpstart engagement, which bundles services, software, and integrations, offers a prescriptive best-of-breed solution that includes:

The solution guides customers through a “recipe” that generates production-ready online analytical processing (OLAP) cubes to which they can connect their designated BI tools. This encompasses rehosting data and ETL processes from the data warehousing environment onto the Hortonworks Data Platform (HDP), helping customers configure Hadoop and installing partner tooling for data integration and OLAP.

To learn more about the Hortonworks solution that can help you right-size your EDW in a time-efficient manner for accelerated time-to-value, please read the white paper below:

Using Hadoop to Optimize the Enterprise Data Warehouse

Leave a Reply

Your email address will not be published. Required fields are marked *