Data Platform Migration | Starschema

Data Platform Migration

Practice Area

  • Data Engineering

Business Impact

  • Reduced license and hardware costs
  • More efficient reporting process

Challenges

  • Slow data platform performance
  • Hard deadline implement a new data platform

Technologies

Oracle, HVR, Talend, Tableau, Greenplum

Summary

When large organizations merge or divest, then new entity has business transformation thrust upon it. Our client, a power generation manufacturer, divested from a larger organization to become a brand-new company. With the looming deadline of a cut-over from the existing data platform, the client engaged Starschema to validate and test the existing technology stack and determine the best way to move forward.

Challenge

The client had an existing, on-premises data platform for handling commercial data but was suffering from slow report loading, sometimes longer than 60 minutes, frustrating the primary data consumers, the sales and marketing teams. The performance issues drove some groups to turn to shadow IT solutions, building their own, parallel data platform. As part of the divestiture, the client wished to take the opportunity to look at migrating its data platform to the cloud. Part of the technology evaluation included the feasibility of migrating the stack components to the cloud.

Solution

Starschema data engineers completed a full design review of the existing technology stack which included Oracle ERP as the system of record, HVR for data replication, Greenplum as the database, Talend for ETL, and Tableau for data visualization. This design review included a detailed review of code and configuration for the various technologies used as well as reviewing data governance.Our experts designed a cloud-based architecture incorporating the existing technology on-premises components. After a lengthy testing phase and a Proof of Concept (PoC), the Starchema team optimized the components of the existing data platform to increase performance, validating the technology stack for post-divestiture operations.

Results

With a successful migration of the Oracle ERP source system to Oracle cloud and the other data platform components to an AWS environment, the client has benefited from reduced hardware, license, and maintenance costs. The new, cloud-based data platform renders reports several times faster than the on-premises version.

Introducing the Stack of the Future for Modern Data Leaders

Fast unobstructed access to data and time to insight matters more now than ever. In these quickly changing times, businesses must innovate and implement a ‘Stack of the Future’ to be able to make accurate, data-driven decisions in minutes, not hours or days. The potential value of data is well known but in the new environment, the ability to easily share and collaborate on data is a competitive differentiator that will be leveraged by forward-thinking companies

COVID–19 Data Set Modeling and Analytics

During times of crisis, companies must look at the available data — both internal and external— and try to understand how that data can be used to determine how the business is currently being impacted, how it is likely to be affected in the future, what are most likely scenarios that will play out, what can be done to counter those scenarios and take advantage of hidden opportunities in this rapidly changing environment. The Starschema COVID-19 dataset ingests reliable data from multiple sources and makes it analytics-ready so it can be easily accessed and used.

A DataOps Journey

Keeping your data platforms running with operational efficiency is both paramount and can be a costly and complicated endeavor. Join us and learn how to apply strategies, techniques, and tools to build a reliable and effective DataOps practice in your organization.

Working with the COVID-19 Data Set

During this time of crisis, everyone is searching for answers. Governments, healthcare institutions, non-governmental organizations, and businesses large and small urgently need to make decisions about their future. We believe they should be armed with accurate, easily accessible, analytics-ready data. That’s why we collated, curated, and unified the most credible and reliable public data sets into a single source of truth data set.

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