Data Warehouse Modernization: Making Enterprise Data Future-Ready

When everything is modernizing, why not data?

With rapid technological advancements, evolution is essential in almost every facet of the digital transformation of organizations. Enterprise Data Warehouse (EDW), the heart of data-driven decision support systems, also continues to evolve at a rapid pace. Data warehouse modernization to the Cloud enables the legacy environment to effectively meet quickly changing business requirements and technology challenges, as well as rapidly iterate new solutions that support future data analytics workloads at any scale.

Companies are willing to make large-scale investments towards modernization now more than ever, keeping in mind that this level of organizational change does not show immediate impact upon a complete digital transformation. They are aware of the long-term benefits for technology and people management that come with EDW modernization.

EDW modernization to the Cloud is considered as the first step of digital transformation for many organizations. But it is met with challenges. One of the major challenges that make companies pause before investing is the time it takes for any visible ROI, due to a multitude of reasons. Not only this, there are numerous other challenges faced by companies when modernizing their data warehouse.

Fear of Vendor Lock-In

Quantiphi Solution

Quantiphi embraces cloud technologies that are built on open-source services and technologies. Our partnerships with the top cloud providers ensures that customer use cases are supported with required scalability, the correct technology stack, and flexible solutions that are agnostic of vendors.

Data Security

Data is a highly lucrative asset for any business. As a result, the fear of any potential data loss remains prevalent for most businesses across industries. Companies, therefore, need to ensure that their sensitive data is secured during and post migration to a target destination.

Quantiphi Solution

Quantiphi never focuses solely on how to address a data breach. Instead, we ensure that it never occurs in the first place. Moreover, our custom data loss prevention solutions can be built around the business use case for a more secure migration.

Time to Insights

Deriving insights critical to business decisions during their modernization journey is the result of several months of migration efforts. This process is very time-consuming and requires collaboration among all teams to get the most out of the data.

Quantiphi Solution

Companies are strongly recommended to detail their expectations of the final use case as precisely as possible to obtain the exact results they desire. With these plans in place, Quantiphi handles the lengthy modernization process with our EDW migration accelerators that reduce time by 30-40%, enabling businesses to perform advanced analytics on their data faster.

High Infrastructure Costs

Handling data on-premise is particularly expensive if companies plan to continuously expand their business. When organizations plan to modernize, managing infrastructure like new hardware, application services, and potential system failures often leads to passing the opportunity for valuable insights because of the steep initial cost.

Quantiphi Solution

Quantiphi helps businesses handle cost-efficiently. For example, data lakes are a relatively cost-effective storage option on the cloud that can be scaled for multiple applications. Moreover, optimized algorithms can reduce power consumption, ultimately saving any additional overhead costs.

Key modernization challenges can be efficiently overcome with a roadmap and its subsequent implementation, as illustrated in the example below, in which Quantiphi helped a commercial insurance company undergo a complete EDW modernization journey.

The path to transformation with EDW modernization

One of the largest commercial insurers in the United States, sought Quantiphi’s help in driving self-service analytics, data science, and reporting capabilities by migrating claims, premiums, policies, and financial transactions data from Oracle Exadata to Google’s BigQuery.

The client’s goal was to reduce reliance on existing complex on-premises data procedures and minimize expensive operational overhead from sustaining such infrastructure. To achieve this, they first had to address the below-mentioned bottlenecks when maintaining their Oracle Exadata system:

• Massive operational overhead from running an on-premise Oracle system consisting of 150 terabytes (TB) of data in total, 30TB of which mapped to over 1500 tables and 2000 queries
• Poor performance due to the current legacy infrastructure’s lack of computational capacity
• No privacy protection mechanism for Personally Identifiable Information (PII)
• Lack of real-time data to perform any advanced analytics

As a starting point, Quantiphi migrated accounting center data to Google Cloud Platform in order to build a financial transaction data warehouse model. Following this, the client’s claims and suffix data, and its related downstream applications were migrated to Google Cloud and a unified claims data warehouse model was created on Google’s BigQuery.

To reduce development time and costs, Quantiphi’s internal data migration accelerators were used to accelerate the discovery of the client’s legacy Oracle warehouse, managed PII information, and converted Oracle Exadata schemas and data to BigQuery through automated scripts. This further enabled the client’s financials and claims data migration and eventual modernization to a production-ready state in less than 15 weeks.

The client now has a unified BigQuery data warehouse that stores 30 terabytes of financial data with increased performance and data security measures. Quantiphi also developed:

• A custom Data Loss Prevention solution for handling sensitive or PII information on the cloud and designed an effective governance model for the client’s users
• Self-service pin boards in Looker and ThoughtSpots for business users to enable streaming data on the cloud
• Scalable computing capabilities for advanced and predictive analytics

For the client, EDW modernization from Oracle Exadata to Google’s BigQuery improved their data processing and consumption capabilities along with faster access to real-time data querying. Not only did we accelerate the client’s daily and monthly streaming data requests through automation and operationalization on the cloud, but we also enabled a sophisticated and custom data security solution for any sensitive PII data leaving the warehouse.

The client saw a 3X growth in its customer base due to its newfound self-service analytical capabilities and faster dashboards for business users.

Modernizing your traditional enterprise data warehouse and providing a foundation for future AI, machine learning workloads and advanced analytics, is increasingly becoming essential for companies to stay competitive. We at Quantiphi and our team of Cloud Engineers are highly skilled at moving legacy systems to the cloud and helping you manage them effectively; ensuring greater cost savings, improved data security, scalability and easy management for businesses across industries.