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Enterprise Data Lake

Build a Lake, not a Swamp

Enterprise Data Lakes can mean different things to different people, from an overgrown staging area for your EDW to a repository for semi-structured streamed data, to a bespoke solution to solve a specific business need.

Regardless of your specific use cases, planning, building and running an enterprise data lake can be challenging.  Here are a few questions to get you thinking.

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What is your Data & Analytics Strategy?

A Data Lake is not an island, but exists as part of a data and analytics ecosystem that includes pipelines, integration and data processing technologies, databases, analytics engines and data access layers.  Your business’s Data & Analytics strategy should be able to describe your approach to each of these areas and should include technologies and reference architectures.

One approach to starting on such a strategy is to begin with a capability model.  Core Compete has developed a Cloud Data & Analytics Ecosystem capability model that we use as a backdrop, to kickstart conversations on strategic decisions and technology roadmaps.


Do you have the experience to avoid mistakes, misstarts and reduce risk?

Technology selection and strategic planning are just the tip of the iceberg when it comes to developing an enterprise data lake.


Core Compete Solutions


IT department doesn’t have experience integrating cloud-based data processing and analytics solutions

Core Compete is partners with all of the major cloud vendors.  Whether you need AWS or want to build your data lake using Google BigQuery, we have the experience and the certifications to ensure success.


Building an enterprise data lake is more than just setting up the infrastructure.  It involves coordinating data feeds and delivery schedules, not to mention testing and validation.

Core Compete has implemented cloud-based solutions for some of the world’s largest and most demanding companies, across multiple industries.  We have the expertise and the resources to bring your project in on time and on budget.

Core Compete’s Agile Analytics approach to development delivers fast value to your business through an iterative approach to data development.  High performance data connectors and reference architectures mean our engineers can deliver fast, consistent, high quality data pipelines and integrate with your systems to deliver analytics in a fraction of the time.


What is plan for ongoing support and maintenance of your data lake?

Data Lakes require maintaining.  From basic operations support to DataOps, you need to account for ongoing support for the new technologies and processes that make up your Enterprise Data Lake.

Core Compete’s commitment doesn’t end with the project.  Our A3 Management Platform offers full application aware monitoring and system maintenance for our clients.  DataOps support ensures that the data and analytics are available on time to meet the needs of your business users.

Core Competes expert team of data architects and engineers can build a scalable solution that integrates with your existing data and analytics ecosystem.  Regardless of where you are on your data lake journey, from inception through development to management, Core Compete offers comprehensive services keep your Data Lake from becoming a data swamp.

Breadth of Experience

Core Compete understands Teradata and BigQuery.  We’ll help you understand the sometimes-hidden scope of a migration initiative, discuss architectures that can ease the conversion and share lessons learned from our experience in migrating customers from Teradata to Big Query.


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Connect with our Enterprise Data Lake Specialists

Nageswara Sastry


Nageswara has 15 years of experience in architecting and implementing various cloud and analytic solutions for customers. He has previously worked for Tech Mahindra, SAS R&D and Bank of America. Outside work he likes to listen to music and play with his daughter. He is now trying to learn and understand various languages that his daughter started speaking.

Sumanth Yamala


Sumanth is an architect and leads the US data engineering practice. Sumanth has experience architecting enterprise applications in analytic and pricing domains, and enabling them in the cloud. He loves nature and walking.

Gaurav Mittal


Gaurav has about 14 years of experience in Big data and analytics space. Gaurav comes with extensive experience of architecting and implementing big data platforms in the cloud. Gaurav is passionate about learning new technologies and delivering customer success. He also enjoys reading books and playing badminton in his free time.

Khalid Soufny


Khalid has over 25 years’ experience delivering Analytics Solutions for various industries such as Specialty Pharmacy, Big Pharma, Hospitality, Retail and Manufacturing. Most recently, Khalid worked for Oracle USA developing BI Solutions for Oracle Knowledge platform. He loves traveling to Europe especially Paris and Barcelona.