Data Lake Design and Implementation

Approach:

Through a set of exploratory workshops with all involved stakeholders, Adastra first works to establish a set of requirements for the data lake: a comprehensive list of data sources that will feed data into the cloud data lake, identify data ingestion mechanisms and analyze downstream data consumption patterns to design optimal data storage and partitioning strategy. If this is your organization’s first cloud project, our team will help you establish all necessary, cloud-based infrastructure and security mechanisms. If you plan to expand your activities in the cloud beyond the data lake, we will help you create a roadmap.

Activities:

• Conduct a series of exploratory workshops to get acquainted with the organization’s data strategy and long-term plans.
• Create a catalogue of the requirements for the data lake.
• Create a high-level design of the solution, making sure it integrates well with existing environments, while taking into consideration the possibility of future cloud migrations.
• Create an end-to-end implementation plan, defining scope, timelines, milestones, and deliverables.
• Define data ingestions strategies for all sources in scope.
• Implement data pipelines to ingest data from any identified source and process the raw data into a standardized and efficient data format, allowing for further cost savings.
• Configure CI/CD pipelines to automate testing and deployment.
• Conduct knowledge transfer and training sessions, making sure all technical and business users are well-acquainted with the delivered data lake solution.

Deliverables:

• Established end-to-end development, testing, and production AWS environments
• Implemented data pipelines to ingest data into the AWS Data Lake and process data within it
• End-to-end scheduled and orchestrated processes
• Automated testing and deployment processes
• Technical documentation and an operations manual

Outcomes:

• Unlimited scalability – take advantage of practically unlimited storage scaling.
• Optimal cost – intelligently and dynamically change the storage class of certain data files to drastically reduce the storage cost.
• Flexibility – AWS provides numerous services to allow for easy ingesting of any data into the data lake.
• Easy access to data – queries to raw and curated data can be executed for the shortest time to insights.
• Democratized data – AWS provides the ability to a much larger number of people in your organization to benefit from extracting business value from the data in the data lake.
• Out-of-the-box security – leverage the built-in AWS security mechanisms to meet compliance and legislation requirements.