AWS Data Lake Implementation

Ingest, store, and access data in any format and volume at unmatched availability. Get the best performance at the lowest cost.

Why Implement an AWS Data Lake?

Realize optimal business value within a data-driven culture by implementing an AWS Data Lake. Utilize a consistent and robust approach to acquire vast amounts of data. In combination with Adastra’s thorough understanding of data and modern data governance practices, your data will be usable for data-driven decision-making.

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 a variety of services to allow for easy ingestion of 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 for 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 built-in AWS security mechanisms to meet compliance and legislation requirements.

Modernize Your Data Estate with AWS Data Lake now

Easily move data between data lakes and purpose-built data services enabling easy data access wherever it’s needed. Enforce access controls from a single place for all services for superior governance.

What Do We Do

Adastra can help you plan and efficiently implement a data lake in the AWS Cloud. As a trusted AWS partner, you can tap into our vast expertise and rely on us to help guide the way for your organization to create a secure and cost-efficient cloud-based single shared repository of data.

Strategy Alignment and Roadmap

Adastra will help you identify your data strategy, cloud maturity and environment. Based on the findings, we not only design your data lake solution as per your requirements, but also create a roadmap for future development and advanced usage of the data lake across the entire organization.

Implement

Leverage our experienced team of seasoned professionals to create the data lake and necessary data pipelines for you, establish CI/CD pipelines, and make sure all security mechanisms are in place. Tap into Adastra’s expertise and benefit from proven frameworks, based on best practices.

Knowledge Transfer

We make sure your team is fully capable of managing the implemented data lake and is comfortable working with it. Optionally, you can benefit from Adastra’s managed services where we will run and update the data lake for you.

Approach to AWS Data Lake Implementation

  • Identify all stakeholders.
  • 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 to 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.
  • Optionally, if you plan to expand your activities in the cloud beyond the data lake, we can help you create a roadmap.

  • If this is your first cloud project – our team will help you establish all necessary, cloud-based infrastructure and security mechanisms.
  • 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.

  • Deliver detailed technical documentation which will allow your team to run the data lake
  • Conduct knowledge transfer and training sessions, making sure all technical and business users are well-acquainted with the delivered data lake solution.
AWS Data Lake Implementation in Healthcare
Success Story

10x Increase in Analytics Team Productivity with an AWS Data Lake Implementation

Skylight Health Group is expanding and acquiring new clinics, along with all their data. The group needed to integrate numerous electronic medical records (EMR) systems and provide healthcare practitioners with predictive analytics.

Adastra built a data management solution that makes it easy for Skylight Health’s teams to add users and access real-time data—without more infrastructure.

10x

more productive analytics team

0

manual effort needed to produce unified and consolidated reports

0

infrastructure maintenance needed

“The level of cooperation between members of our organization and Adastra has always been outstanding. The implementation of the AWS Cloud Analytics Platform powered complex insights into our business in an automated fashion.”

Chris Smith | VP Digital Health, Skylight Health Group

Frequently Asked Questions

A data lake is a system of technologies that allow for the ingestion, storage, management and querying of batch and streaming data at tremendous scale and cost-efficiency. Such a centralized repository of data allows for advanced analytics capabilities, enabling organizations to discover more and more business value in the data they generate. Since the introduction of the term “data lake” in 2010, the number of organizations which have adopted a data lake architecture has increased exponentially.

A data warehouse is an online analytics processing (OLAP) system, which aims at integrating together well-defined and structured data sets (“schema on write”) in order to provide business users with the answers to a set of predefined questions and give them some (but limited) self-service reporting capabilities.

A data lake is aimed at ingesting any data, thrown at it (“schema on read”), in a performant and cost-effective manner. A data lake stores raw data and the only data processing that is applied on the data would usually be done in order to convert the data to a more efficient format, perform data profiling and data quality checks. However,it does not process the data to make it more suitable for the needs of a single downstream consumer. A data lake can easily be the main (or single) source of data for a data warehouse or can simply complement it.

The advantages of cloud services vs. on-premises infrastructure and solutions are numerous. First, the cloud allows you to avoid huge capital expenditures and the risk that you will under or overprovision the necessary hardware. Also, there is no need to adjust your organizational structure to make sure that you have teams who can manage the required on-prem hardware, software, networking, security, etc.

With AWS services you can cut capital expenditures and replace them with much more effective and reduced operational expenditures. As you pay only for what you use, your solutions can scale both vertically and horizontally depending on the workloads in a matter of minutes. Your organization can take advantage of the shared responsibility model and fully managed services, where AWS as a service provider will take care of security, maintenance, patching, and more, so your organization can focus on mission-critical activities.

Let’s modernize with AWS Data Lake