Best Practices for Designing Your Data Lake

Data lakes are complex yet efficient ways to store large amounts of data, and if structured correctly they can be extremely useful. However, this complexity also allows for mistakes to be made which can prevent the Data Lake to perform at its best.

Checklist for Data Lake success

Identifying Business-benefits

Investing in a data lake is worth only if it provides value for a business, that’s unavailable from EDW. Being able to define and articulate this value and convince stakeholders about it is vital to begin this journey.


After identifying the business alignment, it is necessary to define the components a data lake ought to be built of. You may not have complete clarity to begin with (and this is where a Proof-Of-Concept engagement can be helpful to tune and learn along).

Two critical components to build a well-governed data lake are 1.  Data management strategy (that includes data governance and metadata management) 2. Security strategy (which includes regulatory rules and privacy agreements)

I/O and memory model

While designing a Data Lake architecture, it is essential to decide its technology platform and scale-out capabilities. From a data ingestion standpoint, it is required to understand the throughput requirements which will in turn dictate the throughput for storage and network.

Operations plan

To effectively run a Data Lake, proper SLAs are required. Identify SLA requirements (like downtime, data ingestion, processing, and transformation) for business-critical applications that are revenue impacting. A disaster recovery plan is also required to support these SLAs.

Workforce involvement

For a successful data lake implementation, experts with extensive experience in data management & governance are required to clearly define the policies and procedures upfront. Involving Data Scientists (who’ll be the consumers of Data Lake) to hear their requirements and preferences (to interact with the Data Lake) will make a huge difference in making the project successful.

Every industry works differently and therefore a data lake should be created considering this too. The way a data lake works for one industry will be vastly different to that of another. To find out more about data lakes, reach out to us.

We at Agilisium specialise in helping businesses to design and create high performing data lakes for any industry. Get in touch today for more information.