How Data Lakes Can Help Your Journey to Becoming Data-Driven

In 2023, the challenge of becoming a data-driven organization is more evident than ever. Companies need key customer insights to compete in an increasingly crowded market. Meanwhile, the amount of information they need to sort through to find those insights grows every day.

Data lakes can help you gather the right information quickly and take advantage of non-traditional data sources. That’s why these repositories can often advance a company’s journey to becoming data-driven. Below, learn more about data lakes, when they might be the right solution for you, and how to get started.   

What Is a Data Lake?

A data lake is a repository primarily known for storing unstructured data, such as real-time information. Data normally enters the system “as-is,” meaning it is initially less uniform than you would find in a data warehouse. A data scientist within your organization will need to make sense of the information before business users can discover insights. To compare data lakes and data warehouses more in-depth, check out our e-book. 

What data lakes lack in initial structure, they make up for in utility. This is where you will find video files, images, social media mentions, and other insights from non-conventional data sources. Data lakes are also where business leaders will want to turn to leverage real-time data, allowing them to make decisions with the most up-to-date information possible. 

How Do I Know If a Data Lake Will Help My Journey to Becoming Data-Driven? 

Here are some of the key signs that your organization may benefit from a data lake: 

• Your company does not currently have a centralized data repository, meaning that individual departments have their own siloed information hubs. 
• You benefit from a diverse array of data, such as insights found in images and video files.
• It’s important for your company to capture real-time mentions on social media. 
• Your organization has a data warehouse but cannot solely rely on historical data.
• Data scientists at your company have asked for access to a wider array of raw data. 

What Does It Take to Build and Maintain a Data Lake? 

Like any digital system, it’s important to not just build a data lake but also to ensure it stays in great shape for users. Here are some steps you will need to take to put your data lake in the best position possible:

• A data lake should only be consuming accurate and relevant information.
• The repository should be accessible to all authenticated users at the company.  
• There should be a record with all the information that entered the data lake. That way, a user looking for historical data can easily access an archive. 
• Data security and protection should always be top-of-mind.
• Data archiving strategy and retention policies need to be planned to reduce costs.
• Plan to create a data catalog so your lake remains organized and does not turn into a data swamp. 

Another thing to consider about data lakes is that there are different areas (commonly called “zones”) that your organization should be monitoring. These zones are: 

• Raw zone: Where you store all data that has not been transformed 
• History zone: Area where you can view all versions of the previously ingested data
• Work zone: Where data scientists work to study, explore, and structure data
• Sensitive zone: Stores data that has restricted access 
• Gold zone: Area for transformed data that is ready for business users 

Final Thoughts 

Data lakes help organizations centralize their insights, allowing business leaders throughout the company to make decisions with the same high-quality information. This also leads to easier collaboration between teams, ensuring a more cohesive game plan from top to bottom in your organization. 

If you’re still unsure whether a data lake is right for you, check out our e-book, where we compare data lakes to other viable options, such as data warehouses and the emerging lakehouse. We can also help you throughout your journey to becoming data-driven, from understanding your current data maturity levels to building the right repository for you. Learn more on our data analytics services page. 

Let us know how we can help you.