Data Lake

What is a Data Lake?

A data lake is a centralized repository that allows you to store and process large amounts of data in their original, raw format. Data lakes can handle different types of data, such as structured, semi-structured, and unstructured. These originate from various sources, such as databases, files, logs, social media, etc. 

Data lakes enable you to run different types of analytics, such as dashboards, visualizations, big data, machine learning, etc., without having to structure the data first. Data lakes are useful for use cases such as custom data collection.

Some of the benefits of data lakes are:

• They are flexible and scalable, as they can store any amount and variety of data
• They are cost-effective, as they can use low-cost storage and processing options
• They are fast and efficient, as they can provide real-time insights and data-driven decisions
• They are secure and compliant, as they can protect and encrypt data according to policies and regulations

Some of the challenges of data lakes are:

• They are complex and difficult, as they require skilled and knowledgeable users and developers

Did you know?

Qrvey’s embedded analytics solution comes with a built-in data lake powered by Elasticsearch. It’s one of the main reasons SaaS companies choose Qrvey. 

Read more here about Qrvey’s multi-tenant analytics solution powered by a data lake rather than the typical data warehouse options that leave you building the multi-tenant components yourself.