5 Key Benefits Of Building Data-Lakes

No More Data-Silos 

Usually, data in most of the organization is stored in various different locations in different ways with no centralized access management. It’s very difficult to have access to it and perform any kind of analysis. Data-lakes break down these data-silos and provide seamless access to the required data for meaningful insights and faster innovation.

Better Data-Governance 

Data-lakes allow you to receive both your structured & unstructured data from different data sources and store it in a centralized secure repository at any scale. This helps you to have better data-governance and control.

No-Predefined Schema 

With data-lakes, there is no need to have a pre-defined schema. This helps to process the raw data without having any information on the type of analysis that might be required in the future.

Store Data In Any Format

Data-lakes eliminate any requirements of data modeling during the data-ingestion. You can store data in data-lakes in any format & medium i.e. RDBMS, NoSQL Databases, File Systems, and Time Series Databases, etc. Data can be loaded in its existing format like a log, CSV, XML, parquet, etc. without any transformation. Data-lakes are quite cheaper as compared to traditional data warehouse as it allows to store data without any pre-defined format or schema.

Strong Foundation for ML & AI 

By having a centralized data repository in the form of data-lakes, multiple data-sets can be combined together to train and deploy machine learning models to perform predictive analysis and data usage patterns. Since data in Data-lakes is stored in an open format, It makes it easier for various ML/AI-based analytical services to process this data to generate meaningful insights