There are various advantages because of which we chose Lambda Architecture for construction Data Lake for the enterprise. Some of these advantages can be given as:

• Data stored is in raw format. Because of this, at any time, new algorithms, analytics, or new business use cases can be applied to the Data Lake by simply creating new batch and speed views. This is one of the biggest advantages of traditional data warehouses in which data is cleansed and stored. Because of this, new use cases would need to change the data schema, and this is usually time and effort consuming.
• One of its very own important principles, namely recomputation, helps correct fault tolerance without much trouble. As more and more data comes into the lake, data loss and corruption can be something that cannot be afforded. Because of this recomputation, at any moment we can recompute, roll back, or flush data to correct these errors.
• Lambda Architecture separates different responsibilities into well-defined and bounded layers. By doing so, these layers can have different technologies and different optimization techniques can be employed to make it function better without any effect on that other layers. Some of the technologies used in these layers, including stores, can be swapped with a better one without much trouble.
• It provides a pluggable architecture. Adding a new type of source data or similar one already plugged in, the architecture is built to take in these source systems without many changes at all.