What is the Snowflake Data Lake and How Does it Work

Data lakes are structures that are used to store massive volumes of data that can be processed and analyzed later for business analytics. Data lakes are single entities, distinct from the past, where data was stored in various repositories such as data marts and data warehouses.

The launch of the Snowflake data lake, a cloud-based platform has done away with the need for deploying, maintaining, and developing separate data storage systems. This one all-inclusive data lake facilitates seamless management of data in its native format and all forms of data, regardless of whether it is unstructured, semi-structured, or structured can be loaded into the Snowflake data lake.

The functioning of the Snowflake data lake

Data movement within a particular data cloud environment is speeded up on the Snowflake data lake because of its extensible data architecture. Kafka or any other pipeline can be used to generate data and persist it into a cloud-based bucket. From this bucket, an engine and transformation mode such as Apache Spark loads the data into a conformed data zone after transforming the data into a columnar format like Parquet.

The benefits of the Snowflake data lake  

The Snowflake data lake provides highly optimized solutions and a cloud-based architecture that helps businesses to improve their data lake strategy to meet specific organizational needs.

There are several advantages of using this cloud-based platform for meeting data-driven operational requirements.

• Organizations do not have to choose between using a data warehouse and a data lake as all the components of a data storage repository are incorporated in the data lake. It is a single-point data storage system where large volumes of data in their native states like ORC, JSON, CSV, and tables can be easily ingested without having to maintain separate silos.

• The Snowflake data lake offers high-performing computing powers and users do not face any lag or drop in performance even when simultaneously executing multiple intricate queries.

• Snowflake provides unlimited storage capabilities that are very affordable, charging users only the base cost of Snowflake cloud providers like Amazon S3, Google Cloud, and Microsoft Azure. Further, users have to pay only for the quantum of resources used instead of flat fees like traditional data storage systems.

• Snowflake guarantees data consistency as it can be easily manipulated and cross-database links with multi-statement transactions executed.

Some of the other cutting-edge benefits of the Snowflake data lake include using external tables to directly query data without moving it, synchronizing external tables with the Apache Hive meta-store, and increasing the speed and performance of queries by using materialized views instead of external tables. Moreover, data exploration can be optimized by using Snowsight which is an inherent visualization of the user interface for Snowflake.                      

Use the Snowflake Data Lake to process all data and easily transform it back into the data lake.