Data Lakes for Data Science

As data science aspirants and beginners, we tend to focus on the modeling and analysis aspect of an ML project, but often overlook the deployment and development part. One crucial aspect of this is having a centralized repository to store all our structured and unstructured data, which is where data lake solutions come in. In most interviews, candidates are asked about their experience with data lakehouses and warehouses, so here’s a quick revision on what a data lakehouse is and some of the most popular lakehouse solutions used in the industry.

💡Amazon S3 — A highly scalable, durable, and secure object storage service that makes it easy to store and retrieve any amount of data from anywhere on the web.

💡Google Cloud Storage — A fully-managed, highly-scalable object storage service that allows you to store and access data from anywhere on the web.

💡Microsoft Azure Data Lake Storage — A fully-managed, highly-scalable data lake storage service that allows you to store and access large-scale data sets in a cost-effective way.

💡Hadoop Distributed File System (HDFS) — A distributed file system that can store and process large-scale data sets across a cluster of commodity servers. It is often used in conjunction with other big data tools like MapReduce, Pig, and Hive.

💡IBM Cloud Object Storage — A fully-managed, highly-scalable object storage service that allows you to store and access large-scale data sets in a cost-effective way.

💡Snowflake Data Cloud — A fully-managed, cloud-based data warehousing solution that allows you to store, process, and analyze large-scale data sets in a cost-effective way.

💡Databricks Data Lake — A fully-managed, cloud-based data lake solution that allows you to store, process, and analyze large-scale data sets in a cost-effective way, and also supports data integration, data warehousing, and big data analytics.

As a data scientist, having a solid understanding of different data lake solutions and their capabilities will help you make the most of your data and drive insights for your organization.

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