Data storage and warehousing concepts to know as a data scientist👇
Data storage and warehousing are important components of modern data engineering.
With the exponential growth of data, it’s critical to have an efficient and scalable storage solution in place that can handle large amounts of data.
In addition, data warehousing enables organizations to store, organize, and analyze data from various sources in a centralized location, providing a more complete view of the organization’s data.
Let’s look at the tools and technologies to learn for data warehousing:
• Familiarity with data storage solutions such as Hadoop, NoSQL, and columnar databases
• Knowledge of data warehousing concepts and tools such as Amazon Redshift, Snowflake, and Google BigQuery
• Experience with data modeling and schema design for data warehouses
• Familiarity with distributed systems