Introduction

For the enterprise, You need secure data storage. Datawarehouse can be one method to implement. Lately, enterprises prioritize handling information management in a more structured manner. So that the data accessed can be stored and maintained properly. In this article, we will discuss a lot about data warehouse security. The general definition of a data warehouse is a computer system whose job is to archive and analyze historical data for a particular organization or business. Information that is managed can be in the form of data related to sales, salaries, and other daily information. By analyzing structured data, it can produce more accurate information to support decision-making by a company. That is why the data warehouse is included in one of the parameters supporting business intelligence activities. It is the foundation of business performance monitoring.

Every company stores information that cannot be exposed to everyone who works in the company. When moving from a Data Lake to a Data Warehouse more people will gain access to data. You need to ensure that sensitive information is aligned. to what is being stored, how it's restricted in the Data Warehouse, and how it can be accessed via your BI tools.

How to secure sensitive data on the warehousing

The most direct way to limit access to the proper people is to enforce rules on the database level. This can be done by creating slave read-only replicas, creating custom user groups, and encrypting sensitive data.

Slave read - Only

Set up your warehouse to be read-only by default. This prevents any dangerous SQL write statements from being executed on your data.

Custom User Group

Regardless of whether you create the slave read-only warehouse, create a new user group that has read access only. You can choose to exclude access to specific tables or columns of data from that new user group. In addition, you can restrict access to row-specific data. Row-level permission allows you to give full access to tables containing sensitive information but restricts which rows and values the person querying can see. Depending on the underlying database, configuring row-level permissions differs slightly.

Encyrpt Volume

If you need to group or aggregate sensitive data you can create encrypted versions of the data. Then users can create summary tables where sensitive metrics, like financial data, can be aggregated to a level that is appropriate for different departments to see and analyze. The level of security you implement will limit what type of analysis can be performed on the data but does ensure that the sensitive data is protected.