Data marts are a subset of a larger data warehouse, specifically designed to focus on a particular subject or department within an organization.
They’re used to store and manage a subset of data that’s relevant to a specific business function or department, such as sales, marketing, or finance.
The main reason data marts get used in data analytics is they allow for more efficient and targeted data analysis. By isolating a specific subset of data, data marts make it much easier to access and analyze the information that’s most important to a particular department or business function which eliminates the need to sift through large amounts of irrelevant data, saving time and resources.
Data marts can also improve data governance by allowing for more granular control over data access and security. That’s because data marts are typically designed and managed by the specific department or business function that will be using the data, rather than a centralized IT team.
That then allows for a more tailored data management and security protocol that are better suited to the needs of the specific department or business function.
They’re also useful for improving the performance of business intelligence tools, since they’re smaller in size and can quickly be queried so the performance of the analytics will be faster.
What’s a one-way data mart?
A one-way data mart, as the name suggests, is a type of data mart in which data flows in one direction only.
This means that data is loaded into the data mart from a source system, but can’t be updated or modified once it’s in. The purpose being to create a read-only copy of the data that’s isolated from the source system and can be used for reporting and analysis without the risk of modifying the original data.
As an example, in sectors such as finance or healthcare, where data integrity is critical, one-way data marts can be used to ensure that sensitive information is not accidentally modified or deleted. This also increases the security of the data, as it can’t be tampered with.
Another advantage of the one-way data marts is that they can be used to improve data governance. By creating a read-only copy of the data, it becomes much easier to track and audit changes to the original data, as any modifications made will be clearly visible in the data mart. This also makes it easier to detect and prevent data breaches.
Finally, they can also be useful for performance optimization.
With a read-only data mart, the data isn’t updated, so the performance of querying the data will be faster.
Benefits of one-way data marts
The benefits of one-way data marts are clearly many, but some of the most notable include:
Improved data governance: One of the biggest advantages of one-way data marts is that they improve data governance. By creating a read-only copy of the data, it becomes easier to track and audit changes to the original data, as any modifications made will clearly be visible in the data mart. This makes it easier to detect and prevent data breaches and other security issues. Additionally, it also helps organizations to comply with data protection regulations such as GDPR and HIPAA.
Simplified data analytics: Another advantage of one-way data marts is they simplify data analytics. By isolating a specific subset of data, data marts make it easier to access and analyze the information that is most important to a particular department or business function. This eliminates the need to sift through large amounts of irrelevant data, saving time and resources.
Increased data security: One-way data marts also increase data security is in preventing data modification. This is especially important in industries such as finance or healthcare, where data integrity is critical. By creating a read-only copy of the data, one-way data marts ensure that sensitive information is not accidentally modified or deleted. Additionally, it also makes it harder for malicious actors to tamper with the data.
Best practice for building a one-way data marts
Building a one-way data mart can be a tricky process, but with the right approach, it can be done successfully
Identify the right data sources: One of the first steps in implementing one-way data marts is in identifying the data sources that will be used to populate it. This could include transactional systems, external data sources, or other data warehouses. It’s important to choose data sources that are relevant to the specific business function or department that the data mart is being created for.
Choosing the right data integration tool: Once the data sources have been identified, the next step is to choose the right data integration tool to extract, transform, and load (ETL) the data into the data mart. There are many different ETL tools available, each with their own strengths and weaknesses, so it’s important to choose one that’s well-suited to the specific needs of the organization.
Designing the data mart schema: After the data has been extracted and transformed, the next step is in designing the schema for the data mart. That includes creating tables, defining relationships and setting up indexes. It’s important to design the schema in a way that makes it easy to access and analyze the data, whilst also ensuring that it’s properly secured and governed.
One-way data marts are a very specialized type of data mart that can bring many benefits to organizations looking to protect and analyze sensitive data.
They improve data governance, simplify data analytics, and increase data security.
These benefits make them an essential tool in the modern data scientists kit but if you’re not sure where to start, as always, DoubleCloud would be happy to help.