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How can data retention policies help you manage your data warehouse growth?

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Data warehouses are essential for storing, analyzing, and reporting on large volumes of data from various sources. However, as data grows, so do the challenges of managing the data warehouse efficiently and cost-effectively. One of the key aspects of data warehouse management is data retention, which refers to how long you keep the data in the warehouse and when you delete or archive it. In this article, you will learn how data retention policies can help you manage your data warehouse growth by optimizing performance, reducing storage costs, and complying with regulations.

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Tomas Peluritis

Data Person | Data Engineering, Technical Leadership | Uncle Data
Arockia Nirmal Amala Doss

Founder, Data Engineer @ ZippyTec GmbH | Data Migration & Data Engineering Consulting | Data Migration Coaching | AWS…

1 What is a data retention policy?

A data retention policy is a set of rules that define how long you store different types of data in your data warehouse and what actions you take when the data reaches its expiration date. For example, you may decide to keep transactional data for one year, aggregated data for three years, and historical data for five years. You may also choose to delete, archive, or anonymize the data when it is no longer needed. A data retention policy should be aligned with your business goals, data quality standards, and legal requirements.

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Tomas Peluritis

Data Person | Data Engineering, Technical Leadership | Uncle Data
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Significantly simplified, it's just a set of rules for legal/compliance reasons or to minimise data size. These rules are usually connected to GDPR, client data processing agreements etc, but they can also be added in order to make your queries run efficiently and not scan over too much of the irrelevant data.

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Jithin Majeed

Data Engineering | Data Architecture | Data Visualization | Building Scalable Data Solutions
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Data retention policies are vital for managing data warehouse growth as they establish rules for data storage, archiving, and deletion. By defining when data should be removed or archived, these policies prevent the accumulation of unnecessary data, leading to efficient storage resource utilization. As a result, data warehouses become leaner, perform better, and are easier to maintain. Retention policies also help organizations comply with regulations, control costs, and ensure that data remains accessible for analysis. They are a fundamental component of data governance and facilitate structured data management, optimizing data storage while retaining historical data for historical analysis and decision-making.

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2 Why do you need a data retention policy?

A data retention policy can help you manage your data warehouse growth in several ways. First, it can improve the performance of your data warehouse by reducing the amount of data that needs to be processed, queried, and backed up. This can also lower the risk of data corruption, duplication, and inconsistency. Second, it can reduce the storage costs of your data warehouse by freeing up space and minimizing the need for hardware upgrades. This can also make your data warehouse more scalable and flexible. Third, it can help you comply with the regulations and laws that govern the use and disposal of data, such as GDPR, HIPAA, and PCI DSS. This can protect you from legal liabilities, fines, and reputational damage.

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Arockia Nirmal Amala Doss

Founder, Data Engineer @ ZippyTec GmbH | Data Migration & Data Engineering Consulting | Data Migration Coaching | AWS Community Builder
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As data volumes explode, it's not about how much data you store, but how smartly you manage its lifecycle. When crafting a retention policy, start by classifying data based on its business value and regulatory requirements. Not all data is created equal. Some might be crucial for analytics but lose relevance over time, while others have stringent legal retention periods. Also, remember that retention isn't just about deletion. Consider archiving strategies, moving older data to cost-effective storage solutions. Regularly review and update your policy, ensuring it aligns with evolving business needs and regulatory landscapes. In the world of data, being proactive with retention is always better than being reactive.

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Paresh Nayak

Data Architect | Cloud DWH, Data Integration
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Even if an organization retains all the data that's legally required, the organization must be able to produce that data if it's requested by auditors/compliance. Retaining only the minimally required volume of data makes it easier and less time-consuming to locate this data, thereby reducing the chances that an organization is fined for its inability to produce data that's required to be retained. However GDPR,HIPAA - Compliance goes upper hand as per business requirement with BFSI - Insurance with 7 years of retention period.

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3 How do you create a data retention policy?

To create a data retention policy for your data warehouse, you need to follow a few steps. First, you need to identify the sources and types of data that you store in your data warehouse and classify them according to their value, sensitivity, and usage. Second, you need to determine the retention period for each type of data based on your business needs, data quality, and legal obligations. Third, you need to define the actions that you will take when the data reaches its end of life, such as deletion, archiving, or anonymization. Fourth, you need to document and communicate your data retention policy to your stakeholders and users and ensure that they understand and follow it.

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4 How do you implement a data retention policy?

To implement a data retention policy for your data warehouse, you need to use the appropriate tools and techniques that can automate and enforce the policy. For example, you can use partitioning to divide your data into smaller and manageable segments based on time or other criteria. This can make it easier to delete or archive the data when it expires. You can also use compression to reduce the size of your data and save storage space. You can also use encryption or masking to protect the privacy and security of your data. You can also use auditing and monitoring to track and verify the compliance of your data retention policy.

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Tomas Peluritis

Data Person | Data Engineering, Technical Leadership | Uncle Data
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If we're looking at actual retention, it's usually connected to removing the data after some time has passed. It's best if some archiving process runs automatically on the tagged datasets. Retention policy should, in my eyes, be in stages. 1. Archive (if it's s3, move to glacier, unload to files and compress, etc.). In case, for some actual reason, it's needed, you can recover 2. Delete from archive In this scenario, you'd be able to identify gaps in your processes and cover unforeseen scenarios.

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5 How do you review and update a data retention policy?

A data retention policy for your data warehouse is not a static document that you can set and forget. It is a dynamic and evolving document that you need to review and update regularly. You need to consider the changes in your business objectives, data sources, data usage, data quality, and legal regulations that may affect your data retention policy. You need to evaluate the effectiveness and efficiency of your data retention policy and identify any gaps or issues that need to be addressed. You need to solicit feedback and input from your stakeholders and users and incorporate their suggestions and needs. You need to communicate and implement the changes in your data retention policy and ensure that they are followed and enforced.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can data retention policies help you manage your data warehouse growth?

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1 What is a data retention policy?

2 Why do you need a data retention policy?

3 How do you create a data retention policy?

4 How do you implement a data retention policy?

5 How do you review and update a data retention policy?

6 Here’s what else to consider

Data Warehousing

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How can data retention policies help you manage your data warehouse growth?

1

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4

5

6

1 What is a data retention policy?

2 Why do you need a data retention policy?

3 How do you create a data retention policy?

4 How do you implement a data retention policy?

5 How do you review and update a data retention policy?

6 Here’s what else to consider

Data Warehousing

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