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Top 20 Data Warehouse Best Practices in 2024

Astera

Given the generally complex nature of the data warehouse architecture, there are certain data warehouse best practices that focus on performance optimization, data governance and security, scalability and future-proofing, and continuous monitoring and improvement.

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Data Governance Framework: What is it? Importance, Pillars and Best Practices

Astera

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

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Information Governance vs. Data Governance: A Comparative Analysis

Astera

Data governance’s primary purpose is to ensure organizational data assets’ quality, integrity, security, and effective use. The key objectives of Data Governance include: Enhancing Clear Ownership: Assigning roles to ensure accountability and effective management of data assets.

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Top 20 Data Warehousing Best Practices in 2024

Astera

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

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Top 19 Data Warehousing Best Practices in 2024

Astera

It also supports predictive and prescriptive analytics, forecasting future outcomes and recommending optimal actions based on data insights. Enhancing Data Quality A data warehouse ensures high data quality by employing techniques such as data cleansing, validation, integration, and standardization during the ETL process.

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What is a Data Catalog? Features, Best Practices, and Benefits

Astera

Establishing a data catalog is part of a broader data governance strategy, which includes: creating a business glossary, increasing data literacy across the company and data classification. Data Catalog vs. Data Dictionary A common confusion arises when data dictionaries come into the discussion.

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What is Metadata Management? Benefits, Framework, Tools, Use Cases, Best Practices

Astera

Let’s look at some of the metadata types below: Operational metadata: details how and when data occurs and transforms. This metadata type helps to manage, monitor, and optimize system architecture performance. Examples include time stamps, execution logs, data lineage, and dependency mapping. Image by Astera.