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Evaluating Data Lakes vs. Data Warehouses

Dataversity

While data lakes and data warehouses are both important Data Management tools, they serve very different purposes. If you’re trying to determine whether you need a data lake, a data warehouse, or possibly even both, you’ll want to understand the functionality of each tool and their differences.

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Top 20 Data Warehouse Best Practices in 2024

Astera

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

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Building a Grassroots Data Management and Data Governance Program

Dataversity

Many in enterprise Data Management know the challenges that rapid business growth can present. Whether through acquisition or organic growth, the amount of enterprise data coming into the organization can feel exponential as the business hires more people, opens new locations, and serves new customers. The enterprise […].

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The Art of Lean Governance: Root Out Waste in Data Reconciliation

The Data Administration Newsletter

In this blog, we will discuss a common problem for data warehouses that are designed to maintain data quality and provide evidence of accuracy. Without verification, the data can’t be trusted. Enter the mundane, but necessary, task of data reconciliation. This is often a time-consuming and wasteful process.

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The Best Fivetran Alternatives in 2024

Astera

Fivetran is a low-code/no-code ELT (Extract, load and transform) solution that allows users to extract data from multiple sources and load it into the destination of their choice, such as a data warehouse. It also offers limited data transformation capabilities and that too through dbt core, which is an open source tool.

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Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

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The Complete Guide to Reverse ETL

Astera

Reverse ETL (Extract, Transform, Load) is the process of moving data from central data warehouse to operational and analytic tools. How Does Reverse ETL Fit in Your Data Infrastructure Reverse ETL helps bridge the gap between central data warehouse and operational applications and systems.