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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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Best Azure ETL Tools For 2024

Astera

Azure SQL Data Warehouse, now called Azure Synapse Analytics, is a powerful analytics and BI platform that enables organizations to process and analyze large volumes of data in a centralized place. However, this data is often scattered across different systems, making it difficult to consolidate and utilize 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 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. So, in this article, we will explore some of the best alternatives to Fivetran. Award-winning customer support.

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Data Speaks for Itself: The Challenge of Data Consistency

The Data Administration Newsletter

Data quality management (DQM) has advanced considerably over the years. The full extent of the problem was first recognized during the data warehouse movement in the 1980s.

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An Introduction to Metadata Management

Dataversity

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

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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.