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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. Choose Next to create your stack.

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The Key Components of a Successful Data Lake Strategy

Data Virtualization

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

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The Key Components of a Successful Data Lake Strategy

Data Virtualization

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

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Is Data Virtualization the Secret Behind Operationalizing Data Lakes?

Data Virtualization

In attempts to overcome their big data challenges, organizations are exploring data lakes as repositories where huge volumes and varieties of. The post Is Data Virtualization the Secret Behind Operationalizing Data Lakes?

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The Data Lakehouse: Blending Data Warehouses and Data Lakes

Data Virtualization

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

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An AI Chat Bot Wrote This Blog Post …

DataKitchen

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making.

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Modern Data Architecture: Data Warehousing, Data Lakes, and Data Mesh Explained

Data Virtualization

For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.