Remove Big Data Remove Data Architecture Remove Data Lake
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Data Integrity for AI: What’s Old is New Again

Precisely

The goal of this post is to understand how data integrity best practices have been embraced time and time again, no matter the technology underpinning. In the beginning, there was a data warehouse The data warehouse (DW) was an approach to data architecture and structured data management that really hit its stride in the early 1990s.

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Maintaining Your Data Lake At Scale With Spark

Data Engineering Podcast

Summary Building and maintaining a data lake is a choose your own adventure of tools, services, and evolving best practices. The flexibility and freedom that data lakes provide allows for generating significant value, but it can also lead to anti-patterns and inconsistent quality in your analytics.

Data Lake 100
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Straining Your Data Lake Through A Data Mesh

Data Engineering Podcast

Summary The current trend in data management is to centralize the responsibilities of storing and curating the organization’s information to a data engineering team. This organizational pattern is reinforced by the architectural pattern of data lakes as a solution for managing storage and access.

Data Lake 100
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A High Performance Platform For The Full Big Data Lifecycle

Data Engineering Podcast

Summary Managing big data projects at scale is a perennial problem, with a wide variety of solutions that have evolved over the past 20 years. Designed as a fully integrated platform to meet the needs of enterprise grade analytics it provides a solution for the full lifecycle of data at massive scale.

Big Data 100
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Modern Data Architecture for Telecommunications

Cloudera

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Previously, there were three types of data structures in telco: .

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Simplify Your Data Architecture With The Presto Distributed SQL Engine

Data Engineering Podcast

In this episode he explains how it is designed to allow for querying and combining data where it resides, the use cases that such an architecture unlocks, and the innovative ways that it is being employed at companies across the world. And don’t forget to thank them for their continued support of this show!

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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake.