Remove Data Governance Remove Data Lake Remove Data Workflow Remove Metadata
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Toward a Data Mesh (part 2) : Architecture & Technologies

François Nguyen

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. How do we build data products ? How can we interoperate between the data domains ? Data As Code is a very strong choice : we do not want any UI because it is an heritage of the ETL period.

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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

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The Advantages Of Live Data-Streaming In The Competitive Financial Services Sector (Part I)

Cloudera

Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data. The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from.

Banking 60
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The Evolution of Table Formats

Monte Carlo

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

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Addressing The Challenges Of Component Integration In Data Platform Architectures

Data Engineering Podcast

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

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Data Pipeline Architecture Explained: 6 Diagrams and Best Practices

Monte Carlo

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. It is like a smart scheduler for your data workflows.

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The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

Built around a cloud data warehouse, data lake, or data lakehouse. Modern data stack tools are designed to integrate seamlessly with cloud data warehouses such as Redshift, Bigquery, and Snowflake, as well as data lakes or even the child of the first two — a data lakehouse.

IT 59