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Data Profiling: What It Is and How to Perfect It

Alation

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

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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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Data architecture strategy for data quality

IBM Journey to AI blog

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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Data Mesh vs. Data Fabric: A Love Story

Alation

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

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How data engineers tame Big Data?

Dataconomy

Data engineers are responsible for designing and building the systems that make it possible to store, process, and analyze large amounts of data. These systems include data pipelines, data warehouses, and data lakes, among others. However, building and maintaining these systems is not an easy task.

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

LakeFS LakeFS is an open-source platform that provides data lake versioning and management capabilities. It sits between the data lake and cloud object storage, allowing you to version and control changes to data lakes at scale. Share features across the organization.