Remove Data Governance Remove Metadata Remove Publishing Remove Unstructured Data
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Do I Need a Data Catalog?

erwin

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.). This also diminishes the value of data as an asset. Technical Metadata.

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The state of data quality in 2020

O'Reilly on Data

Data scientists and analysts, data engineers, and the people who manage them comprise 40% of the audience; developers and their managers, about 22%. Data quality might get worse before it gets better. Comparatively few organizations have created dedicated data quality teams. Adopting AI can help data quality.

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5 Types of Costly Data Waste and How to Avoid Them

CIO Business Intelligence

. • You have data but don’t use it. Why does valuable data so often go unused? Lack of annotation with the right metadata is a contributing factor. An even larger issue is that people may not know how to see value in data. Recognizing what data can tell you is an acquired skill for people beyond just data scientists.

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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

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Why Spreadsheets Are Your Secret Weapon for Efficient Data Governance

Alation

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. Simply put, metadata adds context.

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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs. Key Design Principles of a Data Mesh.

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Why The Public Sector Needs Data Governance

Alation

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.