Data Governance Data Processing Definition Metadata 
Cloudera
MARCH 9, 2021
In this blog, we’ll highlight the key CDP aspects that provide data governance and lineage and show how they can be extended to incorporate metadata for non-CDP systems from across the enterprise. The SDX layer of CDP leverages the full spectrum of Atlas to automatically track and control all data assets.
datapine
SEPTEMBER 29, 2022
Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? 2 – Data profiling. This is definitely not in line with reality.
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AWS Big Data
AUGUST 16, 2023
Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. Iceberg captures metadata information on the state of datasets as they evolve and change over time. Choose Create.
Octopai
JANUARY 31, 2021
Within each episode, there are actionable insights that data teams can apply in their everyday tasks or projects. The host is Tobias Macey, an engineer with many years of experience. Agile Data. Agile Data. Another podcast we think is worth a listen is Agile Data. TDWI – Philip Russom. Malcolm Chisholm.
Domino Data Lab
APRIL 3, 2019
Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.
Alation
MAY 31, 2023
The Data Governance & Information Quality Conference (DGIQ) is happening soon — and we’ll be onsite in San Diego from June 5-9. If you’re not familiar with DGIQ, it’s the world’s most comprehensive event dedicated to, you guessed it, data governance and information quality. The best part?
IBM Big Data Hub
APRIL 11, 2024
In the context of AI, it can refer to the safety and ethics guardrails of AI tools and systems, policies concerning data access and model usage or the government-mandated regulation itself. Therefore, we see national and international guidelines address these overlapping and intersecting definitions in a variety of ways.
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