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When A Data Catalog Is Not Just a Data Catalog

Data Virtualization

These are the elements that, followed in sequence, enables the use of data and information to generate value, value that can be realized in accordance with the. The post When A Data Catalog Is Not Just a Data Catalog appeared first on Data Virtualization blog.

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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

Do not close the door on me when I am so close to giving you an explanation. Do not close the door on me when I am so close to giving you an explanation. What you have just experienced is a plethora of heteronyms. Heteronyms are words that are spelled identically but have different meanings when pronounced differently.

Strategy 266
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3 commandments that should drive every API strategy

CIO Business Intelligence

According to secondary sources, this mandate included two strategic requirements that any IT leader should consider when seeking to maximize the value of their development teams’ efforts. After all, just as with APIs, when one group of people provides a service to other groups, promises must be clear, and boundaries respected.

Strategy 138
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Best Practices for Data Catalog Implementation

Octopai

In an era where data is often referred to as the new oil, having a well-organized and easily accessible data catalog is no longer a luxury but a necessity as organizations deal with the deluge of too much data (data bloatedness) coming from every system and landscape.

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When is a catalog not a catalog?

Andrew White

I blogged recently about the high level of hype and confusion across Data and Analytics just a few months ago. Here is the original blog from March 2023: Summing Up Three Days at Gartner’s Data and Analytics Conference in Orlando, Florida, USA. Those are subsets of a much larger catalog. That is the wrong question.

Metrics 52
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Use AWS Glue ETL to perform merge, partition evolution, and schema evolution on Apache Iceberg

AWS Big Data

As enterprises collect increasing amounts of data from various sources, the structure and organization of that data often need to change over time to meet evolving analytical needs. Schema evolution enables adding, deleting, renaming, or modifying columns without needing to rewrite existing data. Query the data using Athena.

Snapshot 110
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Business Strategies for Deploying Disruptive Tech: Generative AI and ChatGPT

Rocket-Powered Data Science

First, don’t do something just because everyone else is doing it – there needs to be a valid business reason for your organization to be doing it, at the very least because you will need to explain it objectively to your stakeholders (employees, investors, clients). So what? (2)

Strategy 289