Remove 2022 Remove Data Collection Remove Data Science Remove Metadata
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AI at Scale isn’t Magic, it’s Data – Hybrid Data

Cloudera

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. This leads to the obvious question – how do you do data at scale ? Al needs machine learning (ML), ML needs data science. Data science needs analytics.

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7 enterprise data strategy trends

CIO Business Intelligence

Data fabric is an architecture that enables the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems. The fabric, especially at the active metadata level, is important, Saibene notes.

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The Gartner 2022 Leadership Vision for Data and Analytics Leaders Questions and Answers

Andrew White

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. Which trends do you see for 2022 in AI & ML technology and tools and tool capabilities? – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend.

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Why We Started the Data Intelligence Project

Alation

In 2013 I joined American Family Insurance as a metadata analyst. I was changing careers and had just completed a degree in Library and Information Science. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In 2022, AWS commissioned a study conducted by the American Productivity and Quality Center (APQC) to quantify the Business Value of Customer 360.

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Summing Up Three Days at Gartner’s Data and Analytics Conference in Orlando, Florida, USA

Andrew White

See Product Management Practices Crucial for Data and Analytics Asset Monetization. Data mesh versus data fabric I am not the expert here but in lay terms, I believe both fabric and mesh include a semantic inference engine that consumes active metadata. Both build semantic maps that span silos of data.