Remove 2022 Remove Analytics Remove Data Analytics Remove Data Architecture
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Eight Top DataOps Trends for 2022

DataKitchen

Keep an eye on the eight top trends below that we believe will be significant in the year 2022. The data industry realizes that AI bias is simply a quality problem, and AI systems should be subject to this same level of process control as an automobile rolling off an assembly line. Data Gets Meshier. AI Accountability.

Testing 245
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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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Data Journey First DataOps

DataKitchen

Data Journey First DataOps Putting Problems in Your Data Estate at the Forefront Welcome to the high-octane world of DataOps, a powerhouse that turbocharges data analytics development and management. The Why and How of ‘Data Journey First DataOps’ Let’s start with the ‘why.’

Testing 130
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The Future Is Hybrid Data, Embrace It

Cloudera

Also, Cloudera DataFlow is rated highly in the GigaOm Radar for Streaming Data Platforms. Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors. Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform.

IT 110
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The Future Is Hybrid Data, Embrace It

CIO Business Intelligence

Also, Cloudera DataFlow is rated highly in the GigaOm Radar for Streaming Data Platforms. Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors. Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform.

IT 83
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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. Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. But it isn’t just aggregating data for models.

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Augmented data management: Data fabric versus data mesh

IBM Big Data Hub

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.