Remove Data Processing Remove Optimization Remove Publishing Remove Unstructured Data
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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Also included, business and technical metadata, related to both data inputs / data outputs, that enable data discovery and achieving cross-organizational consensus on the definitions of data assets. Key Design Principles of a Data Mesh. When it comes to data movement outside the boundaries of Data Products (i.e.,

Metadata 124
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Top Takeaways from the Gartner® Innovation Insight: Data Security Posture Management

Laminar Security

That’s particularly concerning considering that 60% of worldwide corporate data was stored in the cloud during that same period. So while the cloud has become an integral part of doing business, data security in the cloud is lagging behind. Data can be copied, modified, moved, and backed up with just a few clicks.

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Ontotext Invents the Universe So You Don’t Need To

Ontotext

Businesses wanted a way to make pie and not an in-depth understanding of forward-chaining, inferential explosion or SPARQL optimizations. The resulting detailed and structured description of content serves as a basis for semantic indexing, search and exploration as well as the ability to create dynamic and automated content publishing.

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How to Take Back 40-60% of Your IT Spend by Fixing Your Data

Ontotext

This is partly because integrating and moving data is not the only problem. The data itself is stored in a way that is not optimal for extracting insight. Unlocking additional value from data requires context, relationships, and structure, none of which are present in the way most organizations store their data today.

IT 69
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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.

Data Lake 102
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The new challenges of scale: What it takes to go from PB to EB data scale

CIO Business Intelligence

To accomplish this, we will need additional data center space, more storage disks and nodes, the ability for the software to scale to 1000+PB of data, and increased support through additional compute nodes and networking bandwidth. Focus on scalability.