Metadata Optimization Structured Data Unstructured Data 
CIO Business Intelligence
DECEMBER 13, 2023
When I think about unstructured data, I see my colleague Rob Gerbrandt (an information governance genius) walking into a customer’s conference room where tubes of core samples line three walls. While most of us would see dirt and rock, Rob sees unstructured data. have encouraged the creation of unstructured data.
CIO Business Intelligence
MARCH 21, 2022
What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Semi-structured data falls between the two.
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CIO Business Intelligence
DECEMBER 4, 2023
Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Beyond “records,” organizations can digitally capture anything and apply metadata for context and searchability.
erwin
JUNE 26, 2020
Organizations with particularly deep data stores might need a data catalog with advanced capabilities, such as automated metadata harvesting to speed up the data preparation process. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata.
Octopai
FEBRUARY 8, 2020
Although it was only one of many Mars mission failures in the history of space travel, it was one that easily could have been prevented by achieving the optimal set of equipment and communication to power space travel. . Moreover, others need to trace data history, get its context to resolve an issue before it actually becomes an issue.
Ontotext
JANUARY 6, 2021
That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. You can apply graph optimizations or operations such as traversals and transformations.
Cloudera
SEPTEMBER 17, 2020
They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Text data served up via Solr’s powerful analytics engine and APIs.
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