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.
Cloudera
NOVEMBER 15, 2021
Here we mostly focus on structured vs unstructured data. In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else.
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CIO Business Intelligence
FEBRUARY 20, 2024
Manufacturers have long held a data-driven vision for the future of their industry. It’s one where near real-time data flows seamlessly between IT and operational technology (OT) systems. Legacy data management is holding back manufacturing transformation Until now, however, this vision has remained out of reach.
Ontotext
JULY 20, 2023
Our state-of-the-art Conversational AI platform serves customers across various domains such as tourism, finance, retail, energy, manufacturing, etc. We take data from any number of data sources, model it in a knowledge graph, train our chatbots on it and use it to dynamically build dialogs in natural language.
CIO Business Intelligence
FEBRUARY 16, 2023
My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America.
IBM Big Data Hub
SEPTEMBER 19, 2023
Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.
Ontotext
MAY 25, 2023
The event attracts individuals interested in graph technology, machine learning and natural language processes in numerous verticals, including publishing, government, financial services, manufacturing and retail. We saw presentations showing the potential for knowledge graphs and LLM to complement each other.
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