Data Enablement Management Predictive Analytics Risk 
FineReport
APRIL 9, 2024
Challenges in Data Management Data Security and Compliance The protection of sensitive patient information and adherence to regulatory standards pose significant challenges in healthcare data management.
datapine
MAY 2, 2023
Benefits Of Big Data In Logistics Before we look at our selection of practical examples and applications, let’s look at the benefits of big data in logistics – starting with the (not so) small matter of costs. This transparency is valuable to shippers, carriers, and customers.
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Cloudera
AUGUST 3, 2021
Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. .
Sisense
OCTOBER 6, 2020
As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data.
Cloudera
SEPTEMBER 12, 2018
It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Mike Barlow , Managing Partner, Cumulus Partners.
IBM Big Data Hub
JUNE 14, 2023
Key SM tools include the following: Industrial Internet of Things (IIoT) The IIoT is a network of interconnected machinery, tools and sensors that communicate with each other and the cloud to collect and share data. Cloud and edge computing Cloud computing and edge computing play a significant role in how smart manufacturing plants operate.
CIO Business Intelligence
APRIL 15, 2022
The patients who were lying down were much more likely to be seriously ill, so the algorithm learned to identify COVID risk based on the position of the person in the scan. A similar example includes an algorithm trained with a data set that included scans of the chests of healthy children.
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