Data Quality Metadata Predictive Analytics 
AWS Big Data
JANUARY 15, 2025
An extract, transform, and load (ETL) process using AWS Glue is triggered once a day to extract the required data and transform it into the required format and quality, following the data product principle of data mesh architectures. From here, the metadata is published to Amazon DataZone by using AWS Glue Data Catalog.
O'Reilly on Data
MARCH 18, 2020
By contrast, AI adopters are about one-third more likely to cite problems with missing or inconsistent data. The logic in this case partakes of garbage-in, garbage out : data scientists and ML engineers need quality data to train their models. This is consistent with the results of our data quality survey.
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Smart Data Collective
OCTOBER 13, 2021
Data Virtualization can include web process automation tools and semantic tools that help easily and reliably extract information from the web, and combine it with corporate information, to produce immediate results. How does Data Virtualization manage data quality requirements? Prescriptive analytics.
datapine
JANUARY 31, 2022
As Dan Jeavons Data Science Manager at Shell stated: “what we try to do is to think about minimal viable products that are going to have a significant business impact immediately and use that to inform the KPIs that really matter to the business”. 5) Find improvement opportunities through predictions. 6) Smart and faster reporting.
Cloudera
JUNE 29, 2023
Look for ways to integrate predictive analytics and ML into liquidity risk management — for example, by monitoring intraday liquidity, optimizing the timing of payments, reducing payment delays and/or dependence on intraday credit. Apply emerging technology to intraday liquidity management. Enhance counterparty risk assessment.
AWS Big Data
MARCH 26, 2024
A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.
IBM Big Data Hub
MAY 9, 2024
Conversely, confidence in the accuracy and consistency of your data can minimize the risk of adverse health outcomes, rather than merely reacting to or causing them. Also, using predictive analytics can help identify trends, patterns and potential future health risks in your patients. Instead, it uses active metadata.
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