Smart Data Collective
DECEMBER 28, 2022
Automated testing can help you identify and eliminate many potential data errors before they become an issue. These tests look for discrepancies between data sets and any unexpected changes in the flow of data. Automated testing can also help you identify and fix problems quickly before they become significant issues.
Domo
MARCH 17, 2017
Domo was also invited to be part of the future session panel, discussing ways executives can navigate the next decade as brand ambitions flourish alongside advances in big data, automation, real-time analytics, artificial intelligence and personalization.
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Insight Software
APRIL 19, 2021
According to The Data Warehousing Institute (TDWI), a think tank devoted to all things data (and a great resource for education and training), data automation liberates IT from spending significant time on mundane tasks, allowing them to focus on more strategic, game-changing breakthroughs for the enterprise.
Cprime
JULY 27, 2021
Automated data collection means shorter learning cycles than Value Stream Mapping. Enables value Stream Governance. Does not collect quantitative performance data. PT and LT data represents the aggregate of all work types. Data is usually gathered manually and is based on expert opinion.
Data Pine
DECEMBER 11, 2019
When SaaS is combined with AI capabilities , it enables businesses to obtain better value from their data, automate and personalize services, improve security, and supplement human capacity. How will AI improve SaaS in 2020?
Astera
APRIL 7, 2023
Enterprise Data Architecture (EDA) is an extensive framework that defines how enterprises should organize, integrate, and store their data assets to achieve their business goals. At an enterprise level, an effective enterprise data architecture helps in standardizing the data management processes.
Astera
APRIL 7, 2023
Enterprise Data Architecture (EDA) is an extensive framework that defines how enterprises should organize, integrate, and store their data assets to achieve their business goals. At an enterprise level, an effective enterprise data architecture helps in standardizing the data management processes.
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