Data Virtualization
OCTOBER 5, 2022
For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.
Data Virtualization
MARCH 28, 2024
Reading Time: 2 minutes The financial industry is in the midst of a profound digital transformation. As noted in the Gartner Hype Cycle for Finance Data and Analytics Governance, 2023, “Through. Unfortunately, most financial organizations have some catching up to do in this regard.
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CIO Business Intelligence
OCTOBER 1, 2022
The partners say they will create the future of digital manufacturing by leveraging the industrial internet of things (IIoT), digital twin , data, and AI to bring products to consumers faster and increase customer satisfaction, all while improving productivity and reducing costs.
CIO Business Intelligence
FEBRUARY 16, 2023
Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.
CIO Business Intelligence
APRIL 29, 2022
This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed.
erwin
OCTOBER 8, 2020
The desire to modernize technology, over time, leads to acquiring many different systems with various data entry points and transformation rules for data as it moves into and across the organization. More and more companies are looking at cloud migration. Request an erwin Cloud Catalyst assessment.
BI-Survey
NOVEMBER 23, 2021
Thus, alternative data architecture concepts have emerged, such as the data lake and the data lakehouse. Which data architecture is right for the data-driven enterprise remains a subject of ongoing debate. Data black holes: the high cost of supposed flexibility. Data Black Holes.
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