Data Lake Digital Transformation Metadata Modeling 
erwin
JULY 17, 2019
Having a clearly defined digital transformation strategy is an essential best practice for successful digital transformation. But what makes a viable digital transformation strategy? Constructing A Digital Transformation Strategy: Data Enablement.
CIO Business Intelligence
AUGUST 3, 2023
But reaching all these goals, as well as using enterprise data for generative AI to streamline the business and develop new services, requires a proper foundation. That hard, ongoing work includes integrating siloed data, modeling, and understanding it, as well as maintaining and securing it over time.
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CIO Business Intelligence
OCTOBER 13, 2023
Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations.
erwin
OCTOBER 8, 2020
But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. With all these diverse metadata sources, it is difficult to understand the complicated web they form much less get a simple visual flow of data lineage and impact analysis.
Timo Elliott
JUNE 19, 2023
With SAP Signavio, you can use Business Process Insights to see whether opportunities for these new composable applications, and then accompany any kind of digital transformation project. It takes high quality data. And most of the highest quality data in most organizations is in their SAP systems. The next area is data.
IBM Big Data Hub
AUGUST 4, 2023
Data democratization, much like the term digital transformation five years ago, has become a popular buzzword throughout organizations, from IT departments to the C-suite. It’s often described as a way to simply increase data access, but the transition is about far more than that.
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. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’
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