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Empowering data mesh: The tools to deliver BI excellence

erwin

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

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Announcing erwin Data Modeler 12.5 with the new ER360 collaboration portal

erwin

Intro erwin ® Data Modeler 12.5 It requires many functional elements of an organization to come together in order to reach the ultimate stages of being able to identify, understand and fully leverage the power of its data. erwin Data Modeler 12.5 erwin Data Modeler 12.5

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Erwin Data Intelligence: A Data Partner’s Perspective

erwin

At Sparkle, we’re a holistic data partner helping organizations increase their data maturity in a strategic yet pragmatic way. One of the key ingredients to ensure data is really embedded in an organization, and one of the key enablers to increase the strategic impact of data, is the setup of a successful data governance program.

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5 Ways Data Modeling Is Critical to Data Governance

erwin

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. GDPR: Key Differences.

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Doing Cloud Migration and Data Governance Right the First Time

erwin

So if you’re going to move from your data from on-premise legacy data stores and warehouse systems to the cloud, you should do it right the first time. And as you make this transition, you need to understand what data you have, know where it is located, and govern it along the way. Then you must bulk load the legacy data.

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Types of Data Models: Conceptual, Logical & Physical

erwin

There are three different types of data models: conceptual, logical and physical, and each has a specific purpose. Conceptual Data Models: High-level, static business structures and concepts. Logical Data Models: Entity types, data attributes and relationships between entities.

Sales 143
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From Chaos to Control with Data Intelligence

erwin

As the amount of data grows exponentially, organizations turn to data intelligence to reach deeper conclusions about driving revenue, achieving regulatory compliance and accomplishing other strategic objectives. It’s no secret that data has grown in volume, variety and velocity, with 2.5 New products and services.

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