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erwin Expert Blog

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. There’s always more data to handle, much of it unstructured; more data sources, like IoT, more points of integration, and more regulatory compliance requirements. Creating and sustaining an enterprise-wide view of...

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As organizations deal with managing ever more data, the need to automate data management becomes clear. Last week erwin issued its 2020 State of Data Governance and Automation (DGA) Report. The research from the survey suggests that companies are still grappling with the challenges of data governance — challenges that will only get worse as...

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A new study into data governance automation indicates organizations are prioritising value-adding use cases, over efforts concerning regulatory compliance.

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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 Physical Data Models: The internal schema database design An organization’s approach to data modeling will be influenced...

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What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. As the value of data and the way it is used by organizations has...

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Enterprises are trying to manage data chaos. They might have 300 applications, with 50 different databases and a different schema for each one. 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...

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Understanding the data governance trends for the year ahead will give business leaders and data professionals a competitive edge. Happy New Year! Regulatory compliance and data breaches have driven the data governance narrative during the past few years. While these will remain big data governance trends for 2020, we anticipate organizations will finally begin tapping...

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Data has been the driving force of the decade. Digital pioneers like Amazon, Netflix and Uber account for some of the most extreme market disruption their respective industries have faced. But such success cannot be attributed soley to head-starts. Many organizations have tried and failed to become truly “data-driven,” and many organizations will continue to...

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Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance. So most early-stage data...

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In the data-driven era, CIO’s need a solid understanding of data governance 2.0 … Data governance (DG) is no longer about just compliance or relegated to the confines of IT. Today, data governance needs to be a ubiquitous part of your organization’s culture. As the CIO, your stakeholders include both IT and business users in...

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