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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.
Organizations with a solid understanding of data governance (DG) are better equipped to keep pace with the speed of modern business. In this post, the erwin Experts address: What Is Data Governance? Why Is Data Governance Important? What Is Good Data Governance? What Are the Key Benefits of Data Governance?
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Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.
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Data intelligence has a critical role to play in the supercomputing battle against Covid-19. While leveraging supercomputing power is a tremendous asset in our fight to combat this global pandemic, in order to deliver life-saving insights, you really have to understand what data you have and where it came from.
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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.
It also highlights select enterprise architecture management suite (EAMS) vendors based on size and functionality, including erwin. For “ EA stakeholders to be more productive and effective ,” not only is a central repository a necessity but collaboration and a persona-driven approach also are critical to the organization’s adoption of EA.
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Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. A single source of data truth helps companies begin to leverage data as a strategic asset.
Our team here at erwin takes great pride in this distinction because customer feedback has always shaped our products and services. The solutions work in tandem to automate the processes involved in harvesting, integrating, activating and governing enterprise data according to business requirements.
Added data quality capability ready for an AI era Data quality has never been more important than as we head into this next AI-focused era. erwinData Quality is the data quality heart of erwinData Intelligence. erwinData Quality is the data quality heart of erwinData Intelligence.
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.
Our customers are in search of creative and sustainable ways to increase their speed to insights for digital transformation, infrastructure modernization and cloud migration and many of them are looking to implement the Snowflake Cloud Data Platform. Let me know your thoughts on the new erwin/Snowflake partnership. Well, we think so.
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If you love our products, please vote. Year after year, customers vote Quest® products as their #1 choice in database solutions. This year Quest® (including erwin) is competing in 7 out of 29 product / solution categories: Best CDC Solution (Quest Shareplex). Best Data Governance Solution (erwinData Intelligence).
With business process modeling (BPM) being a key component of data governance , choosing a BPM tool is part of a dilemma many businesses either have or will soon face. Historically, BPM didn’t necessarily have to be tied to an organization’s data governance initiative. Choosing a BPM Tool: An Overview.
Tackling data-related challenges to keep cloud migration projects on track and optimized. The cloud has many operational and competitive advantages, so cloud-first and other cloud transformation initiatives continue to be among the top data projects organizations are pursuing. compliance with the General Data Protection Regulation).
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