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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Commerce strategy: Ecommerce is dead, long live ecommerce

IBM Big Data Hub

In today’s dynamic and uncertain landscape, commerce strategy—what we might formerly have referred to as ecommerce strategy—is so much more than it once was. Commerce is a complex journey in which the moment of truth—conversion—takes place.

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Data Modeling 101: OLTP data modeling, design, and normalization for the cloud

erwin

How to create a solid foundation for data modeling of OLTP systems. As you undertake a cloud database migration , a best practice is to perform data modeling as the foundation for well-designed OLTP databases. This makes mastering basic data modeling techniques and avoiding common pitfalls imperative. Look at Figure 1 below.

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How foundation models can help make steel and cement production more sustainable

IBM Big Data Hub

These digital twins capture multivariate relationships between process variables, material characteristics, energy requirements, weather conditions, operator actions, and product quality. .” They use high temperature heat in many of their processes that is primarily driven by fossil fuel.

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#ClouderaLife Employee Spotlight: Jess Hohn-Cabana

Cloudera

Jess also has extensive experience in brand strategy, analyst relations, and influencer relations, successfully building awareness for global bands and creating meaningful relationships with key audiences. What is one goal you hope to accomplish in your new role? We must also position Cloudera as a thought leader in our space.

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Can AI Help Make Social Media Healthier?

Smart Data Collective

Meta is using Facebook data to train its algorithms for a variety of purposes , including identifying harmful content to make the platform more holistic. Meta is using Facebook data to train its algorithms for a variety of purposes , including identifying harmful content to make the platform more holistic.

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8 Reasons Data-Driven Companies Are Utilizing Email Marketing

Smart Data Collective

Big data is at the heart of all successful, modern marketing strategies. Companies that engage in email marketing have discovered that big data is particularly effective. When you are running a data-driven company, you should seriously consider investing in email marketing campaigns. That’s not true.