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Product lifecycle management for data-driven organizations 

IBM Big Data Hub

In a world where every company is now a technology company, all enterprises must become well-versed in managing their digital products to remain competitive. In other words, they need a robust digital product lifecycle management (PLM) strategy. Data is an asset, but to provide value, it must be organized, standardized and governed.

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The change management Informatica needed to overhaul its business model

CIO Business Intelligence

Many of our customers had already started to move their applications and it made sense they would want to transition to data management in the cloud as well. The investment thesis was we could dramatically change the value of the company by becoming a true cloud and subscription-driven company. Today, we’re a $1.6

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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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Value Stream Management for digital transformation: A new maturity model

CIO Business Intelligence

New research 1 underscores the common challenges many enterprises face in advancing their Value Stream Management (VSM) maturity levels for digital transformation, emphasizing the crucial need for effective guidance. Recognizing this need, we have created a cutting-edge VSM maturity model.

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Best Practices for a Marketing Database Cleanse

Multiple industry studies confirm that regardless of industry, revenue, or company size, poor data quality is an epidemic for marketing teams. As frustrating as contact and account data management is, this is still your database – a massive asset to your organization, even if it is rife with holes and inaccurate information.

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What Is Data Modeling? Data Modeling Best Practices for Data-Driven Organizations

erwin

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.

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4 IT Management Best Practices Data-Driven Businesses Must Practice

Smart Data Collective

Data-driven businesses are far more successful than companies that don’t utilize data to their advantage. Unfortunately, they often find that managing their data effectively can be a challenge. Companies that rely on big data need a reliable IT department. Keep reading to learn how to do this.

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The Practical Guide to Using a Semantic Layer for Data & Analytics

Download this guide for practical advice on how to use a semantic layer to unlock data for AI & BI at scale. You’ll learn how a semantic layer delivers massive ROI with streamlined query performance, concurrency, cost management, and ease of use. How to enable data teams to model and deliver a semantic layer on data in the cloud.