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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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Data-Driven in 2022: Data Management Opportunities in the Year Ahead

DataKitchen

The post Data-Driven in 2022: Data Management Opportunities in the Year Ahead first appeared on DataKitchen.

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4 Data-Driven Ways to Improve Employee Engagement

datapine

Also, a great way to collect employee engagement data is using Gallup’s Q12 survey , which consists of 12 carefully crafted questions that gauge the most crucial aspects of employee engagement. Work with managers to incorporate career conversations in regular meetings with their teams. Highly engaged employees are 2.3x

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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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Pressure Points: How to Ensure Your B2B Pipeline Passes Inspection

This eBook highlights best practices for developing a pipeline management process that helps sales leaders and their team C.L.O.S.E you’ll see what we mean in this eBook) more revenue through data-driven prospecting, stage analysis, and subsequent sales enablement.

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Data-Driven Workers’ Compensation Claims Management

Smart Data Collective

More insurers are using data analytics to streamline the process for worker's compensation claimants.

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Business Management Systems for Data-Driven Businesses

Smart Data Collective

Big data has become an invaluable aspect to most modern businesses. Nevertheless, many companies have been reluctant to Harvard Business Review reports that only 30% of businesses have a data strategy. However, companies with data strategies are far more successful than those without.

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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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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? Attendance of this webinar will earn one PDH toward your NPDP certification for the Product Development and Management Association.

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How To Design Your Next Roadmap with Data-Driven Pit Stops Masterclass

Speaker: Sonia Singhal, Product Manager at eBay

These days, a simple A/B test can seem to incorporate the whole alphabet, and making a decision from that data isn't as easy as A, B, C either. How can we shorten the time it takes to do the tests while gaining larger amounts of data? Are we even gaining any new insight into the data we are receiving?

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Why B2B Contact and Account Data Management Is Critical to Your ROI

64% of successful data-driven marketers say improving data quality is the most challenging obstacle to achieving success. The digital age has brought about increased investment in data quality solutions. Download this eBook and gain an understanding of the impact of data management on your company’s ROI.

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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.

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The Next-Generation Cloud Data Lake: An Open, No-Copy Data Architecture

In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs.

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MLOps 101: The Foundation for Your AI Strategy

Machine Learning Operations (MLOps) allows organizations to alleviate many of the issues on the path to AI with ROI by providing a technological backbone for managing the machine learning lifecycle through automation and scalability. Why do AI-driven organizations need it? Download this comprehensive guide to learn: What is MLOps?