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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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Game Changer: Modernize IT Procurement with Data-driven Insights

CIO Business Intelligence

And how do we demonstrate ROI in order to proceed? It’s time to discard legacy processes and reinvent IT procurement with a new approach that leverages the power of data-driven insights. It would also provide a simulator for on-premises IT that includes the ability to input your actual costs of storage, hosts, and memory.

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Data-Driven Marketing Strategies Will Be the Norm in The Post-Covid Era

Smart Data Collective

Big data has been instrumental in keeping the pandemic in check. Organizations and governments around the world are using big data technology to track the spread of Covid-19 and find better solutions to keep it in check. However, big data will continue to affect our lives long after the pandemic has subsided.

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Common Business Intelligence Challenges Facing Entrepreneurs

datapine

“BI is about providing the right data at the right time to the right people so that they can take the right decisions” – Nic Smith. Data analytics isn’t just for the Big Guys anymore; it’s accessible to ventures, organizations, and businesses of all shapes, sizes, and sectors.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Five years ago they may have. But today, dashboards and visualizations have become table stakes. Brought to you by Logi Analytics.

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Bringing More AI to Snowflake, the Data Cloud

DataRobot Blog

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. Exploratory Data Analysis After we connect to Snowflake, we can start our ML experiment.

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What CIOs and CTOs should consider before adopting generative AI for application modernization

IBM Big Data Hub

Here’s how CTOs and CIOs can evaluate their technology and data estates, assess the opportunity and chart a path forward. also includes access to the StarCoder LLM, trained on openly licensed data from GitHub. Organizations that have mastered hybrid cloud are well positioned to implement generative AI across the organization.