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9 Habits Of Effective Data Managers – Running A Data Team

Seattle Data Guy

Data teams are expected to juggle a combination of ad-hoc requests, big bet projects, migrations, etc. All while keeping up with the latest changes in technology.

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Understanding Master Data Management (MDM) and Its Role in Data Integrity

Precisely

Challenges around data literacy, readiness, and risk exposure need to be addressed – otherwise they can hinder MDM’s success Businesses that excel with MDM and data integrity can trust their data to inform high-velocity decisions, and remain compliant with emerging regulations. Today, you have more data than ever.

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Transforming Omics Data Management with Databricks Data Intelligence Platform

databricks

This blog explores how new technologies such as Databricks Data Intelligence Platform can pave the way for more effective and efficient multi-omics data management.

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Master Data Management: Common Misconceptions You Should Know

Precisely

When most people think of master data management, they first think of customers and products. But master data encompasses so much more than data about customers and products. Challenges of Master Data Management A decade ago, master data management (MDM) was a much simpler proposition than it is today.

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The AI Superhero Approach to Product Management

Speaker: Conrado Morlan

In this engaging and witty talk, industry expert Conrado Morlan will explore how artificial intelligence can transform the daily tasks of product managers into streamlined, efficient processes. The Future of Product Management 🔮 How to continuously integrate AI into your work to stay ahead of emerging trends and technologies.

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Find Out About The Technology Behind The Latest PFAD In Analytical Database Development

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Dagster offers a new approach to building and running data platforms and data pipelines. Can you describe the operational/architectural aspects of building a full data engine on top of the FDAP stack?

Database 162
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Cloudera wins Risk Markets Technology Award for Data Management Product of the year

Cloudera

Financial services institutions need the ability to analyze and act on massive volumes of data from diverse sources in order to monitor, model, and manage risk across the enterprise. They need a comprehensive data and analytics platform to model risk exposures on-demand. End-to-end Data Lifecycle.