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Building data products with data mesh and data fabric

Flawed decisions due to poor data quality, inaccuracies, and inconsistencies can result in high costs for an organization due to lost opportunities and reputational damages. Data consumers need to be able to trust their data to be confident in the downstream decisions that are being made with their analyses.

So, how can you ensure that you are delivering reliable data to your customers?

In this webcast, you’ll learn about a data product platform equipped with the tools you need to rapidly connect data consumers with high-quality, reliable data sets. Tune in to learn how you can leverage data mesh and data fabric technology to build valuable data products that deliver real-time insights.

These are also closely related to: "How to extract value from your data"

  • How to Build a Culture of Analytics With Alteryx

    Companies that embrace an end-to-end culture of analytics are agile, flexible, and able to seize business-defining opportunities before they’re spotted by the competition.

    However, many organizations aren’t there yet. They continue to struggle with problems like:

    • Information trapped in data silos
    • Analysis dragged down by manual processes
    • And more

    It’s time for change. How can you build the momentum you need to get members of your organization on board with analytic process automation (APA)?

    Read this e-book to learn how you can build the case for adopting a single, powerful APA platform and help your organization create a culture of analytics.

  • Data product manager roles & responsibilities: An inside look

    Previously, no one was responsible for developing data solutions to make analytics scalable and operational across the business.

    Then, forward-thinking organizations created the role of the data product manager to answer questions like “What data exists? Who needs it? How can we monetize? How can we make data more useful to people at our company?”

    For the ins and outs of data product management, access this comprehensive guide. You’ll learn:

    1. What is a data product & how do we treat data like a product?
    2. Data product manager responsibilities
    3. Data vs. software product managers
    4. And more

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