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3 ways to modernize your analytics environment

Modern technological offerings have radically changed the analytics landscape. Performance, agility and simplicity have now become its cornerstones, making a compelling argument for modernizing older analytical environments.

But what’s the key to a successful modernization project?

In this paper, discover how to implement a successful analytics modernization project. Explore 3 logical approaches for migrating to a new analytics environment, and learn:

  • How to replace your existing enterprise data warehouse
  • How to augment the capabilities of your legacy data warehouse
  • Best practices for designing a new logical analytics architecture
  • And more

These are also closely related to: "IBM Dynamic Warehousing"

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    The advent of big data changed data analytics, but not necessarily for the better. Right now, companies often struggle to turn the massive amounts of data that they’ve collected into useful, unified data sets.

    Disparate data storage locations and types, a lack of unified database structures, and changes to a pipeline are just a few of the issues your company could be running into. No to mention, once the data is on hand, it can be another struggle to make it readable information for those who need it.

    Download this ebook by Dremio to examine some of the challenges and trends in the data management world right now.

  • Emergence of data cataloging for modern data management

    The data catalog has emerged in recent years as a key enabler for modern data management architectures – providing the functionality to allow users to discover and access data across the data estate.

    Download this 451 Research report to learn about data cataloging specialist Alation, and explore Alation’s positioning around governance for insight, as well as its partnerships and its search-and-behavior-based machine functionality as adoption becomes more widespread.

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