A human's guide to data architecture for data science
Build a data science-ready architecture that scales flexibly and promotes data fluency across your organization.
In this eBook, we'll explore some of the key technical aspects of data architecture that you should be thinking about as you're making decisions about how to store and access your data. This will help you understand what your options are so you can figure out what's most appropriate for specific use cases and your broader efforts across the organization.
We'll also address the cultural challenges that organizations often face as they start thinking through comprehensive data architectures so you can ensure that everyone, from your data wranglers to your subject-matter experts, are on board and involved in making data-first decisions that benefit your organization.
What you'll learn:
Getting on the same page to create a data-first culture requires breaking down silos and iterate on the process of digital transformation. We examine these aspects:
- Creating a data-first culture.
- Breaking down siloes to promote collaboration.
- Iterating to constantly improve your strategy.
- How Rapidminer fits into your data science architecture