UNDERSTANDING DATA ARCHITECTURE

And how to connect it to business value

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Data architecture is the foundation of every organization’s data strategy, but it's not just something for CIOs and data architects either - everyone at data-powered organizations can benefit from understanding the ways data moves between teams and flows into data projects to yield insights.

Get the guidebook that breaks down the basics, including:

  • Key data architecture terms explained from a non-technical perspective.
  • Illustrated examples of data architecture concepts.
  • How to align architecture with business priorities and KPIs.

Get the Guidebook

About the Authors

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Grant Case & Harizo Rajaona
Senior Analytics Architect / R&D Engineer at Dataiku

Grant is a Customer-Facing Data Scientist and Analytics Architect with Dataiku. In this and his prior roles, Grant has spent time with 100+ companies understanding and architecting solutions for both business analytics and data science platforms. When not working with Dataiku clients, Grant is a Lecturer at Columbia University in the Applied Analytics program and enjoys volunteering at his son's school.

 

Harizo has a background in mathematics and computer science and holds a PhD in Computational and Applied Mathematics from the University of Lille. He works on the R&D team at Dataiku, focusing on technical ecosystem integrations, particularly the challenges of enterprise-grade deployments (security, availability, and scalability).

 

Learn More on LinkedIn

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About this Guidebook

This guidebook is divided into two sections focusing on two major business concerns impacted by data architecture: scalability and security. In order to design (and then maintain) a data architecture that doesn’t hamper an organization, but rather enables it to grow and succeed, these are key considerations. This guidebook also contains:

 

  • Key terms and architectural processes accompanied by clear illustrations.
  • Communication guides on how to collaborate effectively with a variety of teams to design and maintain an ideal data architecture.
  • An exploration of how an organization’s unique structure and industry can impact their ideal architecture.
  • Ways to get proactive about data and service security by examining priorities and potential failure points in an attempt to mitigate risks.
  • And more!
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Excerpt from the Guide

When users want real-time data, architects think distributed systems. But depending on the use-case, operations occurring in “real-time” can mean vastly different things to different people, so the key as a non-data architect is to be clear. If dashboards need to be updated every minute as opposed to refreshing overnight for the next day,

this places divergent constraints on what the architecture needs to support. Nothing beyond physical sensors is actually able to function in real-time, but so long as communication about the time-sensitive needs of the business is clear, then architectural priorities can respond.

Get the Guidebook

Don’t let broad knowledge of data architecture be a limitation; take understanding to the next level with our free illustrated guidebook.

 

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