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Data architecture frames how data is managed from the point of creation or collection, through processing of many kinds, to distribution, usage, and business impact. It provides concepts, structures, guidelines, and standards needed for consistency, reliability, resilience, adaptability, and sustainability of data management processes and practices.
Data architecture is a complex undertaking that describes how the many parts of data management fit together. Looking outward from data architecture, it must work together with business architecture, systems architecture, and technology architecture as an integral part of enterprise architecture. Looking inward, it must connect the dots among data models, structures, sources, processes, flows, products, services, technologies, users, use cases, business impacts, and more.
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This [insert duration] course looks at the concepts, principles, and products of data architecture through six different lenses – business alignment, data lifecycle management, data usage, content & structure, processing & storage, and technology. Putting the pieces together, the course concludes with a look at six steps to architecture design, six methods of architecture implementation, and the importance of continuously evolving data architecture.
You will learn:
- Multiple, complementary definitions of data architecture
- Why data architecture is needed – both business and technical cases
- How data architecture relates to enterprise architecture, data culture, and data governance
- Six perspectives of data architecture and the underlying concepts of each
- What is produced by architectural activities and processes
- How data architecture is developed, managed, and implemented
- Best practices for data architecture
This course is geared towards:
- Practicing and aspiring data architects
- CDOs, CIOs, andother executives with a role in defining data strategy
- Enterprise, business, systems, technology, analytics, and other architects who work with data architects
- Data engineers, application designers and developers, data systems designers and developers, and others who apply data architecture
- Anyone who needs to collaborate with data architects, and everyone with an interest in data architecture
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This exam tests knowledge and understanding of basic concepts, principles, and terminology of analytics.
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You will be tested in these areas:
- Data architecture definitions and purpose
- Relationship of data architecture with business and other architectures
- Products produced by data architecture activities
- Data lifecycles and their relationships with data architecture
- Data assets, data services, data products, and data domains
- Data stakeholders, data users, and data uses
- Data types and data models
- Data systems, data resources, and data management architectures
- Scope, variety, and types of data management technologies
- Designing and implementing data architecture
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Additional Information
Number of Questions:
Time Limit:
Passing Score:
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Once you pass the exam, you will receive a Certificate of Education documenting that you have demonstrated mastery of the topic. Further, the exam counts towards
Certified Information Management Professional (CIMP) designation .
We recommend that you take detailed notes and review the course material multiple times before taking this exam.
Click here to learn more about CIMP exams.
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