Designing and Implementing Analytics Data Architecture is a new business intelligence course designed to address modern data management challenges and provide insights into modern practices and data architecture design patterns and extends both our BIe and data architecture curriculums.

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In today's rapidly evolving business world, utilizing data and analytics has become imperative for organizations to compete effectively. However, with the ever-advancing technologies and capabilities, it is challenging for businesses to keep up with the changes and manage data for maximum impact. Despite this, most organizations still cling to the outdated data architecture of the BI era, which is insufficient for supporting modern analytics use cases. Merely patching new components onto the surface of legacy architecture is not sustainable and fails to provide adequate support for modern data requirements.

Although modern data architecture may seem complex and difficult to implement, it is crucial to step up and embrace it. The first step is to define the necessary business and data capabilities, followed by integrating new capabilities into the existing data management practices.

The step-by-step approach outlined in the course ensures that businesses can establish a sustainable and adaptable data management architecture that caters to their present and future needs. By taking this course, businesses can gain a competitive edge in the market and achieve maximum value from their data resources.

You will learn:

  • The reasons that legacy data architectures need to be modernized
  • The multitude of requirements for effective analytics data management
  • The similarities and differences of Data Lake, Data Fabric, and Data Mesh architectures
  • Techniques to identify analytics business capabilities and requirements
  • Techniques to identify analytics data capabilities and requirements
  • How to apply architectural design patterns and frameworks
  • How to adapt reference architectures
  • The path from requirements to a well-designed architecture
  • Six techniques for architecture implementation

This course is geared towards:

  • Practicing and aspiring data architects
  • CDOs, CIOs, and other executives responsible to provide data management leadership
  • Enterprise, analytics, and technology architects who work with data architects
  • Data engineers and systems engineers
  • Designers and developers of data management and analytics systems
  • Anyone who needs to collaborate with data architects

The course is developed and delivered by elearningCurve Education Director, Dave Wells and  Daniels College of Business  lecturer Jed Summertonand will contribute towards a Certified Information Management Professional (CIMP) accreditation in Data Architecture or the CIMP in Business Analytics.

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