Designing a Deliberate Architecture for Data Engineering, Data Integration, Application Integration, and Data Preparation
  Richard Sherman   Richard Sherman
Managing Partner
Athena IT Solutions
http://athena-solutions.com/datadoghouse/
 


 

Tuesday, October 9, 2018
01:30 PM - 04:45 PM

Level:  Intermediate


A deliberate architecture for data integration helps keep projects on schedule and on budget; improves data quality and data governance; and increases business users’ confidence in data. But many companies resort to a trial-and-error method of gathering data that is disorganized and incomplete. In this workshop, you’ll learn how to design a hybrid integration architecture that supports data, application, and cloud integration. Data may be stored in relational, columnar, or in-memory DBMS, NoSQL, or Hadoop; logical DW, data lake, or data hub; data virtualization; data services, both inter- and intra-enterprise; and, within analytical processes (data blending or preparation). We will review and contrast integration use cases and best practices spanning technologies. We will review roles and responsibilities of IT, data science teams, “citizen” data scientists, and business “power” users.

Key topics:

  • Underlying concepts and architectures
  • Use cases and best fit technologies
  • Best and pragmatic practices
  • Roles and responsibilities of integrators

Many enterprises have siloed integration efforts that are redundant and overlapping. This tutorial will discuss, contrast, and match various types of integration use cases, architectures, technologies, and products.


Rick Sherman is the founder of Athena IT Solutions and has 30 years of business intelligence (BI), data integration, and data warehousing (DW) experience. He has worked on 100-plus BI/DW projects and has also provided guidance through assessments and as an advisor. His work has spanned industries, source systems, and technologies. Rick is an expert instructor and speaker at conferences, webinars, and seminars. He teaches business and IT people BI/DW concepts, design, architectures, and project management through onsite and online courses. He has taught BI courses for 10-plus years at Northeastern University's Graduate School of Engineering. His book "Business Intelligence Guidebook - From Data Integration to Analytics" (Morgan Kaufmann 2014) is used by practitioners and as a graduate textbook. Rick has had 200-plus articles published in industry publications. Rick also performs marketing and industry analysis for firms that create software for the BI industry.


 
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