Python for Data Logistics & Relational Technologies - Tues. June 25 @6pm MST

University of Colorado Denver - Tuesday June 25, 2013 @ 6:00pm MST

Large auditorium (170 person capacity) with 20' screen.

Location: CU Denver - North Classroom #1539 - 1200 Larimer Street
Denver, CO 80217-3364 - Map: http://bit.ly/Tyznzg

Agenda:

6:00 - 6:15 Schmooze - Old Chicago Pizza will be served.

6:15 - 7:30 Using Python for Data Logistics by Ken Farmer

7:30 - 8:30 With the Emergence of Big Data, Where do Relational Technologies Fit? by Donna Burbank

8:30 - 9:30 Network at Old Chicago at 14th and Market.

See: http://www.oldchicago.com/denver-market-street

Using Python for Data Logistics - Abstract

Big Data and Data Science projects looking to reduce the risks, costs, and nightmares associated with managing dozens of data feeds have discovered the ETL (Extract, Transform, Load) product category. But there's no such thing as a silver bullet, and while there are practices and lessons to be learned from ETL, the tools are mostly the legacy of early 90s thinking in which data feeds were fewer, the alternative were COBOL or C, and writing code was deemed risky by DBAs and management. Ken will show how a high-level language like Python, when matched with certain practices and design patterns can offer a very successful alternative to these diagram-driven development tools. The discussion will focus on concepts, designs and patterns, and will include examples of successes and failures with a small amount of code.

Bio

Ken Farmer is a data architect at IBM where he has built and led their Security & Compliance Data Warehouses. These projects used Python extensively for systems management, general data management, ETL, and analytics. He writes about data management at www.ken-far.com (http://www.ken-far.com/), and writes data analysis tools like DataGristle for fun on the side.

With the Emergence of Big Data, Where do Relational Technologies Fit? - Abstract

The recent focus on Big Data in the data management community brings with it a paradigm shift—from the more traditional top-down, “design then build” approach to data warehousing and business intelligence, to the more bottom up, “discover and analyze” approach to analytics on Big Data. Where do relational data bases, data modeling, and data warehousing fit in this new world of Big Data? Do they go away, or can they evolve to meet the emerging needs of this exciting new technology? Join industry expert Donna Burbank as she discusses the issues and opportunities that exist for data management professionals in the Big Data environment.

Bio

Donna Burbank is a recognized industry expert and author, with more than 15 years of experience in data management, metadata management, and enterprise architecture. Donna currently is VP of product marketing for CA Technologies’ data modeling solutions. Previous to this role, she has served in key brand strategy and product management roles at Computer Associates and Embarcadero Technologies and as a senior consultant for PLATINUM technology’s information management consulting division in both the U.S. and EMEA. She has worked with dozens of Fortune 500 companies worldwide in the U.S., Europe, Asia, and Africa and speaks regularly at industry conferences. She has recently co-authored two books: Data Modeling for the Business (http://www.amazon.com/Data-Modeling-Business-Handbook-High-Level/dp/0977140075/ref=sr_1_6?ie=UTF8&s=books&qid=1234753933&sr=8-6) and Data Modeling Made Simple with CA ERwin Data Modeler r8 (http://www.technicspub.com/product.sc;jsessionid=27621D72CAB8EAE50E653231ECFFBB5A.qscstrfrnt04?productId=18&categoryId=1).