Meeting #1 - Welcome

January 26th, 2012 4pm-6pm

The Magnolia Hotel is only a block or two from light rail and centrally located downtown one block off of 16th street mall. Harry's bar is conveniently located upstairs from the meeting room.

AGENDA

WELCOME - Overview of meetup (10 min) INTRODUCTIONS - Meet new members (5 min) EVENT ANNOUNCEMENTS - Attendees welcome to briefly mention upcoming events that the group might appreciate (5 min max) JOB ANNOUNCEMENTS - Attendees can announce job openings and information to the group. (5 min max). Presentation 1 (30 min) Shannon Lucero - Informatica Pushdown Optimization for Big Data Presentation 2 (30 min) Bob Conway - A Modular Approach to Data Integration Logic Presentation 3 (30 min) Kevin Goodfellow - Data Vault Modeling 101 Take meeting upstairs to Harry's bar for further discussion, drinks, and snacks.

Drinks and snacks for this meeting sponsored by: Datasource Consulting.

ABSTRACTS:

Informatica Pushdown Optimization for Big Data

Many companies are utilizing data warehouse appliances and distributed big data environments to store and process their increasing data volumes. Companies using an enterprise ETL tool to integrate and process their data need to look at alternate ETL implementations to avoid potential I/O constraints in the ETL itself. Informatica’s Pushdown Optimization feature allows users to more fully leverage these environments while continuing to benefit from the features that an enterprise ETL tool provides. Shannon's presentation leverages his real world/hands-on experience to point out pitfalls and best practices for implementation of Informatica's Pushdown Optimization.

A Modular Approach to Data Integration Logic

Implementing logic to stitch together disparate data sources can be extremely complex and difficult. In this presentation Bob outlines an approach that simplifies the complexity of data integration logic by modularizing the task into discrete, coherent steps. This modular/reusable approach is easier to plan, design, test, and maintain, thus reducing long term costs, increasing durability and flexibility.

Data Vault Modeling 101

The Data Vault Modeling method is a hybrid modeling technique, created by Dan Linstedt that leverages the positive aspects of the Kimball and Inmon methods, while attempting to minimize the negative impacts of both. The method was created in Denver 10 years ago and has been growing rapidly worldwide with the expansion of distributed database architectures and growing data volumes. Kevin was the first person to be trained in the Data Vault method and also the first to implement it in the field. In this short discussion, Kevin outlines the basic components of the method, positives, negatives, and a few brief examples.