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 November 2015 Chapter Meeting 

Date:  November 18th 2015, Wednesday,  8:30am – 4:00pm

Host: CapTech @ 676 East Swedesford Road in Wayne, PA 19087

 

Presenters:   

 

8:30am – 9:00am

Registration & Breakfast

Sponsored by CapTech

9:00 – 9:15am

DAMA News

Eugene Desyatnik , President, DAMA Phila @damaphila

9:15 - 10:30am

Trying to Swim but Getting Swept Away: Life Preservers for Developing your Predictive Analytics Pipelines

Myles Baker, Senior Data Science Consultant, CapTech  @CapTechListens

10:30 - 10:45am

Break

10:45 - 12:00pm

Modern Data Architecture Case Study: Accolade Health Assistants®

Dan Klein, VP of Information Management, Accolade  @AccoladeInc

Jim Stagnitto, Senior Data Warehouse and Data Mining Architect, a2c  @JimStag

12:00 – 1:15pm

Lunch

Sponsored by CapTech

1:15 - 2:30pm

Setting Up the Big Data Lake

Joe Caserta,  @joe_casertaPresident,

Caserta Concepts @CasertaConcepts

2:30-2:45pm

Break

2:45 - 3:45pm

 Panel Discussion

Todd Homa,  @ToddHomaCapTech

Myles Baker, CapTech

Joe Caserta,  @joe_caserta  Caserta Concepts

Dan Klein, Accolade  @AccoladeInc

Jim Stagnitto, a2c  @JimStag

4:00pm

Happy Hour

Sponsored by CapTech

 

Sponsor(s): CapTech   @CapTechListens

 

Trying to Swim but Getting Swept Away: Life Preservers for Developing your Predictive Analytics Pipelines

 

Business is becoming increasingly data-driven: digital native companies are finding groundbreaking insights, metrics and trend-analysis is normative, and user-to-data evangelism is crumbling traditional notions of privacy. For many, this indicates a fundamental shift in society and business driven by user-generated data and the pursuit of the customer and her Internet of Things. Many organizations recognize and want to seize this predictive power but are overwhelmed by pitfalls like immature data infrastructure, traditional team norms, intimidating complexity, and scalability concerns. We will discuss how to overcome these challenges and create a roadmap to predictive analytical models for real-time reporting.

 

Myles Baker is a data scientist with experience designing and analyzing large-scale distributed processing applications in the healthcare, aerospace engineering, finance, and telecommunications industries. He specializes in predictive analytics and machine learning models, but also has hands-on development experience with Hadoop, Spark, and Cassandra. Mr. Baker received a B.S. in Applied Mathematics from Baylor University and an M.S. in Computer Science from the College of William and Mary.

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Modern Data Architecture Case Study

Accolade simplifies this elusive “last mile” to the consumer through an approach that always puts humans first. Our Accolade Health Assistants® serve as a single, knowledgeable resource to help consumers understand and coordinate the many moving parts of healthcare while addressing barriers and avoiding errors along the way. Technology plays a vital role at every step, enabling us to capture unique consumer and family insights, identify individualized care needs, match intervention types, optimize plans of action and personalize outreach and messaging strategies across any channel.

In this discussion, Dan Klein and Jim Stagnitto will discuss how they worked to architect a solution that moved Accolade’s data assets into the era of Big Data . The solution that is now in use at Accolade utilizes an innovative approach to data modeling, leverages the latest Open Source and Cloud technologies, and has delivered against an aggressive ROI.

Speaker Bios

Dan Klein leads the Information Management group at Accolade. In his time at Accolade, he has worked to advance the Business Intelligence capabilities and redesigned the way data is acquired and processed. He is passionate about developing and implementing solutions that align with strategic business initiatives to help advance Accolade’s ability to understand and assist clients. Prior to Accolade, Dan spent 13 years in the technology consulting and application run capabilities at Accenture.

Jim Stagnitto is a Senior Data Warehouse and Data Mining Architect specializing in architecting and designing large-scale, high volume, and challenging Data Warehousing solutions in the Healthcare industry.  His areas of focus include Data Warehousing, Data Quality, and Data Integration.   He is the co-author of Agile Data Warehouse Design with Lawrence Corr, guest author of Ralph Kimball’s “Data Warehouse Designer” column, Intelligent Enterprise contributor, and contributing author to the latest Ralph Kimball & Joe Caserta Book: “The Data Warehouse ETL Toolkit”

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Setting Up the Big Data Lake

Why are we doing this? Why analyze and share all these massive amounts of data? Basically, it comes down to the belief that in any organization, in any situation, if we can get the data and make it correct and timely, insights from it will become instantly actionable for companies to function more nimbly and successfully. Enabling the use of data can be a world-changing, world-improving activity and Joe presents the steps necessary to get you there and covers:

 * Understand the distinct benefits of the Data Warehouse and the Data Lake and examine how the combination of the two offers exponential gain

* Discuss key considerations before getting started  what to keep in ETL environment and what to move to the data lake)

* Learn the technology solutions that exist today to facilitate the integration of the two

* Look at the developing solutions coming to market

 Joe explains the concept of and defines the “Data Lake” and emphasizes the role of a strong data governance strategy that incorporates the seven components needed for a successful program. Attendees at this session will get answers to key questions: In the transition to Big Data, what is the toughest question that organizations must ask themselves? What are the biggest challenges of big data and why is it so hard? In the big data world, is there a role for the traditional warehouse? How do we move information out of the data lake for business benefit? What are the core technologies - and those on the horizon - that we must know about consider? Why are we doing this? Why even try and analyze massive amounts of data, and where will it get us an organization?

Joe Caserta is a recognized big data strategy consultant, author, educator and president of Caserta Concepts, an award-winning New York-based innovation consulting and technology implementation firm founded in 2001. His firm specializes in Transformative Data Strategies, Modern Data Engineering, Advanced Analytics, Strategic consulting and Technical Architecture, and Design and Build solutions, helping clients maximize data value.

Joe is co-author of the industry best-selling book The Data Warehouse ETL Toolkit (Wiley, 2004), a contributor to industry publications, and frequent keynote speaker and expert panelist at industry conferences and events. He also serves on the advisory boards of financial and technical institutions, and is the organizer and host of the Big Data Warehousing Meetup Group in NYC.