Instructor:
Tim Daciuk
Business Development Manager, Advanced Analytics, IBM

Workshop sponsored by:

Workshop

Friday October 21st, 2011 in New York City
Full-day: 9:00am - 4:30pm

Hands-On Introduction to Text Analytics
with IBM SPSS

Intended Audience:

• Managers: Project leaders, directors, vice presidents, marketing manager, product manager, and managers of any kind involved with data driven decision making
• Analysts: Marketing analysts, product analysts, financial analysts and business analysts who want to be more effective in having an impact via text analytics
• Technology experts: Data analysts, BI directors, developers, DBAs, web analysts, and consultants who wish to extend their expertise to text analytics

Background Required: An interest in leveraging textual data as an asset.

For more on text analytics, see the colocated conference, Text Analytics World

Workshop Description

Your organization holds an increasing amount of data in unstructured and semi-structured formats from customer e-mails, call center logs, incident descriptions, suspicious transaction reports, open-ended customer survey responses, news feeds, Web forms, and so on. Leveraging this information in a thorough and systematic way is increasingly critical in order to understand customer behavior and attitudes, develop successful predictive models and drive business decisions.

This introduction to text analytics provides true hands-on experience, using IBM SPSS Modeler and IBM SPSS Text Analytics software. The course will guide you to actively analyze text, improving the understanding of unstructured data, and using this understanding to enhance data mining models.

Outline of Topics and Hands-On Activities:

1. Introduction
   Text and data mining
   Voice of the customer


2. A Text Mining Example
   Introduction
   A Typical Text Mining Session


3. Linguistic Analysis and Text Mining
   The steps in text extraction
   Categorizing extracted terms and concepts
   Linguistic resources


4. Creating a Text Mining Concept Model
   Text mining concept model
   Relationships between concepts and data


5. Clustering Concepts
   Introduction
   Building clusters


6. Creating Categories
   Preparing for categorization
   Extending categories


7. Using Text Mining Models
   Exploring the text mining model
   Developing a model using categories and customer data
   Scoring new data


8. More software: A Look at Cognos Consumer Insight
   What is Cognos Consumer Insight (CCI)
   Applications of CCI
   Social Media/Blog Analysis
   An example and live software demonstration

Software
While most of the concepts covered during this workshop apply regardless of the particular text analytics software employed, this workshop proides hands-on experience with a leading software solution: IBM SPSS Modeler and IBM SPSS Text Analytics. A software license will be made available to participants for use on that day (included with workshop registration).

Attendees receive a copy of the course materials at the beginning of the workshop.

Schedule

Price and Registration Info:

• Workshop starts at 9:00am
• Morning Coffee Break at 10:30am - 11:00am
• Lunch provided at 12:30 - 1:15pm
• Afternoon Coffee Break at 2:30pm - 3:00pm
• End of the Workshop: 4:30pm

Instructors

Tim Daciuk, Business Development Manager, Advanced Analytics, IBM

Tim Daciuk is a Business Development Manager with IBM. Tim works to help customers, and potential customers better understand the value of Predictive Analytics; how that aligns with the IBM software family, and, how it aligns with customer business strategies. Tim provides customers with everything from a business understanding to in-depth technical demonstrations of the Predictive Analytics product suite in action. Additionally, Tim is an accomplished speaker and has spoken at conferences, meetings and professional seminars throughout Canada, the U.S., Europe and Asia. Tim also leads several seminars in Predictive Analytics across North America for audiences from technical specialists to business decision makers.

Tim Daciuk has a 30 year history in statistics, data mining and predictive analytics. He has worked in roles as a consultant, trainer, pre-sales, and marketing. Tim has worked with both Public Sector and Commercial endevours, as well as serving as an advisor to many academic research projects. Of late, Tim has specialized in the use of data and text mining and how these technologies can be applied in a business context, across industries. Tim works closely with industry and software leaders to help business government and institutions understand and unlock the power of predictive analytics.