Day 1: Wednesday, August 23rd

11:00 AM - 11:45 AM Welcome Brunch & Registration

11:45 AM - 12:00 PM Sponsor Orientation

11:45 AM - 12:00 PM Delegate Orientation

12:00 PM - 12:25 PM Chairperson Official Welcome to IQPC’s Chief Data & Analytics Officer Exchange

Opening Keynote Address

12:30 PM - 1:00 PM Overcoming the Organizational Barriers Required to Enable Data Driven Business Models

Chief Data executives have been hired in many companies and given the authority they need to drive data management and data science initiatives forward. However, many organizations are struggling with how to effectively align the “technology” of the data with the “business” of the data, and many data executives are in the midst of rewriting internal policies and standards. To successfully utilize the data to drive business, it’s critical to align data strategy with business motivation and drivers.

In this interactive session we’ll discuss how to:
•Address the gaps and challenges associated with data management and scaling the pilot initiatives across the organization
•Change organizational behavior by integrating data stewardship and accountability into the operational processes of the entire company
•Define the core building blocks of a successful data strategy
•Develop data quality control processes including the adoption of business rules and the establishment of authorization points


Plenary Session

1:05 PM - 1:35 PM Big Data Winners and Losers: The Ethics of Algorithms

Bennett Borden, Chief Data Scientist and Chair, IGED Group, Drinker Biddle & Reath, LLP
Analytic models are playing an increasing role in the development, delivery and availability of goods and services. Who gets access to what goods or services and at what price are increasingly influenced by algorithms. This may not matter when we’re talking about a $0.25 coupon for a candy bar, but what about public goods and services like education, healthcare, and energy distribution? What about predicting who will get a job or how we will police our society?

In this session, we will explore:
•The socioeconomic impact of algorithms
•The ethics of big data
•How to work ethics into our analytics projects.

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Bennett Borden

Chief Data Scientist and Chair, IGED Group
Drinker Biddle & Reath, LLP

1:40 PM - 2:10 PM Business Meetings

2:15 PM - 2:45 PM Business Meetings

2:50 PM - 3:15 PM Networking Break

Master Class A

3:20 PM - 4:05 PM Turning Data into Actionable Insights

Data is being created at a staggering pace, and too much data creates information overload. As such, organizing and storing all of this data is problematic, and companies don’t know how to use all of this data to create insight. The downside of this data chaos is poor customer service, lost productivity and risk of exposing confidential or personal information.
Join us in this session as we discuss how to turn your “dark” data into operational data by:
•Separating redundant, outdated & trivial data
•Grouping “like” documents together and determining how closely they match
•Creating metadata that includes retention periods, security policies & indexes for full-text search
•Indexing your documents and developing search criteria by word, phrase or categories
•Creating centralized visibility & control, in-place document management, and improve compliance & security

Master Class B

3:20 PM - 4:05 PM Transform Your Business’ Data into Revenue-Generating Assets with Outward Facing Analytics

Many businesses are generating more data than ever before, and the value of that data has increased exponentially. Therefore, it’s critical for your organization to unleash the value contained in the data that you already collect every day, which will help turn an underutilized asset into significant net new revenue.

In this session we’ll discuss how to design, develop and deliver flexible analytic solutions by:
•Implementing a scalable, manageable and secure platform that’s designed to deliver embedded analytics and data products to drive insights across the entire business network
•Elevating business processes and driving revenue without increasing IT and development spend or compromising the functionality and performance of your existing systems and applications
•Improving engagement and reducing operational inefficiencies due to human error
•Working alongside existing teams and tools to create and securely distribute targeted analytics

Plenary Session

4:10 PM - 4:55 PM Turning Data Analytics into Quantifiable Results

For organizations that have historically relied on hard-won experience to drive outcomes, the discipline of data-driven decision making may be a wholly new approach to thinking about how to improve business performance. An assessment of analytics maturity is crucial to company performance, so it’s important to define a framework for a repeatable analytics process.

Join this illuminating discussion as we discuss the stages necessary to creating this framework, such as:

•Defining how the organization communicates, sets and executes goals; and measures performance
•Predicting and understanding the behaviors and tendencies of your customers, and forecasting how they will behave in the future in a variety of circumstances
•Assigning the best interaction strategy to each customer based on understanding and predicting their behavior
•Identifying the best mix of strategies by balancing business objectives with the goals of customers
•Launching the optimized mix of strategies into the field and capturing the responses to those strategies
•Analyzing the results by comparing predictions, strategies, executed campaigns and customer responses in order to evaluate the impact on business performance

5:00 PM - 5:30 PM Business Meeting

5:35 PM - 6:05 PM Business Meeting

Plenary Session

6:10 PM - 6:40 PM Understanding Active and Dark Data in the Enterprise: Moving Beyond Data Governance

The traditional top down approach to data governance has failed. Organizations attempt to define target enterprise data models, formats for standard data, and an understanding of their inventory, but these goals are not achieved. Moving beyond traditional data governance means leveraging big data and analytics on the data itself to address the issue.

This session will provide a discussion around:
•Creating a robust data repository to understand the active and dark data in the operational systems
•Leveraging the repository as the hub for the data lake and for deep understanding of data profiles
•Applying machine learning and tools to drive understanding of data duplication, lineage, and uncover value
•Developing a data-driven unified data model using machine learning and SME crowdsourcing
•Ingestion of large data volumes using streaming technologies


6:45 PM - 6:45 PM Networking Cocktail Reception