Background

Data Analytics particularly in the context of Big Data has become the ‘Mantra’ for the new genre of  Data Scientists. It helps organisations to gain insights into their data, and helps them achieve Business Intelligence. Today Business Intelligence plays an essential role in understanding the target market and the positioning of the products , services and the competition in this market place. Business Intelligence in its turn relies upon ‘Predictive Analytics’ which is an important tool in supporting Business Decisions and Performance Simulation. With the growth in the domain of ‘Streaming Data’ in on-line businesses and in real time applications such as gaming and sensor information, a new field within ‘Big Data’, namely ‘Real Time Analytics’, has emerged.

Speakers at this conference focus on the rationale and the use cases for Data Analytics; its application in multiple sectors; and the challenges, the do’s and the don’ts of implementing these powerful new technologies and tools.  The conference programme includes sessions on Predictive Analytics and Real Time Analytics and their applications in the retail sector, utilities and emerging new applications such as gaming and on-line delivery of public services.

Target Audience

The Information Systems and Business Analytics departments of the following organisations will benefit by attending this event:

  • Utility companies (gas, electricity, telephone, water)
  • Traditional retailers (providing e-delivery and online services)
  • Public sector organisations (city administration, police forces, public health authorities)
  • Online gaming companies and other online service providers
  • (Big) Data Scientists who provide services to the above range of organisations will also benefit by attending the event

In particular the I.S. as well as the Business Analytics Departments of the above companies will learn how volumes of streaming data are analysed and displayed; presenters will discuss the latest technologies.

Co-Located Events

Three co-located events:

Organised by

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Programme

  • Programme
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    Session 1: Plenary

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    Plenary keynote: Pinpointing the Persuadables: Concept, Science, and Sentiment in the 'Big Data' era
    Daniel Porter, BlueLabs
    Marketing, political campaigning, and healthcare have one major thing in common: millions of per-person treatment decisions must be selected in order to drive positive outcomes. Prior to President Obama's re-election campaign, standard practices for persuading voters—that is, changing their minds—were unscientific and driven by long-standing assumptions and hunches. This mirrors outreach efforts by other companies and organizations, which know that a certain percentage of their marketing efforts will inevitably be wasted on people who are not going to be receptive to it. Daniel Porter of BlueLabs, who served as the Director of Statistical Modeling for the Obama Campaign, will discuss his experience using the results from a large-scale randomized, controlled experiment to target persuadable voters for the Obama Campaign, as well as ways these cutting edge statistical modeling techniques can be applied to influencing behavior in realms ranging from health outcomes to customer retention. Attendees will walk away with greater insight into the capacity predictive modeling to identify individuals likely to be persuaded, and the necessary ingredients for experimental testing.
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    Short Introduction by the sponsors
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    SESSION 2: Business intelligence

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    The INFORMS Analytics Maturity Model: Developing an analytics program to realize your business objectives
    Aaron Burciaga, INFORMS/Accenture
    Business success nowadays is increasingly dependent on the collection of important data, even Big Data, and the application of business analytics that provide maximum advantage from that data. How well do you and your organization use analytics? What are the key ways you can improve? In this presentation, Aaron Burciaga, chair of the committee that created the INFORMS Analytics Maturity Model, will explain how you can do a penetrating self-assessment, plan improvements, set a timeline, and obtain any assistance you’ll need to achieve the highest level of analytics maturity.
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    PANEL 1: DISCUSSION ON THE MORNING SESSIONS AND Q&A
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    SESSION 3: Predictive Analytics

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    How Data Analytics Is Positively Impacting the World Economy One Company At A Time
    Bill Harvey, Co-Founder and Strategic Advisor, TiVo Research / TRA
    • The direct name/address matching of multimillions of homes behind privacy firewalls has now made possible more than a doubling of the sales effects of marketing for some leading edge advertisers.
    • This is that story, and how to reproduce and exceed its effects for your own company and your clients’ companies.
      • Case studies of what was done and what the results were.
      • Generalized learnings.
      • Methodological recommendations.
    • How Data Analytics Is Positively Impacting the World Economy One Company At A Time>
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    Case Study: Driving Contextual Sentiment Analytics in a CPG Environment
    Anees Merchant, Senior Vice President – Digital, Blueocean Market Intelligence

    Anees Merchant, SVP with Blueocean Market Intelligence, will share with attendees a case study that details an approach to driving sentiment analysis for a global Consumer Products and Goods company that was looking to be more focused on context. Anees will describe how the analysis helped the client in terms of business impact and improving the overall customer experience.

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    Predictive Analytics powering Personalization in eBay
    Ishita Majumdar, Ebay
    In this talk, the speaker will emphasise the role of Data Science and Predictive Analytics in ebay in the first part. This will be followed by a more focused use case, ebay solution and the value proposition of the customer.
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    SESSION 4: Real Time Analytics

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    Keep expectations of real time analytics at bay
    Diego Klabjan, Northwestern University and Opex Analytics
    Real time analytics poses additional challenges, in particular when supporting a decision maker. Through use cases mostly based on our own experience we will discuss the challenges and how to keep expectations at the right level. Learn how to approach real time analytics projects in order to maximize success.
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    Real-Time Analytics in the Enterprise: Tools and Techniques to Extend Your Analytical Capabilities

    Mike Ferguson, CEO at Intelligent Business Strategies via GoToWebinar
    This session looks at where real-time analytics fits in your analytical architecture and what tools and techniques can be used to implement real-time analytics. In particular it looks at:

    • Types of streaming data
    • The need for in-memory data and scalable analytical applications
    • First generation technologies - Complex Event Processing
    • Building custom real-time analytical applications - Streaming analytics tools for developers – IBM InfoSphere Streams, Apache Storm, Spark Streaming and more
    • Simplifying access to streaming data using SQL–based tools e.g. ParStream, SQLStream
    • Decision Management
    • Combining streaming analytics with other analytical workloads
    • Integrating streaming analytics into your existing set-up
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    PANEL 2: DISCUSSION ON THE AFTERNOON SESSIONS AND Q&A

DATA ANALYTICS WORKSHOP

PRE-CONFERENCE WORKSHOP

16 September 2015, Chicago

 

SESSION 1: DATA ANALYTICS

 

Title TBC

Aaron Burciaga, INFORMS

 

The New Best Practices for Extracting Maximum Measurable Financial Value from Marketing Using Big Data Analytics

Bill Harvey, Co-Founder and Chairman, Research Measurement Technologies

19 out of 20 users of Big Data are still limiting themselves to digital advertising, whereas Big Data can be used for all media including television, in-store, outdoor, in-theater as well as digital, social, and mobile. This workshop will provide detailed instruction and participants can ask free follow-up questions beyond the conference itself by email.

  • The 9-Step Protocol covering all aspects of maximizing ROI on Marketing
  • How to understand why advertising is or is not working, and how it is working, and how to make the creative engage emotionally and sell more effectively
  • Why it always makes sense to heavy up on key geographies, and how to identify those geographies
  • Controlled Experimentation that can be managed at scale by small teams

 

 

SESSION 2: FOUNDATIONS OF TEXT MINING AND SENTIMENT CLASSIFICATION

 

Compositional Sentiment Analysis and Deep Learning

Stephen Pulman, Oxford University/TheySay Analytics

Almost all commercial sentiment analysis systems use some kind of supervised machine learning to classify text as positive, negative or neutral. A common complaint among users is that such systems are insufficiently fine-grained, not being able to distinguish, for example, that A has a positive attitude to B but a negative attitude to C, in the same sentence. They are also often found to be inaccurate when faced with sophisticated uses of language such as “I thought I couldn’t fail to like this movie, but actually I could”.

A line of research at Oxford and elsewhere has been trying to develop “compositional” approaches to sentiment analysis, that is, approaches that are sensitive to the grammatical structure of sentences, using deep learning methods, among others.

This talk will give a non-technical overview of some of these recent research developments, and will demonstrate their utility in some practical applications of compositional sentiment analysis.

 

 

Text and Network Analysis for Sentiment Mining

Enza Messina, Professor, Department of Informatics Systems & Communication (DISCo) – University of Milano-Bicocca, Italy

In this talk we show how social relationships can be managed to improve user-level sentiment analysis of microblogs, overcoming the limitation of the state-of-the-art methods that generally consider posts as independent data. Early approaches consist in exploiting friendship relations, but since two friends could have different opinions about the same topic, it could however be inappropriate to measure sentiment similarity. We show how combining post contents and approval relations may lead to significant improvements in the polarity classification of the sentiment both at post and at user level.

 

Detection of Fake or Deceptive Opinions

Bing Liu, University of Illinois at Chicago (UIC)

 

Opinions from social media are increasingly used by individuals, businesses and organizations for making purchase decisions and making choices at elections, and for marketing and product design. Positive opinions often mean profits and fames for businesses and individuals, which, unfortunately, give strong incentives for people to game the system by posting fake or deceptive opinions to promote or to discredit some target products, services, businesses, and individuals without disclosing their true intentions, or the person or organization that they are secretly working for. In this talk, I will introduce this problem and discuss the current state-of-the-art detection algorithms.

Tickets

  • Student and Academic Rates
    199/299 USD

    Student Price 199 USD

    Academic Price 299 USD

    Limited Availability
  • Early Bird Price
    399 USD

    Click for combined Conference and Workshop Rates

    Early Bird 14 April - 24 April 399 USD

    Standard Rate 25 April – 14 May 499 USD

    End Users Organisations

    Ends 24 April
  • Early Bird Price
    749 USD

    Early Bird 14 April - 24 April 749 USD

    Standard Rate 25 April – 14 May 849 USD

    Non-Sponsoring Vendors and Consultants

    Ends 24 April

Location