This talk examines key trends in analytics deployment and developments in advanced technology. Specific areas of focus include: (1) data acquisition and delivery, (2) operational intelligence in the real-time enterprise, and (3) analytic applications architecture. The implications of these technology developments for analytic implementations will be discussed with examples from across a number of different industries. Learn about key trends in data acquisition and delivery and analytic applications architecture, and discover important modes of delivering operational intelligence.
The proliferation of mobile devices and a new breed of consumers is driving a revolution in requirements for pervasive access to data for marketing analytics. A new breed of consumers has emerged with a DIY (Do It Yourself) mindset related to technology and unprecedented sophistication in using data for personal decisions. This change in consumer behavior is creating demand for consumer intelligence capability in which direct access to data is required for personal decision making. We will discuss the implications of this phenomena for deployment of omni-channel marketing and illustrate leading edge case studies in the delivery of marketing intelligence integrated across all channels.
The era of Big Data presents exciting opportunities for leveraging analytics to create competitive advantage and new sources of revenue. To maximize business value, however, an enterprise must innovate in the context of good governance models to avoid technology projects for the sake of technology. In this workshop we describe a framework developed at the Massachusetts Institute of Technology for maximizing business value with the right combination of innovation and governance. We will examine new scenarios for monetising from Big Data sources. We will also explore opportunities for exploiting non-traditional data types from both internal and open data sources.
There are a significant number of big data analytics opportunities where graph processing is an effective model of computation for problem solving. In this workshop we present a programming model for implementation of graph algorithms and explain how the execution model works. We also provide example applications in the area of social network analysis, product cross-selling, and fraud detection.
Trends in healthcare are toward more data, more complexity, more decisions, and less time and resource for execution. The only way to be successful in this environment is to leverage a more advanced framework for healthcare analytics. This seminar will discuss best practices in healthcare delivery and architecture frameworks for realisation of decisioning services for improving quality and efficiency of care. A reference architecture for deployment will be described in detail along with cases studies of successful realisation in major healthcare organisations within the United States. Special emphasis will be placed on the value proposition for integration of disparate data sources such as Medicaid, TANF, Child Support, and SACWIS.
Mark Twain, a famous American author, once stated that there are “Lies, Damned Lies, and Statistics.” This phrase is used to describe the persuasive power of numbers, particularly the use of statistics, to lead people to draw incorrect conclusions. This workshop describes the subtle mistakes that can easily be made when interpreting the results from an analytic study or report. We describe logically sound processes for deciphering data using methods designed to illuminate actionable information for data scientists without distracting or misleading the knowledge worker from the relevant facts needed for effective decision-making.
The concept of “Data Lake” is becoming a widely adopted best practice in constructing an analytic ecosystem. When well executed, a data lake strategy will increase analytic agility for an organisation and provide a foundation for provisioning data into both discovery and integrated data platforms. However, there are many pitfalls with this approach that can be avoided with best practices deployment. This workshop will provide guidance on how to deploy toward the “data reservoir” concept rather than ending up with an all too common “data swamp”.
The next wave of Big Data Analytics (BDA) will be dominated by sensor data and interconnected devices. This third generation of BDA will dwarf first (weblog) and second (social media) generation data sources in both size and value. This seminar examines the opportunities and challenges associated with collecting, storing, and analysing data produced from the Internet of Things (IoT). We will also discuss best practices in creating value from IoT data using case study examples within both the B2C and B2B sectors.
The use of big data is a lynch pin in the deployment of smart cities of the future. The potential of big data goes far beyond the efficiencies that can be created in areas such as energy consumption, health care, education, and law enforcement. The true potential of big data is directly engaging society in governance through increased transparency and delivery of services using access to data as a foundation. This workshop will provide mini-case studies in a range of settings from developed countries such as the USA and developing countries such as Pakistan. An emphasis of the discussion will be on how city governments can use data to improve quality of life for their citizens.