Data Analytics, particularly in the context of Big Data, has become the ‘Mantra’ for the new genre of Data Scientists. By applying analytics to structured and unstructured data and mining, that is, extracting items of information which are important for business planning and execution; enterprises are changing the way they plan and make business decisions. Given that many business decisions are influenced by behavioural biases, Sentiment Analysis represents another valuable source of information that aids business decisions and performance evaluation.
This conference explores Data Analytics and Sentiment Analysis and their connections to business intelligence. It provides a platform to discuss how businesses can benefit from Data Analytics and Sentiment Analysis to aid decision making and thus respond to “market pull”. The programme includes talks from subject experts, case studies and opportunities for networking and discussion.
The conference is characterised by a compact format: a single track, one-day event covering two important information sources for business intelligence. As a consequence, the event not only provides attendees with the opportunity to learn more with less time out of the office, but it also offers a rich networking experience.
Topics to be covered:
Chairman: Stephen Nelson-Smith, Principal Consultant, UNICOM
Alec McCutcheon, Director, UNICOM Seminars
Clive Holtham, Professor of Information Management; Director; Cass Learning Laboratory, Cass Business School, City University London
The success of the incredible technology-based innovations of the 20th century has masked a major change taking place globally. Much of conventional problem-solving has been converted to contexts which are relatively predictable and machine-supported. This means that the tasks facing executives in organisations have shifted from planning and control of the everyday, to coping with the an increasingly turbulent future. This future is not simply unknown, it is in crucial respects unknowable. Those of us working in intelligence, innovation and technology therefore need as a matter of some urgency to focus on how to deal with this volatile future. This presentation draws on extensive research and development work to show how organisations, their managers and their systems need to adapt to volatility.
Jim Anning, Head of Data and Analytics at British Gas Connected Homes
Big companies have been practising “Business Intelligence” for around 150 years, but most companies have grown up dealing with small volumes of relatively meaningful data... Sales, Web visits, Resources etc…
Mobile Technology and the Internet of Things are making it cheap to collect large volumes of relatively meaningless data… temperatures, motion sensors, location, tweets etc. How do you even begin to make sense of it all?
Jim Anning heads up Data & Analytics for Connected Home, the company behind Hive. With more data from homes around the UK than any other organisation, Jim’s team of Data Scientists and Engineers build algorithms to create value from the raw data and ultimately bring intelligence to our homes.
In this talk Jim will outline the approach his team take to dealing with a multitude of tiny data points, mining those, making the data meaningful and delivering products that customers value. Along the way he’ll try and answer the question “Can Home Intelligence learn from Business Intelligence and can Business Intelligence learn from Home Intelligence?”
Chairman: Richard Veryard, Head of Data and Intelligence at Glue Reply
Dr Nikolaos Vlastakis, Lecturer in Finance, University of Essex
Recent research has linked internet search activity to the stock market. In this paper, we use the daily internet search volume index (SVI) from Google as a means of enhancing forecasts of the volatility of the stock market. The superior volatility forecasts are translated to direction of change forecasts and evaluated statistically and economically. Our results reveal that investors can form profitable investment strategies using the SVI.
Tilman Sayer, OptiRisk Systems
We present a use case in the domain of trading and risk control. We describe an information architecture and the related modelling paradigms in which sentiment and market data are combined. The analytic models capture the impact of sentiment on asset prices. The ex-ante predictive models followed by decision models for trading are described, the ex-post performance is evaluated, key figures are summarised. Finally we briefly show our control panel for algorithm control and results display.
Bhupendra Patil, Senior Solutions Architect, RapidMiner
Dai Clegg, independent consultant
Ben Houghton, Data Scientist, Barclays plc
Social Media is a key tool for helping organisations understand their customers better and become more client centric. One key barrier is the difficulty of analysing this data and extracting insight at scale. This seminar talks about the challenges associated with applying Natural Language Processing to Social Media data to gain meaningful insights.
Barend Botha, Seven Symbols Ltd / IoTDataViz.com
As the internet of Things is starting to take shape, there is a growing need to make sense of the avalanche of data and the hidden insights that it contains. With the rapid pace of change, an ever expanding web of technologies, hardware and networks, Data Visualization plays a key role in finding and presenting the insights and value for business and consumers alike.
During this session we will explore the value, complexity and opportunity of Data Visualization for The Internet Of Things, highlighting some real world examples and case studies from Wearables through to Smart City application areas.