The Society of Data Miners, in association with the Alan Turing Institute, is delighted to announce the first in a series of practitioner seminars. This will be a talk by Gavin Meggs, Analytics Director of Sky's Insight & Decision Science division, to be held at the Alan Turing Institute, British Library, 96 Euston Road, London NW1 2DB (near Kings Cross / St Pancras) at 2-4pm, Thursday 3rd November 2016.
Over recent years much has been made of progress in the fields of Machine Learning, of Data Science and of whatever the latest incarnation of Good Old Fashioned AI is… but the harsh reality is that in industry ‘numerical analysis’ in all its forms makes up only a fraction of the smarts you need to succeed. In this session we will look at some of the ground-breaking achievements of Sky’s Insight & Decision Science team in the media industry and how they have come into being. Across a range of topics drawn from experience in Customer Marketing, Advertising and Content we will examine the analytical techniques used, how we create space for innovation and the role that organisational design, prioritisation and pragmatism play in our success. We will also discuss some of the knotty challenges that remain and current thinking on how they may be addressed.
For background reading see: http://mediatel.co.uk/newsline/2015/10/26/sky-sciences-the-shit-out-of-stuff-google-doesnt/
Gavin Meggs is Director of Analytics within the Insight and Decision Science Department of Sky UK. He is responsible for delivering complex data insight projects in support of Sky’s strategic objectives. Gavin has an extensive background in data mining and analytical methodology development, and has broad experience in marketing and commerce, for many years working at large brands such as Orange, Ernst & Young and BT. His experience in the development of analytical teams, combined with his hands-on and practical experience of insight delivery and business development, places him at the forefront of his field.
The Society of Data Miners, in association with the Alan Turing Institute, is delighted to announce the second in a series of practitioner seminars. This will be a talk by Rick Adderley, CEO of A E Solutions Ltd, to be held at the Alan Turing Institute, British Library, 96 Euston Road, London NW1 2DB (near Kings Cross / St Pancras) at 2-4pm, Thursday 10th November 2016.
This talk will discuss the challenges of mining Police data to provide operational intelligence. Rick will introduce the data and systems involved in day-to-day reporting, resource tasking and arresting offenders, including the issues of linking data across systems and the challenges of extracting useful information from free text. Digging into more advanced analytics, Rick will discuss criminal network analysis or CNA, an important tool in crime prevention and detection, and the differences between analysing overt networks (SNA) and covert networks (CNA). Rick will describe how supervised and unsupervised learning methods have been used in the identification of prolific and priority offenders, and how the results are used to solve crimes and target offenders, and to use resources effectively. Finally Rick will describe the EU-funded FP7 project Valcri (www.valcri.org), and its task to provide a Police data set that is suitable for release into the research community.
Rick is a retired Police Officer having served for 32 years in an operational capacity. His legacy to the Service is an intelligence product which was developed for the West Midlands region and is now used by all UK Police Forces; he specialises in profiling criminal activity. Rick retired in 2003 and started his data mining company, A E Solutions, focusing within the UK Emergency Services arena. Rick is also a director of the Society of Data Miners.
The Society of Data Miners is delighted to announce a talk by Matthew Tod, Analytics Director at D4T4, which will take place at 6pm on Monday 21st November 2016 at Google Campus London, 4-5 Bonhill Street, London EC2A 4BX (between Old Street & Moorgate tube).
Digital Insight has grown up mainly in isolation from mainstream customer analytics, but now these worlds are colliding as it becomes clear that omni-channel businesses need omni-channel analytics. In this talk, Matthew will explore some of the challenges of joining big digital data to small customer data to create a more accurate view of the world. Doing this takes a fresh approach, different ways of working and the adoption of new technology such as the Apache Spark big data platform. Cost-effective new technology makes new approaches possible, but there are consequences: more data-wrangling, more coding, analytics becomes a team sport, and skills shortages increase the pressure. So the world of big data is driving fundamental innovation, and all analytical people will need to evolve to meet the challenge!
Matthew Tod is a data and analytics entrepreneur and business builder. He started his analytics journey helping to launch MathSoft, the company behind S-Plus language which was the precursor of R. Subsequently he launched the Publicis Group digital marketing agency Publicis Networks. He then created the UK’s first digital analytics consultancy, Logan Tod & Co, in 2002 and built up the business providing services to clients such as Argos, Boots, CarphoneWarehouse, Debenhams, and Sky; in 2012 he sold the business to PwC. Today he has two roles: leading the analytics team at D4t4 Solutions Plc where he is creating a new business blending online big data with customer data, and providing analytics leadership to customer data platform company Celebrus Technologies.
The Society of Data Miners is an independent non-profit organisation for the public good with the purposes to:
- Increase the benefits of data mining to society;
- Increase knowledge and awareness of the nature and benefits of data mining;
- Advance the profession of data mining;
- Form a community of and for data miners.
In pursuit of these purposes, the Society of Data Miners will:
- Hold events for data miners to exchange experience, formulate best practice and broaden the scope and benefits of data mining;
- Encourage adoption of the highest ethical standards in data mining;
- Provide public and media information about data mining and its benefits;
- Provide certification of data miners who have reached a recognised level of competence and experience in data mining practice;
- Encourage the creation of a literature of data mining practice;
- Encourage data mining standards;
Many thanks to Ashish Umre from Tesco for his insights into digital optimisation analytics in a large corporate environment, and to all who attended and contributed to the lively discussion!
Many thanks to Sophie Sparkes from Tableau for her excellent and entertaining presentation on 25/11/15. Thanks also to Christophe Le Lannou for organising the event, and to the Digital Catapult Centre for hosting us.
Slides are available here:
Rich Huebner is undertaking valuable research into the impact of management involvement on the success of data mining projects. Please take his survey here: https://www.surveymonkey.com/r/tms-and-data-mining
Many thanks to all those who attended and took part in the discussion; it is your contribution which makes these events so worthwhile.
You can download the slides here:
Predictive Analytics assists the achievement of business objectives; a Predictive Analytics Strategy indicates what business objectives will be achieved through Predictive Analytics, how they will be achieved, and how the business benefit will be measured. Many organisations are in need of a strategy for Predictive Analytics, and Tom will address this need in two ways: by listing and organising the elements which make up such a strategy, and by outlining the activities needed to develop such a strategy in a specific business situation. Also including pitfalls in Predictive Analytics Strategy, using examples from commercial and government organisations.
This is one of 3 FREE webinars in association with the UNICOM Data Analytics conference, also including big data challenges in financial services and predictive analytics for TV advertising performance.