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Midlands Business Intelligence Forum
Harvey Nash Presents The Third:
David Milburn Principle Consultant How are companies getting value from Big Data Analytics?
Pana Lepeniotis Chief Data Architect MDM, Data Quality and the importance of taxonomy on an organisations’ data lifecycle
Brian Cain Lead BI Architect “Perfect Is the Enemy of Done" - How Agile BI in a governed environment has changed the delivery model
Agenda For The Evening
To finish between 7:30-8:00pm, then onto a local restaurant for those who are interested in carrying on the debate.
The Forum
- Motivation and Purpose:
• Everything is in in London!• Manchester, Bristol and Leeds are attempting to emulate• To build and grow BI expertise in the Midlands.• To share problems, pitfalls and solutions.
- Future location:
• We are on the lookout for somebody to host the next forum. If it might be of interest, please do let me know.
- Frequency:
• Keen to get everyone’s thoughts afterwards.
Now over to David Milburn
BIG DATA – Getting Value
David MilburnMidlands BI Forum – December 4th
2014
Safe Harbour
The information in this presentation is based on personal industry analysis/experience and does not represent any strategy or opinions of the company that I work for.This document is provided without a warranty of any kind, either express or implied.
Augmented Gartner V-Model
Value
Volume
Velocity
Veracity
Variety
What is BIG DATA Analytics
• It is not a single dimension of the V-Model but at least 3 dimensions
• It is a cultural shift from reporting & dashboards to being data driven and analytical
• It is not a technology such as an appliance it is enabled by technology
• It is driven by hypothesis or data discovery• Typical technologies include HADOOP, NOSQL, Graph DBs,
Geospatial, R, Entity extraction, sentiment analysis, mathematical models (predictive & advanced)
Value
Volume
Velocity
Veracity
Variety
Customer Use Cases
• Segmentation• Propensity to default• Decision trees• Embed in to systems• Measure & Refine• Target non-payers,
defaulters and offer payment schemes
• Life time value of customer• Design treatments• Embed in to systems• Measure & Refine• Ensure repeat business
BBC TV Licencing AVIS Car Rental
Value
Volume
Velocity
Veracity
Variety
Customer Use Cases
• Logical network modelling• Geospatial modelling• Object modelling of capacity &
capability• Real-time data capture of people,
trains, freight• Mathematical modelling of vehicle
movement• Forecast arrival, improve service and
safety
• 24 x 7 real-time capture of machine sensor data for borers, trucks etc.
• Geospatial modelling• Mathematical modelling • Move from schedule to predictive
maintenance (>£100k per day when truck is out)
Swiss Rail Mining / Natural Resources
Value
Volume
Velocity
Veracity
Variety
How to prepare
• Work with vendors to understand capability of technology & visualisation tools: POC
• Shift focus from managing infrastructure and applications to leveraging data
• Explore data within data sets not previously utilised but are important to the business
• Identify areas where analytics capability exists and consolidate for competitive advantage
• Identify projects where value can be realised and get executive commitment
Value
Volume
Velocity
Veracity
Variety
BIG DATA – Getting Value
David MilburnMidlands BI Forum – December 4th
2014
THANK YOU
