If you haven’t heard of the International Institute for Analytics (IIA) yet it is “dedicated to the advancement of analytics in everyday business practices. Under the direction of Tom Davenport, IIA brings together the world’s leading analytics practitioners and researchers to provide unique insights to both business and IT leaders on the most current research findings and industry best practices”.
Filed under: Algorithms, Datarati, Predicitive Modelling | Tags: Kaggle, Predictive Analytics
Kaggle is proud to announce a world first! In-line with the Premier’s State Plan for Open Government, the New South Wales Minister for Roads, David Borger, today announced the first ever predictive modeling competition for government.
The NSW Roads and Traffic Authority (RTA) is offering $10,000 for the algorithm that best predicts travel times on Sydney’s M4 freeway. Two years’ worth of historical data on road use between 2008 and 2010 has been made available for the competition.
The predictive model will be used to enhance the RTA’s recently launched live traffic website that provides information to motorists on incidents and congestion.
Filed under: #mktgcloud, Algorithms, Datarati, Predicitive Modelling | Tags: Data Mining, Predictive Analytics, Video
In this session Neil explores the approach to insight generation through data mining and predictive analytical technologies.
Using real world case studies he covers the ins and outs of data mining analytics on digital data, which types of techniques can be used to solve which kinds of problems and some of the challenges that you will inevitable face along the way. Discover what your data can tell you if you ask it the right questions.
Data Mining Process and Predictive Analytics
In Part I (out of three), Neil discusses the difficulty of extracting signals from all the noise present in the overwhelming quantity of data we deal with nowadays. While we now have tools for free and the cost of collecting data is diminishing, Neil questions: “what do we do with all this data?”
He introduces other tools that can help us to address some of these challenges:
- Data Mining is about discovering things we don’t already know. It is about uncovering patterns and relationships in data that we may not have already thought about.
- Predictive Analytics is using that understanding to think about what might happen in the future; it is about applying those historical patterns to predict those future outcomes.
Neil goes over the Data Mining Process and the steps needed in order to implement it and, more importantly, to get insights out of it:
- Business Understanding: what problem are we trying to solve? What is the business trying to achieve?
- Data Understanding: do we have the data to be able to answer this questions? If not, what is the cost of acquiring that additional information?
- Data Preparation: all data is dirty and needs to be cleaned and transformed. This is the heavy lifting stage.
- Analysis & Modeling: the tools must be chosen based on what the business is trying to understand and the data available.
- Evaluate Outcomes: how well does the model actually works from a statistical point of view (significance) and from a business point of view (actionability)?
- Deployment: driving the insight into the business.
Neil Mason joined Foviance as part of an acquisition of Applied Insights whom he was director and co-founder. With 25 years of in-depth industry experience in marketing analytics and strategy, Neil leads Foviance’s analytical consulting practice.This delivers an enhanced digital marketing analytics capability to both Foviance’s and Applied Insights existing and future clients.
Neil is one of the world’s leading analytics guru’s and he has a big reputation. He holds an MBA from Kingston Business School, a Diploma in Business and Economic Forecasting and currently serves on the Board of Directors of the Web Analytics Association, the global industry body for digital analytics professionals.
Filed under: #mktgcloud, Datarati, Web Analytics | Tags: Predictive Analytics
Brian Clifton (PhD), is an independent author, consultant and trainer who specialises in performance optimisation using Google Analytics.
Top 5 Predictions for Web Analytics in 2011.
2.) Optimisation rather than reporting
3.) Predictive Analytics
4.) Accessing the web will be different, so will measurement
5.) Webtrends will no longer exist
Filed under: Algorithms, Analytics, Datarati, Predicitive Modelling | Tags: Data Mining, Predictive Analytics, Visa
If you ever doubted the power of the credit card companies, consider this: Visa, the world’s largest credit card network, can predict how likely you are to get a divorce.
There’s no consumer-protection legislation for that.
Why would Visa care that your marriage is on the rocks? Yale Law School Professor Ian Ayres, who included the Visa example in his book Super Crunchers, says “credit card companies don’t really care about divorce in and of itself—they care whether you’re going to pay your card off.”
And because people who are going through a divorce are more likely to miss payments, your domestic troubles are of great interest to a company that thrives on risk management.
Filed under: #mktgcloud, Algorithms, Analytics, Business Intelligence, Data, Datarati, Predicitive Modelling, Statistics, Technology | Tags: Google Ventures, Predictive Analytics, Recorded Future
Google has invested in a startup company that claims to be able to predict the future.
The company’s investment arm, Google Ventures, has sunk an undisclosed sum into Recorded Future, a Cambridge, Massachusetts-based startup that “offers customers new ways to analyze the past, present and the predicted future,” according to a new Google VenturesWeb site that went live on Monday.
Recorded Future’s own Web site doesn’t list any products for sale, but the company appears to have developed a data analytics technology that could be used to try to predict future stock market events or even terrorist activity, according to blog posts and videos on its site. The technology looks at how frequently an entity or event is referred to in the news and around the Web over a period of time, then uses that data to project how it might behave in the future.