EDB singapore and Data Scientists

by Albert Anthony D. Gavino

Would you consider in working in Singapore, Predictive Analytics, Business Intelligence, Analytics ranging from HR, Business, Non-profit and even Medical Science are now the in field when talking about the sexiest occupation in the next two to three years.

the Business Sector Software is controlled by three big names: IBM, SAP and SAS. Background in Statistics, Machine Learning and Databases is most preferred by Companies, and it would be a big help if applicants and beginners get a grasp of the learning concepts such as Logistic Regression, Time Series, Cluster Analysis and Association. Still a lot of open source software are available such as WEKA and Rapid Miner, though free ware are more raw and a bit needs more sharpening compared to the big names. Though that wont hurt but its more power than your Excel spreadsheet software and Pivot Tables.

Global News Network: Big Data Analytics

Just finished with a program Interview on GNN, entitled Big Data Analytics which covers Business Intelligence and Predictive Analytics, it will be aired on Channel 8, Destiny Cable/Sky Cable on Tuesday July 30 from 10 am to 11 am. Mr. Toti Casino is the host and current president of the Philippine Computer Society (PCS)

Predictive Analytics World Conference 2013

Cross-Industry, Cross-Vendor Sessions

The only conference of its kind, Predictive Analytics World delivers vendor-neutral sessions across verticals such as banking, financial services, e-commerce, entertainment, government, healthcare, high technology, insurance, non-profits, publishing, and retail.

And PAW covers the gamut of commercial applications of predictive analytics, includingresponse modeling, customer retention with churn modeling, product recommendations, online marketing optimization, behavior-based advertising, fraud detection, insurance pricing and credit scoring.

Why bring together such a wide range of endeavors? No matter how you use predictive analytics, the story is the same: Predictively scoring customers and other organizational elements optimizes business performance. Predictive analytics initiatives across industries leverage the same core predictive modeling technology, share similar project overhead and data requirements, and face common process challenges and analytical hurdles.

The Cross-Vendor Summit:

• Meet the vendors and learn about their solutions, software and services
• Discover the best predictive analytics vendors available to serve your needs
• Learn what they do and see how they compare.

Valuable Colleagues:

• Mingle, network and hang out with your best and brightest colleagues
• Exchange experiences over lunch, breaks and the conference reception, connecting with those professionals who face the same challenges as you.

Conference scope

Predictive Analytics World's sessions cover business applications of predictive analytics, including:

• Marketing and CRM (offline and online)
  • Response modeling
  • Customer retention with churn modeling
  • Acquisition of high-value customers
  • Direct marketing
  • Database marketing
  • Profiling and cloning
• Online marketing optimization
  • Behavior-based advertising
  • Email targeting
  • Website content optimization
• Product recommendation systems
• Insurance pricing
• Credit scoring
• Fraud detection

Predictive Analytics book by Eric Siegel

by Albert Anthony D. Gavino

For Predictive Analytics newbies, this would be a good book, it discusses analytics in a more simpler way and how companies are using analytics to their advantage.

the book is more on applications instead of the technical know how on predictive analytics.

Predictive Analytics book by Eric Siegel

In this rich, entertaining primer, former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction:

• What type of mortgage risk Chase Bank predicted before the recession.


• Predicting which people will drop out of school, cancel a subscription, or get divorced before they are even aware of it themselves.


• Why early retirement decreases life expectancy and vegetarians miss fewer flights.


• Five reasons why organizations predict death, including one health insurance company.


• How U.S. Bank, European wireless carrier Telenor, and Obama's 2012 campaign calculated the way to most strongly influence each individual.


• How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy!.


• How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job.


• How judges and parole boards rely on crime-predicting computers to decide who stays in prison and who goes free.


• What's predicted by the BBC, Citibank, ConEd, Facebook, Ford, Google, IBM, the IRS, Match.com, MTV, Netflix, Pandora, PayPal, Pfizer, and Wikipedia.

Buy the Book:

    
    

What are Lift Charts?

by Albert Anthony D. Gavino

Lift Charts help us evaluate data mining models.

You can tell from the chart that the ideal line peaks at around 40 percent, meaning that if you had a perfect model, you could reach 100 percent of your targeted customers by sending a mailing to only 40% of the total population. The actual lift for the filtered model when you target 40 percent of the population is between 60 and 70 percent, meaning you could reach 60-70 percent of your targeted customers by sending the mailing to 40 percent of the total customer population.

a Lift Chart Example from Microsoft Business Intelligence

HR analytics

Today offices have become smarter, even the HR department has become more evil complete with devil tails  collecting our data from time to time. Take this for example

Predictive Analytics on Employee data

• what days do employees take sick leaves?
• can we predict if an employee gets sick more often to predicting resigning?
• how about predicting on what months female employees get pregnant or give birth
• or what common illnesses are present during the month of June, are employees filing for the common cold sickness?

Now consider yourself an HR executive, and have all these rich big data at your fingertips, you can connect this data with Facebook Data and LinkedIn Data, employees who have undergone training, would they post it on facebook or post it on LinkedIN, are your employees joining professional organizations? how do you track you employees whereabouts? Are they drinking on friday nights? or are they watching movies with friends and families?

a Call Center Employee

IBM Products:

IBM SPSS Modeler and IBM predictive analytics have the power to analyze your employee data.