Anasse Bari - Predictive Analytics For Dummies

Predictive Analytics For Dummies

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Library of Congress Control Number: 2013954216

ISBN 978-1-118-72896--3 (pbk); ISBN 978-1-118-72941-0 (ebk); ISBN 978-1-118-72920-5 (ebk)

Manufactured in the United States of America

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Chapter 1

In This Chapter

Explaining the building blocks

Probing capabilities

Surveying the market

Predictive analytics is a bright light bulb powered by your data.

You can never have too much insight. The more you see, the better the decisions you make and you never want to be in the dark. You want to see what lies ahead, preferably before others do. Its like playing the game Lets Make a Deal where you have to choose the door with the hidden prize. Which door do you choose? Door 1, Door 2, or Door 3? They all look the same, so its just your best guess your choice depends on you and your luck. But what if you had an edge the ability to see through the keyhole? Predictive analytics can give you that edge.

What would you do in a world where you know how likely you are to end up marrying your college roommate? Where you can predict what profession will best suit you? Where you can predict the best city and country for you to live in?

In short, imagine a world where you can maximize the potential of every moment of your life. Such a life would be productive, efficient, and powerful. You will (in effect) have superpowers and a lot more spare time. Well, such a world may seem a little boring to people who like to take uncalculated risks, but not to a profit-generating organization. Organizations spend millions of dollars managing risk. And if there is something out there that helps them manage their risk, optimize their operations, and maximize their profits, you should definitely learn about it. That is the world of predictive analytics.

Big data is the new reality. In fact, data is only getting bigger, faster, and richer. Its here to stay and youd better capitalize on it.

Data is one of your organizations most valuable assets. Its full of hidden value, but you have to dig for it. Data mining is the discovery of hidden patterns of data through machine learning and sophisticated algorithms are the mining tools. Predictive analytics is the process of refining that data resource, using business knowledge to extract hidden value from those newly discovered patterns.

Data mining + business knowledge = predictive analytics => value

Todays leading organizations are looking at their data, examining it, and processing it to search for ways to better understand their customer base, improve their operations, outperform their competitors, and better position themselves in the marketplace. They are looking into how they can use that information to increase their market share and sharpen their competitive edge. How can they drive better sales and more effectively targeted marketing campaigns? How can they better serve their customers and meet their needs? What can they do to improve the bottom line?

But these tools are useful in realms beyond business. As one major example, government law enforcement agencies are asking questions related to crime detection and prevention. Is this a person of interest? Is this person about to commit a heinous crime? Will this criminal be a repeat offender? Where will the next crime happen?

Other industries, notably those with financial responsibility, could use a trustworthy glimpse into the future. Companies are trying to know ahead of time whether the transaction theyre currently processing is fraudulent, whether an insurance claim is legitimate, whether a credit card purchase is valid, whether a credit applicant is worthy of credit the list goes on.

Governments, companies, and individuals are (variously) looking to spot trends in social movements, detect emerging healthcare issues and disease outbreaks, uncover new fashion trends, or find that perfect lifetime partner.

These and plenty more business and research questions are topics you can investigate further to find answers to by mining the available data and building predictive analytics models to guide future decisions.