The book is an argument for the use of Big Data in firms of all sizes. I selected this book for this week’s column because I have heard the term ‘Big Data’ misused often of late. It is most frequently confused with doing a little more research than the competitors, or applying data to decisions made previously on little more than gut feel.
This book explains why Big Data is a big deal.
Car insurance rates, for almost all the industries 80 year history, have had remarkably little to do with whether one is a competent and careful driver. All young drivers pay higher premiums even if young Joey rarely drives above the speed limit, always obeys traffic signals, and never had so much as an accident on his bicycle.
There is a reason most car insurance companies based their rates on relatively simple variables. Three of the biggest American companies started up on the 1930s. Eighty years ago, those primitive models represented the best that car insurance companies could do. Rates are no longer based on a small, primitive set of independent variables. Insurance companies are implementing more contemporary, accurate, dynamic, and data-driven pricing models. This is a direct result of advances in GPS, mapping, mobile technologies, and telemetry. The result is revolutionizing car insurance.
It is now possible to track which drivers routinely exceed the speed limit and ride through red lights. We can ascertain which drivers routinely drive dangerously slowly. Who is driving less cautiously despite never being fined? Who obeyed traffic signals in the past, but does not anymore? Which drivers text while driving, a practice considerably more dangerous than driving drunk. Does a man with two cars (a sports car and a station wagon) drive each differently?
For data-challenged companies, accurately answering pertinent questions like these is extremely difficult.
If you are puzzled as to how Big Data differs from the ubiquitous ERP and CRM programmes already found in most companies, the answer lies in the types of data involved. ERP and CRM systems handle structured data, but it is unstructured data that represents most of what we call ‘Big Data.’ For any organization, structured data now only tells part of the story. Unstructured information accounts for more than 80% of all data in organizations. By some estimates, it is growing ten to fifty times faster than its structured counterpart is.
Unstructured data has always existed, but we never thought of it as “data.” Much of this unstructured data is digitized and available nearly instantly. Most data is born digital.
Author Phil Simon is a fan of the Canadian band, Rush. He attends a concert and takes photos of the band in action. After the concert, he add his pictures, collection of digital data, to an online album of Rush photos and titles it “Rush 2012” and puts it on the web to be viewed by other Rush fans.
If someone wanted to see only recent pictures of the band’s drummer Neil Peart, and not the concert, he would have to trawl through the collection. To avoid this, Simon tags the photos with various descriptors to make searching easier. He uses a dedicated picture site that does some of the tagging automatically. With a face-recognition facility the album software can identify each member of the band. The single picture yields multiple pieces of data.
A fan searching for the drummer can search across the pictures of thousands of Rush fans.
Now consider Walmart, the world’s largest retailer. In September 2011, it was logging one million customer transactions per hour and fed information into databases estimated at 2.5 petabytes in size. Add to this books, newspapers, and magazines —all examples of unstructured data. Then throw in the 48 hours of video uploaded to YouTube every minute.
All this Big Data can be enormously valuable in answering mission critical question. What products would our customers consider buying? When is the best time of the year to launch a new product? What are people saying about our latest commercial or brand? How do we sell more products?
Centuries-old winemakers like Gallo have been able to launching new varietals based on advanced analytics and data culled from social networks. HR departments are turning to Big Data to solve a long-vexing problem: how to hire better employees and retain them.
Google has been able to predict local flu outbreaks with accurately based on thousands of user search queries.
There is no mass market anymore. There is an overwhelming choice in everything from TV stations, to music, to clothing. Using Big Data companies are able to target precise audiences and tight, key demographics. The consulting firm McKinsey has called Big Data “the next frontier for innovation, competition, and productivity.”
The successful use of Big Data is impacting on medical research and drug discovery. UPS regularly mines truck delivery data to optimize new routing methods and reduce expenses. Even pizza shops in America are using Big Data.
Now, businesses of any size can, and must, start exploiting Big Data. As Edwards Deming once said, “In God we trust, all others must bring data.”
Readability Light ---+- Serious
Insights High -+--- Low
Practical High --+-- Low
Ian Mann of Gateways consults internationally on leadership and strategy
ISBN-13:
978-1118638170
ISBN-10:
1118638174
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Customer reviews
Top reviews from other countries
Subra Velu
Must have book for Big Data introduction
Reviewed in India on October 2, 2015Verified Purchase
Src
There are better books available
Reviewed in India on June 2, 2018Verified Purchase
tarun kandwal
Average book
Reviewed in India on December 5, 2015Verified Purchase
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