Learning to Love Data Science, by Mike Barlow
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Learning to Love Data Science, by Mike Barlow
Ebook PDF Learning to Love Data Science, by Mike Barlow
Until recently, many people thought big data was a passing fad. "Data science" was an enigmatic term. Today, big data is taken seriously, and data science is considered downright sexy. With this anthology of reports from award-winning journalist Mike Barlow, you’ll appreciate how data science is fundamentally altering our world, for better and for worse.
Barlow paints a picture of the emerging data space in broad strokes. From new techniques and tools to the use of data for social good, you’ll find out how far data science reaches.
With this anthology, you’ll learn how:
- Analysts can now get results from their data queries in near real time
- Indie manufacturers are blurring the lines between hardware and software
- Companies try to balance their desire for rapid innovation with the need to tighten data security
- Advanced analytics and low-cost sensors are transforming equipment maintenance from a cost center to a profit center
- CIOs have gradually evolved from order takers to business innovators
- New analytics tools let businesses go beyond data analysis and straight to decision-making
Mike Barlow is an award-winning journalist, author, and communications strategy consultant. Since launching his own firm, Cumulus Partners, he has represented major organizations in a number of industries.
Learning to Love Data Science, by Mike Barlow- Amazon Sales Rank: #1074708 in Books
- Published on: 2015-11-19
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .30" w x 6.00" l, .0 pounds
- Binding: Paperback
- 162 pages
About the Author
Mike Barlow is an award-winning journalist, author and communications strategy consultant. Since launching his own firm, Cumulus Partners, he has represented major organizations in numerous industries.
Mike is coauthor of The Executive’s Guide to Enterprise Social Media Strategy (Wiley, 2011) and Partnering with the CIO: The Future of IT Sales Seen Through the Eyes of Key Decision Makers (Wiley, 2007).He is also the writer of many articles, reports, and white papers on marketing strategy, marketing automation, customer intelligence, business performance management, collaborative social networking, cloud computing, and big data analytics.
Over the course of a long career, Mike was a reporter and editor at several respected suburban daily newspapers, including The Journal News and the Stamford Advocate. His feature stories and columns appeared regularly in The Los Angeles Times, Chicago Tribune, Miami Herald, Newsday, and other major US dailies.
Mike is a graduate of Hamilton College. He is a licensed private pilot, an avid reader, and an enthusiastic ice hockey fan. Mike lives in Fairfield, Connecticut, with his wife and two children.
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Most helpful customer reviews
4 of 4 people found the following review helpful. It's a well written book, and probably deserves another star... By William G. Ryan It hurts me to give it 3 stars and I feel obligated to point out that I'm an author myself and a data scientist both of which I suspect color my judgment. As an author, I'd be inclined to give it a 5. It's very well written, well edited and while parts or it seem a little disorganized, he did a very good job writing it.I received a review copy of the book so I am further inclined to cut him some slack b/c I was expecting it to be a little more focused but the 'cobbled together' vibe it has is precisely b/c it's a collection of essays. That's critical to note before buying the book. They're good essays, they're well written, but this isn't something that someone took from concept to product.As a practicing data scientist, I found it frustrating. This field didn't really exist 10 years ago (it's hard to say exactly when it started and people were certainly doing what we know refer to as 'data science' for quite a while, but there weren't job ads or college programs for data science until fairly recently). So if you want to know what data science is and be familiar with the trendy terminology being thrown around in the CIO space these days, this will get you there. It's a bit paradoxical b/c as fast as the field is changing, many things are outdated by the time they're published. On the other hand, books like SuperCrunchers or Natural Language Processing w/ Python are a few years old and still completely relevant.If you're a data scientist I think you'll find this underwhelming or at least dated. If you're a manager or CIO/CTO/CDO trying to decipher the current iteration of buzzword bingo going on around the field, it'll get you there in a quick and easy fashion. The book doesn't purport to make you an expert on the field or teach you the finer points of say, deep learning but it does give you an overview of what the field is all about and what people are doing with it.As soon as I hit the Submit button I'm going to feel guilty for being too harsh on him, there's a lot to like about this book and he clearly did a lot right in terms of writing it, but if you're interested enough in the subject to buy a book on it, you'll probably want something a little more substantive.
2 of 2 people found the following review helpful. Insightful Essays By Tech Journalist On Data Science, IOT, Makers, Infrastructure By Ira Laefsky Insightful and diverse essays by leading tech journalist, Mike Barlow on many important topics connected with Data Science. Not limited to a specific type of analytics, or software applications, or the deprecated term "Big Data"-- This collection of essays touches on the emerging Industrial Internet, the world wide Maker Movement, fading divisions between software and hardware, tools such as Hadoop and Machine Learning, and pervasive issues such as Data Security and Governmental Regulation.Highly recommended, blends the insights of an early participant with the overview of a knowledgeable journalist.
1 of 1 people found the following review helpful. It isn’t a bad book by any stretch of the imagination By Jerry Saperstein I should have read the description of the book more carefully before I ordered it because it isn’t what I thouth it would be. This is a book of essays written over the past several years by Mike Barlow, a journalist. The subtitle declares it a work “Exploring Predictive Analytics, Machine Learning, Digital Manufacturing, and Supply Chain Optimization”. I don’t think it wil be remembered in five years and maybe not even three. It isn’t a bad book by any stretch of the imagination. Rather it addresses a set of subjects where the velocity of change is so great that today’s ideas may be obsolete within months. Given that, Barlow attempts to explain, illustrate and demonstrate what “data science” is. Simply put, “data science” is the contemporary way f viewing the world around us. Not very long ago, people like Elmo Roper, George Gallop and Arthur Nielsen attempted to explain the world to politicians and marketers through interviews expressed as polls. Procor & Gamble examined consumers through counting how many cans ansd boxes moved off the grocery sore shelf. Now every transaction of every kind is memorialized as a statistic somewhere, giving rise to the basis of “big data”. But who will analyze and interpret it? How will they do it? Why should they do it? It’s a book of generalities and a pretty decent introduction to big data and data science. In many cases, what the author puts forth are ruinations as opposed to hard science, providing grist for discussion if you can actually find someone else interested in this subject. Barlow covers a lot of territory and, remember, this is a collection of essays, so sometimes interesting points are raised and simply disappear forever in succeeding sections. But Barlow writes well, obviously has an enquiring mind and asks a lot of questions which, one way or another, he answers. As an introduction to “big data” and “data science”, this is an entertaining and informative book. It will not make you an expert, but it wil help you recognize one.Jerry
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