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Are you drowning in a sea of data? Would you like to take control of your data and analysis to quickly answer your business questions and make critical decisions? Do you want to confidently present results and solutions to managers, colleagues, clients and the public?
If so, you are an Accidental Analyst! Although you didn't plan for a career as a data analyst, you're now in a position where you have to analyze data to be successful. Whether you've been working with data for a few years or are just getting started, you can learn how to analyze your data to find answers to real-world questions. Even if you're an expert, you'll find creative ideas on how to work with accidental analysts. Using illustrated examples, we'll walk you through a clear, step-by-step framework that we call The Seven C's of Data Analysis.
Read this book for inspiration, ideas and confidence to begin tackling the problems you face at work. Keep it by your desk as a reference on how to organize, analyze and display your data using best practices of visual analytics. Don't worry, you can continue to use your favorite spreadsheet or data analysis software—this information is not tied to any particular application. Throughout the book, we also include tips, tricks, and shortcuts that took years of analyzing data to discover and understand!
This book is valuable for users of Microsoft Excel, Microsoft Access, Business Objects, Cognos, JMP, Microstrategy, Panopticon Software, QlikView, R, SAS, SPSS, Tableau Software or Tibco Spotfire.
Please visit us at www.AccidentalAnalyst.com for articles, our free newsletter and upcoming events.
"This is a wonderful book, filled with practical advice.
... a great resource for building analytical prowess."
Stephen Few
Best-selling author of "Show Me the Numbers" and "Now You See It"
"Finally, a book that clearly explains the fundamentals of business analytics!"
Tim Latendress
Financial Analyst
"This book is an amazing resource for regular business people."
Diego Saenz
President, Petplace and former CIO of Pepsi Latin America
In his talk at the 2012 Tableau Conference, Pat Hanrahan, PhD,
explained that the book changed how he thinks about analytics and
inspired him to develop a new approach to teaching.
Professor at Stanford University
Co-founder of Tableau and Pixar
Two Academy Awards
Eileen McDaniel, PhD
Co-Founder and Managing Partner of Freakalytics, specializing in educational materials and analytical training with the goal of empowering people to get the most out of their data and take decisive action in their daily work. Her unique experience in science and business inspired her to adapt the scientific method for business, resulting in the Seven C's framework. She also is co-author of Rapid Graphs with Tableau and the Rapid Dashboards Reference Card and App.
Stephen McDaniel
Co-Founder and Principal Data Scientist of Freakalytics. He has over 25 years of experience as a statistician, analyst, data architect, instructor, data miner and software innovator. He has been a faculty member at The Data Warehouse Institute (TDWI) and at The American Marketing Association. He is lead author of SAS for Dummies and has worked with over 100 organizations including Netflix, SAS, Tableau, UC-Berkeley, Duke and the US Navy.
- Sales Rank: #771788 in Books
- Brand: Brand: CreateSpace Independent Publishing Platform
- Published on: 2012-05-08
- Original language: English
- Number of items: 1
- Dimensions: 10.00" h x .68" w x 8.00" l, 1.33 pounds
- Binding: Paperback
- 300 pages
- Used Book in Good Condition
About the Author
Eileen McDaniel is Co-Founder and Managing Partner of Freakalytics, LLC, specializing in educational materials and analytical training that empower people to get the most out of their data and take decisive action to solve problems in their daily work. She leads the development of training manuals and other publications, consults on short-term marketing research projects, and prepares and presents sessions given at both public conferences and internal company workshops. As a scientific researcher with a PhD in Ecology, she won multiple awards for excellence in both research and teaching, including one on Capitol Hill from the U.S. Congress. She designed and implemented studies in which she collected and analyzed data from disparate sources to offer novel approaches to resource management. Her research experience evolved into an interest in green or eco-marketing analytics and completion of an MBA Certificate in Marketing Analytics. She is co-author of “Rapid Graphs with Tableau Software 7”, and the “Rapid Dashboards Reference Card and App”. Eileen’s unique expertise in science and business led her to realize that although scientists have a formal, step-by-step method to collect and analyze their data, business analysts lack a similar plan. This realization inspired the framework for data analysis used in “The Accidental Analyst”. Stephen McDaniel is Co-Founder and Principal Analyst of Freakalytics, LLC. He has over 20 years of experience as a statistician, analyst, data architect, instructor, data miner, consultant, software innovator and author. He has been a faculty member at The Data Warehouse Institute (TDWI) and with the American Marketing Association (AMA) and has led data warehousing, business intelligence and advanced analytic teams at Tableau Software, SAS Institute, Brio Technology, Glaxo, TAP, Netflix and Loudcloud. Stephen is lead author of multiple versions of “SAS for Dummies”, “Rapid Graphs with Tableau Software 7”, and the “Rapid Dashboards Reference Card and App”. At Freakalytics, he was the founder of Tableau’s worldwide training program with Eileen, providing public and onsite hands-on analytic training. He has worked with and been an invited instructor at many leading organizations including Target, State Farm, Eli Lilly, IMS Health, Boeing, American Express, Oracle, Intellectual Property Australia, Duke University, Fidelity Investments, US Navy CyberDefense, Brown University and The US Department of the Treasury.
Most helpful customer reviews
7 of 8 people found the following review helpful.
Great Resource for anyone without formal training in Statistics or Analyst
By Thirsty in Seattle
The Accidental Analysis is a great book for anyone who has a block of data and needs to make conclusions from it. The focus of the book is on Visual Analysis which is the act of building visuals from data to solve problems and identifying actions. The example in the book focuses on business intelligence and sales in particular, but the framework they lay out can be used by anyone doing any type of analysis with numbers.
The book is an excellent resource for anyone who finds themselves doing analysis without any formal training or experience in analytic or statistics. I was a humanities major in college, now working in the business world, and found the book to be very easy to understand. The focus is on practical applications and real world situations. You don't need to know anything about statistics or data management to use the book, though if you do, I think you'd still likely get a lot out of the book.
Instead of talking about equations, they lay out a basic 7 step framework that is very easy to understand. The first part of the book walks you through forming questions to guide your analysis, and the practical aspects of collecting data, correcting problems in the data, and joining multiple data sources together. The second part of the book focuses on the analysis of the data. Particularly how to chart the data, analyze what's going on, and communicate the results. If you are a fan of Stephen Few or Edward Tufte's work you will appreciate the advice given in the second part of the book. Additionally the book is filled with lots of tips, tricks, and best practices.
The book is laid out very well and you always know where in the process you are through the tabs printed on every page. As they teach the steps they walk through a hypothetical situation from start to finish using a Pet Store's sales data that builds throughout the book. This allows you to see the steps in practice. They use Tableau to build the visuals in the book so this makes it a great resource if you're wanting to go beyond the authors' other book Rapid Graphs with Tableau, which focuses on learning the software. But the book is written in such a way as it stands alone from any particular BI software and could easily be used with Excel, Access, Business Objects, Cognos, JMP, Micorstratgy, QlikView, R, SAS, SPSS, or Tibco Spotfire.
0 of 0 people found the following review helpful.
Great Read
By Margaret Wheelhouse
Bought for work
2 of 3 people found the following review helpful.
A different look than my stat & CS training
By Design with Data SF
I have really enjoyed this book and found it grew on me as I read it. I think it is an excellent way to think about and even rethink analytics in the real-world. What's most interesting is that some of it is obvious after a year or two of analysis but much of it is not, until you have read it and then you think, of course we should show ROI or percentiles or year over year growth on the same graph!
This book is loosely structured around the scientific method but reshaped for addressing business analytics with a decidedly visual bent. They have converted the scientific method to the 7 C's of analysis and have great examples throughout the process. The 7 C's are: Choose questions, Collect data, Check data, Clean data, Chart the data, Customize the analyses and Collaborate the results. I found their tabs on every page (a pictogram of where you are in the 7 C’s) of the book a great way to quickly orient yourself as to which C you are in and what stage of the analytic process you are working in.
This book is black and white, which I enjoyed more than I expected since the examples are beautifully illustrated, even without color. In fact, the examples have me rethinking my tendency toward excessive color, which I see may impede my point. Finally, there is great advice for those of us who would rather stay at our desk and program- get out there and ask more questions of the business “owners”, making certain these conversations shape your approach to the analysis and especially how you present your results. I have found this advice quite useful in my work already!
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