We will do our best to check back every week and supply answers to any questions about analytics.
Adrian Tennant
6/7/2013 09:22:47 pm

I am around half-way through the book right now, and notice that you pepper the text with references to companies and publications.

Would it be possible for you to collate these resources on one page of this website, with links where available?

Adrian

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Jinho
6/9/2013 11:58:30 am

Thanks for your suggestion. I'll figure out what I can do. Tom might have a good idea how to do it.

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Adrian Tennant
6/7/2013 09:25:05 pm

Are the illustrations in the book available online in color? They're fun! They could make great posters for a collaborative space in our office.

Adrian

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Adrian Tennant
6/7/2013 09:25:14 pm

Are the illustrations in the book available online in color? They're fun! They could make great posters for a collaborative space in our office.

Adrian

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Jinho
6/9/2013 12:02:42 pm

Let me check with the HBR Press.
Probably they have the original illustrstions in color.
I wonder whether they'll provide them on line.

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Kevin Knights
6/24/2013 10:45:25 am

I am interested in formal study in Analytics. Can you suggest a few reputable programs I might consider in terms of becoming a qualified Data Analyst and possibly more specifically a Competitive-Intelligence Analyst?

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Jinho
6/25/2013 07:06:20 pm

Please take a look at pages 164-166 of our book. Some programs for MSA(Master of Science in Analytics) are introduced there.

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Kevin Knights
6/25/2013 10:46:44 pm

Thank you very much Jinho. I'll have a look.

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Nancy Martinez
8/13/2013 01:30:12 am

I am working on a data cleansing project and must provide some meaningful metrics to leadership. They are not impressed with "we captured 28% of records with null in DOB field" type metrics. I am at a loss what to provide as meaningful metrics.

Your book helped but a couple examples specific to my dilemma would be appreciated!
Thanks.

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Jinho
8/13/2013 06:06:42 am

Can you be more specific? What is your data cleansing project? Data stucture? Purpose of cleansing, etc.

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Nancy Martinez
8/13/2013 11:57:23 pm

Replacing existing OWB with ODI tool to provide business rules at front end rather than back end.

Taking data sources from web portal, FoxPro and SQL server and running all through ODI - Staging Table - into DW

Reverse engineering data in FoxPro, providing XML data to run through ODI

Replacing multiple views in DW with a mega view of combined data domains

There are great anecdotal stories to tell, but metrics are challenging for me to determine.

Nancy Martinez
8/13/2013 11:57:47 pm

Replacing existing OWB with ODI tool to provide business rules at front end rather than back end.

Taking data sources from web portal, FoxPro and SQL server and running all through ODI - Staging Table - into DW

Reverse engineering data in FoxPro, providing XML data to run through ODI

Replacing multiple views in DW with a mega view of combined data domains

Nancy Martinez
8/13/2013 11:59:39 pm

Replacing existing OWB with ODI tool to provide business rules at front end rather than back end.
Taking data sources from web portal, FoxPro and SQL server and running all through ODI - Staging Table - into DW

nancy martinez
8/14/2013 12:00:14 am

Reverse engineering data in FoxPro, providing XML data to run through ODI

Replacing multiple views in DW with a mega view of combined data domains

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Vikas Mehra
9/1/2013 03:04:10 pm

Wondering, in the data analysis methods tab, whether the second table on multivariate analysis is complete! Please clarify.

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Jinho
9/2/2013 11:57:18 pm

Only two examples are included in the text. Wine equation for a multiple regressiom and Go case for a logistic regression.

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Vikas Mehra
9/5/2013 02:11:40 pm

Thank you Jinho for the clarification. Best regards!

10/1/2013 04:50:44 pm

They, too, were able to get to know each other more, have a bonding, and enlighten themselves to their importance in the organization.

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Eileen Yordan
10/27/2013 09:18:27 pm

Congratulations on your new book.

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Jinho
10/28/2013 01:13:51 pm

Dear Eileen,
Lont time no see. How's Col. Yordan? And your sun? He must have grown up a lot. My email is [email protected]. Please let me know yours. I was looking for youe email address.

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Elliot weiss
5/19/2014 04:24:55 am

Jinho, where can I find copies of 100 common senses in statistics & freak statistics? Are they available in the US?

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Patricia Partida
4/26/2015 07:30:31 am

Im working with a project for a master degree; I learn a lot of your books for my was very useful .

Thanks !!

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Pant
5/6/2015 01:15:55 am

Is there a way to post the "10 questions to ask" and have it available on the Internet? It's a very handy list to have printed out!

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Bob Bryant
8/21/2015 11:57:20 am

I am currently doing my dissertation in the field of predictive analytics of big data. My research topic focuses on retention and learning analytics as it relates to the big MOOC data from Coursera and MITx. Can you lead me to some good resources that would inform the theory related to predictive analytics applied to personalized learning that shows correlation to retention?

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Karen
2/16/2017 02:55:09 pm

Where can I find a copy of "100 Common Senses in Statistics and Freak Statistics"? I haven't been able to locate a copy.
Thank you

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Martin Lavoie
5/15/2017 08:33:49 am

One of the top challenges I face in my work (analytics) is with management buy-in as well as employee adoption. I'm looking for recommendations (sites, books, advice) in terms of org. change management to adopt analytics. Ranging from maturity assessment (readiness), driving a fact based decision culture etc. Thanks.

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10/19/2017 11:56:54 am

Hello Jinho & Tom! Just started listening to Keeping Up ...Quants audiobook (plus I've purchased but haven't yet rec'd paperback). Here are 3 questions right off the bat. 1. What's the difference bwtn a machine learning algorithm and a "non-machine learning" algo?
#2. Are all Hidden Markov model algorithms machine learning algos? # 3. Are all Naïve Bayesian algos machine learners? Eager to hear your replies and I'm enjoying your book! Thanks, Rick

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T Mi
1/2/2018 04:17:13 pm

Hi,

I am reading your book. It' s really interesting.

I have a question regarding the calculation of prediction intervals in forecasting when we don't have access to SAS or minitab tools. I found the formula for calculating prediction intervals in the case of simple linear regression. Do you have any reference we can look into to calculate prediction intervals for different forecasting methods (multiple linear regression, moving average, exponentiel smoothing, time-series decomposition).

Thank you.

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Michael
1/10/2018 09:46:48 pm

In Chapter 2 you list the six analytical stories. I dont understand their placement within the problem recognition. Could you explain further how they connect to the problem recognition?

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shane moynihan
1/9/2019 02:06:59 am

Hi Thomas, I am working on a capstone project this quarter before checking out of a JWMI (Jack Welch) EMBA program and would appreciate your support on biz analytics. I am currently reading your book (well written btw) and executing a final project in parallel where I have chosen to frame the challenges facing Apply at the moment with decreasing iPhone sales and their next course of action to sustain shareholder value. Framing the challenge, i.e. decreasing iPhone sales which will have an knockoff effect on revenues going forward, seems straight forward, but your support on determining which items of data to use over and above, qtr on qtr unit sales, rev (both by geography) would be greatly appreciated. I'm thinking market share might be another, along with avg unit sales price and margin but what others might I look at that are retrievable from public forums/publications that helps both frame and analyse the challenge at hand?
Many thanks in advance
Shane

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Messay Zerga
6/5/2019 01:09:52 pm

I'm currently a graduate students at University of Maryland University College in Data Analytics. I'm reading this book and loving it. The analytics concept you have introduced in the book and simple but powerful. Frame the problem, Solve It and Communicate well! I hope to study at HARVARD once I finish my current program. you guys are amazing!

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    Authors

    Thomas H. Davenport is a visiting professor at Harvard Business School, the President’s Distinguished Professor of IT and Management at Babson College, and a research fellow at the MIT Center for Digital Business. He is also a senior advisor to Deloitte Analytics and the cofounder and research director of the International Institute for Analytics. Davenport is the coauthor of Competing on Analytics and Analytics at Work. This is the seventeenth book he has authored, coauthored, or edited.

    Jinho Kim is a professor of business and statistics at the Korea National Defense University and the research director of the KNDU Lab for Analytics Research. He holds a PhD from the Wharton School and is the author of six books published in Korea, including the bestselling 100 Common Senses in Statistics and Freak Statistics. He has developed and run an educational program for building individuals’ analytical skills. His current research focuses on the use of analytical methods to address various issues in business and society.

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