Reddit reviews Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
We found 22 Reddit comments about Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. Here are the top ones, ranked by their Reddit score.
O'Reilly Media
I've never heard of that book before, but I took a look at their samples and they all seem legitimate.
I would just buy the Ebook for $59 and work through some problems. I'd also maybe purchase some books (or find free PDFs online). Given that you don't have a deep understanding of ML techniques I would suggest these books:
There are others as well, but those are two introductory-level textbooks I am familiar with and often suggested by others.
Data Science = Technical Skills + Stats Skills + Business Expertise. So, for technical skills, start with Python, SQL, and Tableau. For Stats Skills, pick up 2nd, 3rd, and 4th year stats book. For business experience, work on business projects where use Python and Stats skills to solve them.
EDIT:
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking, Storytelling with Data: A Data Visualization Guide for Business Professionals
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython , Python Data Science Handbook: Essential Tools for Working with Data
So, you gotta sharpen up your programming skills.
Godspeed
Yes, this x100. I work with so many large companies, and you've described one of the largest problems I consistently run into.
"It's all in the data -- figure it out"
I often recommend this book: Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
If businesses cannot describe their problem in two sentences, it means they do not understand the problem they are trying to solve.
Well I'd recommend:
For a more basic stats refresh before you dive in, pretty much any introductory textbook will be sufficient. For a very basic but quick and dirty refresh on basic stats you can get: Statistics in Plain English
Are there any good resources for learning more about this?
I have a tech sales background and have an interest in analytics. I picked up this book as a springboard- https://www.amazon.com/Data-Science-Business-Data-Analytic-Thinking/dp/1449361323/ref=nodl_
It sounds like you have the easy part, which is learning the technical skills. The hard part is knowing what questions to ask of the data, it's about identifying the right problems to solve, if that problem can be solved by data, then actually convincing your boss or client of the results.
As quantitative people, we're often too quick to assume that a problem can be solved with a data-driven approach. A good data scientist knows when the data is useful, when it isn't, and what questions to ask. I suggest reading a book called Data Science for Business, it will get you in the right mindset.
If you need to make an argument for the application of a data science tool, I recommend to read Data Science for Business. The book does not focus on R (or any other tool/language), but makes a compelling case for the value of data science, that aims at establishing an understanding for people not concerned with the technicalities of data science.
One of the best not-very-technical books on data science in business is Thinking With Data. It's quirky but gets at the core of what good data science is supposed to be.
Beyond that, Data Science for Business has some great stuff in it, but you would probably want to skip the more technical parts, which might end up being most of the book, depending on your interest in that. Same for Think Like a Data Scientist (apologies for the self-promotion).
Medium.com has some solid articles about data science and various aspects of business, but they are scattered and I haven't yet seen a collection of articles that broadly cover what you're looking for.
“Competing on Analytics” is a classic.
Competing on Analytics: Updated, with a New Introduction: The New Science of Winning https://www.amazon.com/dp/1633693724/ref=cm_sw_r_cp_api_iDdSBbNABWMN6
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking https://www.amazon.com/dp/1449361323/ref=cm_sw_r_cp_api_8EdSBbKH69PFN
You will find it hard to beat "Data Science for Business: What you need to know about data mining and data-analytic thinking". This book is used as a MBA course book at NYU. The book is not full of algorithms, nor does it overload you with complex math. It teaches you how to break common business problems down into fundamental ideas and provides a framework to help you learn the techniques to solve these problems. It's just the right balance of theory and practical knowledge. You will learn about many of the modeling techniques used today with just the right amount of detail. I can't say enough about this book and I'm not the only one. http://www.amazon.com/Data-Science-Business-data-analytic-thinking/dp/1449361323
Take a look at Data Science for Business. It covers a lot of other topics and are more theoretical, but I think it is pretty nice. Let me know what you think
https://www.amazon.com/Data-Science-Business-Data-Analytic-Thinking/dp/1449361323
Hello, I am an undergrad student. I am taking a Data Science course this semester. It's the first time the course has ever been run so it's a bit disorganized but I am very excited about this field and I have learned a lot on my own.I have read 3 Data Science books that are all fantastic and are suited to very different types of classes. I'd like to share my experience and book recommendations with you.
Target - 200 level Business/Marketing or Science departments without a programming/math focus.
Textbook - Data Science for Business https://www.amazon.com/gp/product/1449361323/ref=ya_st_dp_summary
My Comments - This book provides a good overview of Data Science concepts with a focus on business related analysis. There is very little math or programming instruction which makes this ideal for students who would benefit from an understanding of Data Science but do not have math/cs experience.
Pre-Reqs - None.
Target - 200 level Math/Cs or Physics/Engineering departments.
Textbook -Data Mining: Practical Machine Learning Tools and Techniques https://www.amazon.com/gp/aw/d/0123748569/ref=pd_aw_sim_14_3?ie=UTF8&dpID=6122EOEQhOL&dpSrc=sims&preST=_AC_UL100_SR100%2C100_&refRID=YPZ70F6SKHCE7BBFTN3H
My comments: This book is more in depth than my first recommendation. It focuses on math and computer science approaches with machine learning applications. There are many opportunities for projects from this book. The biggest strength is the instruction on the open source workbench Weka. As an instructor you can easily demonstrate data cleaning, analysis, visualization, machine learning, decision trees, and linear regression. The GUI makes it easy for students to jump right into playing with data in a meaningful way. They won't struggle with knowledge gaps in coding and statistics. Weka isn't used in the industry as far as I can tell, it also fails on large data sets. However, for an Intro to Data Science without many pre-reqs this would be my choice.
Pre-Req - Basic Statistics, Computer Science 1 or Computer Applications.
Target - 300/400 level Math/Cs majors
Textbook - Data Science from Scratch: First Principles with Python
http://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/149190142X
My comments: I am infatuated with this book. It delights me. I love math, and am quickly becoming enamored by computer science as well. This is the book I wish we used for my class. It quickly moves through some math and Python review into a thorough but captivating treatment of all things data science. If your goal is to prepare students for careers in Data Science this book is my top pick.
Pre-Reqs - Computer Science 1 and 2 (hopefully using Python as the language), Linear Algebra, Statistics (basic will do, advanced preferred), and Calculus.
Additional suggestions:
Look into using Tableau for visualization. It's free for students, easy to get started with, and a popular tool. I like to use it for casual analysis and pictures for my presentations.
Kaggle is a wonderful resource and you may even be able to have your class participate in projects on this website.
Quantified Self is another great resource. http://quantifiedself.com
One of my assignments that's a semester long project was to collect data I've created and analyze it. I'm using Sleep as Android to track my sleep patterns all semester and will be giving a presentation on the analysis. The Quantified Self website has active forums and a plethora of good ideas on personal data analytics. It's been a really fun and fantastic learning experience so far.
As far as flow? Introduce visualization from the start before wrangling and analysis. Show or share videos of exciting Data Science presentations. Once your students have their curiosity sparked and have played around in Tableau or Weka then start in on the practicalities of really working with the data. To be honest, your example data sets are going to be pretty clean, small, and easy to work with. Wrangling won't really be necessary unless you are teaching advanced Data Science/Big Data techniques. You should focus more on Data Mining. The books I recommended are very easy to cover in a semester, I would suggest that you model your course outline according to the book. Good luck!
https://www.amazon.com/Data-Science-Business-Data-Analytic-Thinking/dp/1449361323
Try this one. It's as good as any
http://amzn.com/1449361323
Read this book, Data Science for Business. It sounds like you don't need to code, but need to be able to converse.
Similar to what /u/Cyzzie said, you are looking for some business intelligence tools. I would start at the beginning and read a book like http://www.amazon.com/Data-Science-Business-data-analytic-thinking/dp/1449361323/ref=sr_1_2?ie=UTF8&qid=1417617015&sr=8-2&keywords=big+data+business+intelligence to get an idea of the concepts behind business intelligence, and then look into tools like Pentaho or Hadoop.
Read this book Its a little deep, but I believe its a good start if you want to get into data science. Also, check out the Tableau and Alteryx tutorial videos.
Big Data: A Revolution that will Transform how We Live, Work, and Think by Mayer-Schonberger and Cukier (https://www.amazon.com/Big-Data-Revolution-Transform-Think/dp/0544227751)
Data Science for Business: What you Need to Know about Data Mining and Data Analytic Thinking by Provost and Fawcett (https://www.amazon.com/Data-Science-Business-Data-Analytic-Thinking/dp/1449361323/ref=pd_bxgy_14_img_3?_encoding=UTF8&psc=1&refRID=XSYTKYEVG8W52XART2BD)
Data and Goliath by Schneier (https://www.amazon.com/Data-Goliath-Battles-Collect-Control/dp/039335217X)
Cathy O'Neill's book is ok. It is worth reading, I thought it could have been better.
Dataclysm is great.
Awesome book
http://www.amazon.com/Data-Science-Business-data-analytic-thinking/dp/1449361323/ref=sr_1_1?ie=UTF8&qid=1416173703&sr=8-1&keywords=big+data+for+business
Im currently a DBA transitioning into a (somewhat) BA role. Its difficult to say what patterns to look for or books to read in regards to that position in the field of healthcare field. But bridging the gap between data and your new role this could be a good start. OH and be prepared to document more than ever have before.
Check out Data Science for Business by Foster Provost & Tom Fawcett
https://www.amazon.com/Data-Science-Business-Data-Analytic-Thinking/dp/1449361323
that's a good last point. I would like that.
yea it was a text-book for example.
But other books such as: https://www.amazon.com/Data-Science-Business-Data-Analytic-Thinking/dp/1449361323 is $18 on kindle.