Practical Analytics

[NitinKale]

Hi Everyone,

I just wanted to post a quick note to inform you all that we’ve begun writing on the Practical Analytics book.  My co-author, nancy.jones, and I are trying to create a resource that covers all of the key general analytics concepts and illustrates the hands-on application of those concepts using the most popular SAP Analytics technologies.  We intend to make the book appropriate for both university classroom use and professional readers who are new to the topic.  We will have the book ready in Spring 2015.

Here’s the overview: 

Practical Analytics covers analytics concepts and activities in a way that provides real-world skill building while reinforcing fundamental concepts. This book provides a much-needed approach to analytics through theory, applications, and hands-on experience using the leading industry tools from SAP. Although many books have been written on statistical data analysis, data mining, predictive analytics and business intelligence, these books are often too technical or theoretical for a business user. The goal of this book is to provide a comprehensive and self-contained overview of analytics for students and practitioners. The reader will be able to learn and apply all the concepts in the book without excessive prerequisite courses or experience.  The table of contents is available here for more details on the concepts that will be covered.

For updates on the book as we progress or to get early access to chapters for review, please sign up for the mailing list and we’ll keep you in the loop.

Nitin Kale

Table of Contents

Section 1 - Basics	6.      Reporting
1.      Introduction to data analytics	6.1.    Where   are reports used?
1.1.    What   is Analytics?	6.2.      Authoring reports
1.2.    Why   study analytics?	Section 4 - Data Visualization
1.3.    Who   and how they benefit? Some examples	7.      Charts   and Dashboards
1.4.      Analytics methodology	7.1.      Charting techniques to display large datasets
1.5.      Roadmap of topics (chapters)	8.      Advanced visualization
1.6.   Introduction to model company – Global Bike   Inc.	8.1.       Effective visual techniques
Section 2 - Data Provisioning	8.2.       Advanced chart types
2.      Data acquisition	Section 5 – Knowledge discovery, prediction &   decision making
2.1.    Source   systems. Examples and opportunities	9.      Data mining
2.2.    Data   Collection	9.1.    What   is data mining?
2.3.    Data   representation for structured and unstructured data	9.2.    Why is   it needed?
2.4.    Data   storage	9.3.   Predictive vs. descriptive analytics
3.      Data harmonization	9.4.      Supervised vs. unsupervised models
3.1.      Mapping and consolidating data from multiple sources	9.5.    Data   mining process
3.2.      Separating signal from noise	10.   Descriptive models for data mining
3.3.    Dirty   data handling and cleansing	10.1.    Unsupervised models
4.      Data staging	10.2.  Model   verification and validation
4.1.      Transactional systems vs. informational systems	11.   Predictive models for data mining
4.2.      Normalized vs. denormalized models	11.1.    Supervised modeling
4.3.    Data   warehouses	11.2.  Model   verification and validation
4.4.      Multidimensional modeling- star schema	11.3.  Data   mining models for predictive analysis
4.5.      Multidimensional modeling - snowflake schema	12.   Big data analytics
4.6.      Modeling cubes using snowflake schemas	12.1.  What is   big data?
4.7.    Cube   optimization	12.2.    Structured vs. unstructured data
4.8.    ETL –   Extraction, transformation, loading	12.3.    Developments in big data technology
Section 3 - Reporting and analysis	12.4.  Case   studies in big data analytics
5.      Slicing and dicing	13.   Decision making
5.1.    What   is slicing and dicing?	13.1.  From   data to insight to decisions to actions
5.2.      Spreadsheets and pivot tables	13.2.    Responsibilities for the analyst
5.3.      Slicing and dicing	13.3.  Using a   combination of analytical tools
5.4.      Consumers to CEOs, everyone slices and dices	13.4.  Expert   Systems
5.5.    Tools   used for slicing and dicing (using MS Excel)	13.5.    Evaluating analytical process in terms of outcomes
5.6.      Multidimensional analysis

[Former Member]

very good, adding the book to my wish list.

[wisthrop]

Is this going to be available on Amazon for ordering or only directly from the publisher? Also, is it in print or only the eBook?

[NitinKale]

Jared,

It is available only through the publisher's website - http://epistemypress.com/books/practical-analytics/. And it is only available as an ebook.

[Former Member]

Very interested in adopting this book but it appears from the instructions that it requires a Windows-based machine for the instructor and students. I am assuming that since all of the instructions are for that. Can you confirm/deny? The issue is that lots of my students have Macs (as do I) and I don't want to force them to do a dual boot. Help?

[NitinKale]

Gregory,

We provide instructions for professors and lab managers on software installation for Windows machines. The client side apps are Windows only. What we suggest is to either set up your lab with the software or set up a remote desktop environment that students can connect to. The second option has worked successfully at my University for years.

[NitinKale]

Also, Thank you for considering the book for adoption. Feel free to contact me if you need any help or have questions about the books or supplemental materials.