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Howard Friedman posted blog posts
yesterday
Howard Friedman posted a blog post

Data Science: Lifecycle approach to data-driven value creation

Data science had broad applications across many different industries. If we focus on industries that are in the business of buying (some or all) of a company, then trying to improve the operations before selling then we can identify at least three critical stages for data science to play a significant role.Early Exploration: Mining databases for trend and customer insightsEnhanced Pre-acquisition Analysis: Linking early exploration insights with company data. Testing growth, customer value and…See More
May 31
Howard Friedman's blog post was featured

Data Science: Lifecycle approach to data-driven value creation

Data science had broad applications across many different industries. If we focus on industries that are in the business of buying (some or all) of a company, then trying to improve the operations before selling then we can identify at least three critical stages for data science to play a significant role.Early Exploration: Mining databases for trend and customer insightsEnhanced Pre-acquisition Analysis: Linking early exploration insights with company data. Testing growth, customer value and…See More
May 31
Howard Friedman posted a blog post

6 Reasons for Investing Some Time to Learn Tableau

I have seen a few mentions of Tableau in my feed and wanted to offer some thoughts on why I strongly suggest data scientists investing a few hours to learn the basics of Tableau.(1)   Tableau is widely used. Many people that have reporting functions rely on Tableau so knowing the basics is helpful to your business and clients.(2)   Tableau is great for quick data visualizations and for generating some insights into the data and variable relationships.(3)   Tableau as Extract, Transform and…See More
Apr 17
Howard Friedman posted a blog post

10 things to consider when purchasing business intelligence software

Background: Business intelligence software casts a wide net. Software for site selection, customer segmentation, marketing tests, employee productivity, operational metrics, sentiment analysis, profitability sectors and mapping tools all fall in this category. Businesses are constantly challenged with business intelligence software questions such as:·      Should we “Build or Buy”?·      Should we “Retain, Upgrade, or Replace” software?·      What value are we getting from the…See More
Mar 7
Howard Friedman's blog post was featured

10 things to consider when purchasing business intelligence software

Background: Business intelligence software casts a wide net. Software for site selection, customer segmentation, marketing tests, employee productivity, operational metrics, sentiment analysis, profitability sectors and mapping tools all fall in this category. Businesses are constantly challenged with business intelligence software questions such as:·      Should we “Build or Buy”?·      Should we “Retain, Upgrade, or Replace” software?·      What value are we getting from the…See More
Mar 7
Howard Friedman posted a blog post

Adding Program Evaluation to the Data Science Curriculum

We tried to do XYZ. Did it make a difference?”Whether you are in the for-profit world or the not-for profit world, this is a very basic question that many people try to answer.  You could be working at a bank trying to figure out which offer is most appealing to customers, at an online retailer figuring out which ad display gets the most clicks, at the Department of Education trying to test the effect of smaller class sizes, at the city government office trying to see if the new bike lane…See More
Feb 20
Howard Friedman's blog post was featured

Adding Program Evaluation to the Data Science Curriculum

We tried to do XYZ. Did it make a difference?”Whether you are in the for-profit world or the not-for profit world, this is a very basic question that many people try to answer.  You could be working at a bank trying to figure out which offer is most appealing to customers, at an online retailer figuring out which ad display gets the most clicks, at the Department of Education trying to test the effect of smaller class sizes, at the city government office trying to see if the new bike lane…See More
Feb 20

Profile Information

Short Bio
Statistician, health economist and writer at the United Nations Population Fund (UNFPA) and Columbia University. Developer of SAS Business Knowledge Series Courses, former Director of Data Modeling in Banking, consultant for health industry.
My Web Site Or LinkedIn Profile
http://howard-friedman.com
Professional Status
Professor
Years of Experience:
15+
How did you find out about DataScienceCentral?
Twitter
Interests:
Networking, New venture, Other

Howard Friedman's Blog

Developing a Logic Model for Program Evaluation

Posted on June 20, 2018 at 11:53am 0 Comments

Before implementing a program, I like to first develop a logic model.  

This can be a fast exercise that can lead to insights into the strengths and weaknesses of the program design.  There are many different models used and I prefer a simple one with 4 basic parts:

1. Inputs—resources that go into a program including staff, materials, money, equipment, facilities,…

Continue

Program Evaluation: 8 Steps

Posted on June 20, 2018 at 3:02am 0 Comments

In business, we often implement programs and then try to determine if the program had an impact. This is an example of program evaluation where, more generally, program evaluation is a study conducted with the intent of determining how effective a given intervention (program) is at achieving a specific outcome.

What types of programs? That could be a cross-sell program, customer retention program, new advertising method etc.

Is this just A/ B testing? A/B testing is a great…

Continue

Data Science: Lifecycle approach to data-driven value creation

Posted on May 29, 2018 at 9:00am 0 Comments

Data science had broad applications across many different industries. 

If we focus on industries that are in the business of buying (some or all) of a company, then trying to improve the operations before selling then we can identify at least three critical stages for data science to play a significant role.

  1. Early Exploration: Mining databases for trend and customer insights
  2. Enhanced Pre-acquisition Analysis: Linking early exploration…
Continue

6 Reasons for Investing Some Time to Learn Tableau

Posted on April 17, 2018 at 9:23am 0 Comments

I have seen a few mentions of Tableau in my feed and wanted to offer some thoughts on why I strongly suggest data scientists investing a few hours to learn the basics of Tableau.

(1)   Tableau is widely used. Many people that have reporting functions rely on Tableau so knowing the basics is helpful to your business and clients.

(2)   Tableau is great for quick data visualizations and for generating some…

Continue

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