Blog Header 1.jpg

Blog

Sort by Topic

Analytics Best Practices – Agile Data Science

Anna Godwin

September 15, 2017

BLOG_Analytics-Best-Practices-Part-1.jpg

This is the second in a series of blogs where Data Scientists Anna Godwin and Cory Everington discuss five Analytics Best Practices that are key to building a data-driven culture and delivering value from analytics. In this installment Anna discusses the benefits of using Agile Data Science as a framework for managing data science projects. 

Read More »

Top 3 Keys to Leading a Successful Data Analytics Initiative

Gerhard Pilcher

September 8, 2017

BLOG_Top 3 Keys to Leading Data Analytics Initiative.jpg

Data analytics has been called the most powerful decision-making tool of the 21st century. Even though it has come of age only within the past twenty years, thousands of businesses, governmental agencies, and nonprofit organizations have already used it to dramatically increase productivity, reduce waste and fraud, enhance quality, improve customer service, boost revenues, optimize strategies, combat crime and terrorism, and solve a host of other tough challenges. Elder Research, CEO, Gerhard Pilcher, and Vice President of Operations, Jeff Deal, coauthored Mining Your Own Business to provide an easy-to-read overview of data mining and predictive analytics for organizational leaders who want to know more about these powerful tools and develop an analytic capability in their organization.

This blog, drawing from chapter 3 of this book, reviews the three most important keys to leading a successful data science initiative.

Read More »

Building an Effective Data Science Team

Miriam Friedel

September 1, 2017

BLOG_Building-An-Effective-Data-Science-Team.jpg

There are no unicorns.

Often when people think of data scientists, they imagine a mythical person who knows how to do everything required for success:  write sophisticated Python libraries, derive cutting edge machine learning algorithms using a deep understanding of statistics, shepherd successful models through deployment, administrate the database, create elegant visual dashboards, deeply understand the business, and drive corporate strategy. The required skills listed on many job postings for Data Scientists is long, overwhelming, and in many cases, completely out of reach for a single person.

Read More »

It is a Mistake to Accept Leaks from the Future

John Elder, Ph.D.

August 25, 2017

BLOG_Avoid-Leaks-From-The-Future-21.jpgIn his Top 10 Data Mining Mistakes John Elder shares lessons learned from more than 20 years of data science consulting experience. Avoiding these mistakes are cornerstones to any successful analytics project. In this blog about Mistake #5 you will learn how easy it is to accept leaks from the future in your modeling results and the importance of scrutinizing any input variable that works too well.

Read More »

Analytics Best Practices – Part 1

Cory Everington

August 18, 2017

BLOG_Analytics-Best-Practices-Part-1.jpgThis is the first in a series of blogs where Data Scientists Cory Everington and Anna Godwin discuss five Analytics Best Practices that are key to building a data-driven culture and delivering value from analytics. In this installment Cory discusses the benefits of having a shared framework of Analytics Best Practices to allow you to focus on what's most important—the results.

Read More »

It is a Mistake to Listen Only to the Data

John Elder, Ph.D.

August 11, 2017

BLOG_Mistake-to-listen-only-to-the-data.jpgIn his Top 10 Data Mining Mistakes John Elder shares lessons learned from more than 20 years of data science consulting experience. Avoiding these mistakes are cornerstones to any successful analytics project. In this blog about Mistake #4 you will learn that inducing models from data has the virtue of looking at the data afresh, not constrained by old hypotheses. But, while “letting the data speak”, you must be careful not to tune out received wisdom, because often, nothing inside the data will protect one from significant, but wrong, conclusions.

Read More »

Predicting Gratefulness: Machine Learning for Human Behavior

Will Goodrum

August 4, 2017

BLOG_grateful-giving-predicting-human-behavior.jpgMachine learning has many strengths. Predictive models can synthesize information from millions of disparate cases and identify patterns that would otherwise pass undetected. These patterns lead to inferred insights from the data that can surpass human judgment. The potential value from predicting human behaviors before they happen is exciting to businesses and government agencies. Imagine having the foresight to know which of your customers are likely to churn, which of your providers have a high likelihood of making fraudulent claims, or which of your patients are grateful enough to donate to your hospital foundation?

Read More »

Predictive Analytics Basics: Six Introductory Terms & The Five Effects

Eric Siegel

July 28, 2017

BLOG_Predictive-Analytics-Basics.jpgRenowned author and founder of the Predictive Analytics World conference series Eric Siegel shares six key definitions—and The Five Effects of Prediction—from his book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die.

Read More »

Statistical & Cognitive Biases in Data Science: What is Bias?

Will Goodrum

July 21, 2017

BLOG_What-is-bias.jpgThis is the first in a series of short blog posts where we explore common varieties of bias that can beset analytics projects. Bias has serious ramifications for the success of analytics in any organization. Understanding the nature of bias is crucial for understanding the extent of a model’s accuracy. In this first post, we discuss what bias is, why it occurs, and why it matters (a lot).

Read More »

Transforming Business: Why Do We Stop Asking Why?

Bryan Jones

July 14, 2017

BLOG_Why-stop-asking-why.jpg

I’ve lived through this phenomenon first hand. The environment was new to me, sitting at my assigned seat at the cherry wood conference table for the weekly executive staff meeting. I was told very clearly that I was to stick to the presentation, answer only when asked a direct question, and never, no matter what happens, ask why! After being ushered out of the meeting when I finished, we quickly huddled for a post-meeting debrief. Everyone started asking “How do you think it went?” “What do you think he meant when he said this?” and “Did you understand what he asked us to do?” I finally asked, “Why didn’t we just ask him?”

Read More »