Services

Data & Analytics strategy


For leaders looking to craft a strategic data and analytics roadmap.

Learn More
Data & Analytics strategy

data science consulting


For organizations looking to solve complex business challenges with data science.

Learn More
data science consulting

Analytics Capability Development & Training


For organizations looking to train and empower their analytics workforce.

Learn More
Analytics Capability Development & Training

Enterprise & Individual Training

Statistics.com - The Institute for Statistics Education - An Elder Research Company

Custom training on our Statistics.com platform quickly upskills your workforce to more effectively meet your business objectives through direct personal guidance, cutting-edge thought leadership, and a powerful dose of practical experience. Learn more →

Featured Insights

View All

Leading A Data Analytics Initiative

This eBook includes Chapter 3 from industry experts Jeff Deal and Gerhard Pilcher’s book Mining Your Own Business, A Primer for Executives on Understanding and Employing Data Mining and Predictive Analytics. Chapter 3 titled “Leading a Data Analytics Initiative” covers the key challenges and considerations for business leaders employing analytics to provide data-drive insight.

The Ten Levels of Analytics

Every technical project involves some sort of analytics, ranging from simply reporting key facts, to predicting new events. In this eBook we define ten increasingly sophisticated levels of analytics so that teams can assess where they stand and to what they aspire. The eBook clarifies definitions of three types of analytic inquiry and four categories of modeling technology and illustrates these levels with examples using tabular data representations commonly found in spreadsheets and single database tables. Additionally, the Levels are extended to encompass emerging data types such as time series, spatial data, and graph data, by providing data complexity as second dimension for categorization alongside algorithmic sophistication.

Top 10 Data Science Mistakes

In two decades of mining data from diverse fields, we have made many mistakes, which may yet lead to wisdom. In this eBook, we briefly describe, and illustrate from examples, what we believe are the “Top 10” mistakes of data science, in terms of frequency and seriousness. Most are basic, though a few are subtle. All have, when undetected, left analysts worse off than if they’d never looked at their data.

Featured Clients & Partners

Case Studies

Government

US Postal Service


Elder Research partnered with the U.S. Postal Service Office of Inspector General to develop and deploy a custom solution to identify and prioritize questionable contracts and healthcare claims for investigation. Leads generated were 74% actionable, resulting in over $11 million in recoveries, restitutions, and cost avoidance in the first year.

Download PDF

Commercial

DentaQuest


Elder Research developed a provider risk scoring model that enabled targeted intervention with low quality providers and reduced per patient cost by nearly 20 percent.

Download PDF

Commercial

nTelos


By applying advanced techniques for modeling and visualizing customer records, Elder Research created a combined data and text mining solution to increase marketing efficiency and reduce churn. The model improved targeted messages which resulted in higher profitability for nTelos, a regional mobile phone carrier.

Download PDF

Resources

FEATURED VIDEOS

Gerhard Pilcher discussed the gap between the promise of analytics to transform a company and the actual results, and how adaptability and intuition by leadership can help close that gap.

Target Shuffling Video_Final

Target Shuffling is a process for testing the statistical accuracy of data mining results. It is particularly useful for identifying false positives, or when two events or variables occurring together are perceived to have a cause-and-effect relationship, as opposed to a coincidental one. 

View All Videos

RECENT WHITE PAPERS

View All White Papers

BOOK OVERVIEW

COVER_Mining_Your_Own_Business.jpg

Mining Your Own Business is a practical guide for organizational leaders and top-level executives that demonstrates how to harness the power of data mining and predictive analytics, and avoid costly mistakes.

Learn More