Cloud Analytics for the NFL and NCAA Football

Industry: Sports Analytics

Project Type: Power BI and Analytics / Cloud Solutions

Tools Used: Amazon Web Services (AWS), Microsoft SQL Server Database Engine, Microsoft SQL Server Reporting Services, Microsoft SQL Server Analysis Services, PowerShell.

The Benefits

Minutes of Effort

instead of days of effort for the duplication script to produce copies of the environment.

Attract Additional Customers

with the professional analytics environment.

Handle New Customers

with excellent performance in the environment.

Project Overview

Pro Football Focus (PFF) is an organization dedicated to providing in-depth analysis of NFL and NCAA football in the United States. Using a group of experienced football analysts, PFF produces numerical grades for teams and players by watching and grading every player on every play.

Pro Football Focus (PFF) needed to provide customers (fantasy football, NFL teams) with:

A secure, interactive, high-volume cloud environment for performing data analysis.
An analytics environment that didn’t impact the performance of the data gathering system.
An entire environment that was duplicatable at the touch of a button.

Goals

Structured, yet highly interactive analytics experience.

Dashboard and reporting environment that could withstand heavy use.

Robust and reliable presentation environment.

The Approach

SCS created an analytics solution for PFF based on Amazon Web Services.
The entire cloud configuration is scripted so the existing environment can be duplicated and deployed in a very short period of time.
SCS used SQL Server to create an ETL process to bring near real time analytical data into the analytics environment.
The initial reporting was designed and developed by SCS to set standards and best practices used by PFF during subsequent analytics development.
SCS provided training sessions to PFF so they can support and enhance the analytics in the future.

The Results

PFF now provides its customers with a secure environment for performing reporting and analytics.

This environment can easily grow to meet user needs.

The environment delivers data with minimal latency while exerting minimal impact on the data entry environment.

Additional copies of the environment, down to the data content and system configuration, can be stood up quickly to facilitate development and load sharing environments.

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