Tableau > Case Studies > AOL's Journey to Self-Service Business Intelligence with Tableau

AOL's Journey to Self-Service Business Intelligence with Tableau

Company Size

1,000+

Region

America

Country

United States

Product

Tableau

Tech Stack

Tableau Server

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Digital Expertise
Productivity Improvements

Technology Category

Analytics & Modeling - Real Time Analytics

Applicable Industries

Telecommunications

Applicable Functions

Business Operation

Use Cases

Real-Time Location System (RTLS)

Services

Data Science Services

About The Customer

AOL is a leading-edge web services company that offers premium and niche content sites, along with world-class tools and platforms. The company deals with a massive amount of data, with tens of millions of searches daily, each generating between 20 and 40 rows of data. This results in 400 to 800 million records every single day. The company was operating on a push model where the Business Intelligence (BI) team would have to manually pull and send out reports to those who needed them. This process was time-consuming and inefficient.

The Challenge

AOL, a leading-edge web services company, was facing challenges with its data not being integrated with the corporate data repository. The company was dealing with a massive amount of data, with tens of millions of searches daily, each generating between 20 and 40 rows of data. This resulted in 400 to 800 million records every single day. The company was operating on a push model where the Business Intelligence (BI) team would have to manually pull and send out reports to those who needed them. This process was time-consuming and inefficient.

The Solution

AOL implemented Tableau to manage and analyze its massive data. The company integrated its data with the corporate data repository and stored all reports within the Tableau Server. This allowed everyone to access the reports, with access granted as needed. The implementation of Tableau changed AOL's workflow from a push model to a pull model, where people could pull the data they needed when they wanted. This enabled self-service Business Intelligence, where people were in charge of the data they needed. The data was readily available, eliminating the need for querying or pulling data every day. AOL also used Tableau to analyze real-time data, setting up a real-time tracker to track the performance of different products in search areas every 15 minutes.

Operational Impact

AOL was able to transition from a push model to a pull model, enabling self-service Business Intelligence.
The company was able to analyze real-time data, tracking the performance of different products in search areas every 15 minutes.
The implementation of Tableau allowed AOL to spend more time on solving problems or fixing issues, rather than creating reports.
The company was able to monitor changes in real time, determining whether changes were working or not working.

Quantitative Benefit

Tableau saved 64 hours of work for one report, which is almost like eight business days.
Reports that would take two weeks to put together from concept to production could be done in minutes or hours with Tableau.
More complex reports that would take weeks or months to do could be done in a day or two with Tableau.