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

Edit This Case Study Record

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

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

Tableau

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	AOL was able to transition from a push model to a pull model, enabling self-service Business Intelligence.
Impact #2	The company was able to analyze real-time data, tracking the performance of different products in search areas every 15 minutes.
Impact #3	The implementation of Tableau allowed AOL to spend more time on solving problems or fixing issues, rather than creating reports.

Impact #1

AOL was able to transition from a push model to a pull model, enabling self-service Business Intelligence.

Impact #2

The company was able to analyze real-time data, tracking the performance of different products in search areas every 15 minutes.

Impact #3

The implementation of Tableau allowed AOL to spend more time on solving problems or fixing issues, rather than creating reports.

Benefit #1	Tableau saved 64 hours of work for one report, which is almost like eight business days.
Benefit #2	Reports that would take two weeks to put together from concept to production could be done in minutes or hours with Tableau.
Benefit #3	More complex reports that would take weeks or months to do could be done in a day or two with Tableau.

Benefit #1

Tableau saved 64 hours of work for one report, which is almost like eight business days.

Benefit #2

Reports that would take two weeks to put together from concept to production could be done in minutes or hours with Tableau.

Benefit #3

More complex reports that would take weeks or months to do could be done in a day or two with Tableau.

Download PDF Version

Overview

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

Operational Impact

Quantitative Benefit