Download PDF
Nielsen's Business Intelligence Revamp with Alteryx and AWS
Technology Category
- Networks & Connectivity - RFID
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Equipment & Machinery
- Telecommunications
Applicable Functions
- Quality Assurance
Use Cases
- Time Sensitive Networking
Services
- Cloud Planning, Design & Implementation Services
- System Integration
The Challenge
Nielsen, a global leader in audience measurement, data, and analytics, faced a significant challenge in 2017. Their Business Intelligence (BI) process was disorganized, with many small, independent groups rather than clearly defined silos. The situation was further complicated by an aging BI solution that had been running silently in the background for nearly a decade. The subscription for this tool had ended years ago, and it was only a matter of time before it would shut off without warning. This system was unsustainable, and a solution was needed. The urgency of the situation was heightened when Nielsen's encoding verification solutions (EVS) department, which relies on next-day BI reports to track the encoding process and ensure correct broadcasting and encoding across all available markets, discovered that their reporting process was built on the very BI tool that was about to be turned off. They had less than 90 days to find a solution.
About The Customer
Nielsen is a pioneer in market research and a global leader in audience measurement, data, and analytics. The company is built on data insights and uses patented encoding technology across radio and television to enhance audience measurement. Nielsen's encoding verification solutions (EVS) department helps preserve, maintain, and document the accuracy of that encoding technology. One team in EVS focuses specifically on radio transmission across the United States. This team relies on next-day BI reports that track the encoding process and ensures that radio stations are broadcasting and encoding correctly across all available markets.
The Solution
Nielsen had already chosen AWS as its cloud infrastructure for its scalability and powerful computing engine. Wayne McClure, solution architect at Nielsen, saw an opportunity to find a self-service analytics tool that would integrate well with AWS while empowering business users across the organization to handle analytics. They chose Alteryx, a tool that would empower not only seasoned analysts but also business users to create a more inclusive use of their data. The team could house data in AWS, analyze the data in Designer, and schedule and automate workflows with Server, which Nielsen deployed on AWS. Users could also easily pop the data into Tableau for visualization. Utilizing Alteryx on the AWS platform, Wayne’s team was able to go into a rapid-fire testing process to get an end output. The team removed several redundant systems and cleaned up SQL queries. Using Alteryx, the team ended up with daily completed reports in a 4-minute process instead of 4 hours.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Smart Water Filtration Systems
Before working with Ayla Networks, Ozner was already using cloud connectivity to identify and solve water-filtration system malfunctions as well as to monitor filter cartridges for replacements.But, in June 2015, Ozner executives talked with Ayla about how the company might further improve its water systems with IoT technology. They liked what they heard from Ayla, but the executives needed to be sure that Ayla’s Agile IoT Platform provided the security and reliability Ozner required.
Case Study
IoT enabled Fleet Management with MindSphere
In view of growing competition, Gämmerler had a strong need to remain competitive via process optimization, reliability and gentle handling of printed products, even at highest press speeds. In addition, a digitalization initiative also included developing a key differentiation via data-driven services offers.
Case Study
Predictive Maintenance for Industrial Chillers
For global leaders in the industrial chiller manufacturing, reliability of the entire production process is of the utmost importance. Chillers are refrigeration systems that produce ice water to provide cooling for a process or industrial application. One of those leaders sought a way to respond to asset performance issues, even before they occur. The intelligence to guarantee maximum reliability of cooling devices is embedded (pre-alarming). A pre-alarming phase means that the cooling device still works, but symptoms may appear, telling manufacturers that a failure is likely to occur in the near future. Chillers who are not internet connected at that moment, provide little insight in this pre-alarming phase.
Case Study
Premium Appliance Producer Innovates with Internet of Everything
Sub-Zero faced the largest product launch in the company’s history:It wanted to launch 60 new products as scheduled while simultaneously opening a new “greenfield” production facility, yet still adhering to stringent quality requirements and manage issues from new supply-chain partners. A the same time, it wanted to increase staff productivity time and collaboration while reducing travel and costs.
Case Study
Integration of PLC with IoT for Bosch Rexroth
The application arises from the need to monitor and anticipate the problems of one or more machines managed by a PLC. These problems, often resulting from the accumulation over time of small discrepancies, require, when they occur, ex post technical operations maintenance.
Case Study
Robot Saves Money and Time for US Custom Molding Company
Injection Technology (Itech) is a custom molder for a variety of clients that require precision plastic parts for such products as electric meter covers, dental appliance cases and spools. With 95 employees operating 23 molding machines in a 30,000 square foot plant, Itech wanted to reduce man hours and increase efficiency.
