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Sisense > Case Studies > Powering Smart Media Buys with Sisense
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Powering Smart Media Buys with Sisense

Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Analytics & Modeling - Real Time Analytics
  • Application Infrastructure & Middleware - Data Visualization
Applicable Functions
  • Business Operation
  • Sales & Marketing
Use Cases
  • Real-Time Location System (RTLS)
Services
  • Software Design & Engineering Services
  • System Integration
The Challenge
Ignite Media processes massive amounts of data, maintaining approximately 3 TB of transaction, demographic, and media performance data. They had been building all their reporting internally using PHP and .Net, but it was becoming increasingly difficult to scale. Writing new reports from scratch to follow a 'hunch' could take weeks, making it impractical to test new ideas. The company had valuable data but lacked the resources to fully leverage it. Mazda Ebrahimi, the VP of Application Development, sought a solution that would allow them to produce results faster and more easily without sacrificing their intellectual property.
About The Customer
Ignite Media Solutions is dedicated to enhancing the customer experience by partnering with clients to maximize the effectiveness of media expenditures. They help their partners improve brand performance, sales, and profitability through innovative tools and technology at every point of the consumer lifecycle. The company processes massive amounts of data, including transaction, demographic, and media performance data, to provide valuable insights and reporting. With a focus on improving customer experience and media effectiveness, Ignite Media Solutions is a key player in the media and entertainment industry.
The Solution
Mazda Ebrahimi tested various solutions, including Tableau, before selecting Sisense for its ease of use, power, cost-effectiveness, and support. He set up a virtual machine with 128GB of RAM and loaded a table with 320 million rows and 500 columns for processing. Sisense was installed and set up within hours, and the results were nearly instantaneous for any queries. Ebrahimi created Elasticubes centered around specific topics, allowing analysts to work within those cubes without creating multiple reports. The system maintains these subsetted views of the data, enabling clients and internal users to use predefined dashboards to browse and customize queries. Sisense simplified complex data relationships by creating 'views' stored in the database, allowing users to create new cubes quickly and easily.
Operational Impact
  • The ease of use and speed of Sisense freed up over 50 man hours per month in Mazda’s group.
  • They were able to spend more time digging deeper into their data, testing out 'hunches,' and following various trains of result sets.
  • Enhanced security through cube-stored user permissions.
Quantitative Benefit
  • Freed up over 50 man hours per month across 3 employees.
  • ~40 Dashboards categorized by topic.
  • ~20 ElastiCubes.

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