Customer Company Size
Large Corporate
Country
- Worldwide
Product
- BigMemory Max
Tech Stack
- In-memory data management
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
Technology Category
- Analytics & Modeling - Real Time Analytics
Applicable Functions
- Sales & Marketing
Use Cases
- Real-Time Location System (RTLS)
Services
- Data Science Services
About The Customer
The customer is a leading ad tracking and market research firm that provides insight into the watching and buying habits of an estimated 10 million global consumers. Ad agencies and brand marketers rely on the company’s online measurement tools to maximize the effectiveness of fast-moving Internet advertising campaigns. The company's customers retrieve campaign performance reports through a web portal, which in turn queries a diskbound database to compile reports from tens of terabytes of ad-tracking data.
The Challenge
The company provides insight into the watching and buying habits of an estimated 10 million global consumers. Ad agencies and brand marketers rely on the company’s online measurement tools to maximize the effectiveness of fast-moving Internet advertising campaigns, so it’s critical that the company deliver ad performance reports quickly. Customers retrieved campaign performance reports through a web portal, which in turn queried a diskbound database to compile reports from tens of terabytes of ad-tracking data. However, customer satisfaction took a hit when slowdowns in data access began to degrade system performance. In some cases, customers had to wait as long as 20 seconds for campaign reports — an eternity in today’s need-itnow world. Even more troubling, slow database access caused an internal security system to time out on more than 50% of queries, and the problem only got worse as data volumes grew.
The Solution
The company needed a solution that would both accelerate data access and effectively manage fast-flowing, rapidly growing online campaign data. Following a successful Proof-of-Concept (POC) implementation, the company decided to use Terracotta BigMemory as an in-memory data management solution for daily data feeds. Every 24 hours, BigMemory’s in-memory store is refreshed with 200GB of fresh results (the data is also written to a database). The solution makes extensive use of BigMemory’s simple, powerful Search API, which supports complex, high-performance queries on large in-memory datasets.
Operational Impact
Quantitative Benefit
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