Case Study - Data Warehouse Optimization
A company who is a key player in the Online Marketing and Advertising Sector, faced inefficiencies in its data management strategies, particularly in measuring and optimizing online real-time auction performance. The reliance on outdated tools and incorrect metrics necessitated a complete overhaul of their Data Warehouse system.
- Saved Yearly
- $60,000
- Cloud Storage Saved
- 2/3
- Revenue Surge
- 30%
- Client
- Dignity
- Year
- Service
- Data optimization
The Challenge
The primary issues stemmed from increasing cloud usage, outdated manual data extractors and a lack of structured data warehousing, leading to inaccurate data collection and inflated operational costs.
As a result, the process of data transformation was not just costly but also unnecessarily complex, leading to suboptimal outcomes in online real time auctions which is a heart of every Ad Serving company.
The Solution
To combat these issues, we integrated advanced components within the Keboola platform, improving data accuracy and streamlining the extraction process. Data marts were introduced for logical data segmentation, aligning data transformations with business goals and enhancing operational efficiency. This approach provided a foundation for strategic decision-making and optimized real-time bidding processes.
This enabled us to use tailored transformations closely aligned with specific business objectives, such as outsourcing data tables, creating complex Business Plan strategies or providing ad hoc real time data to external bidding systems.
Results, numbers and impact
The overhaul led to significant operational cost savings, reducing annual expenses by $60,000 and cutting credit spending by two-thirds. This financial efficiency was paralleled by a 30% revenue surge from optimized real-time auctioning systems, showcasing the value of accurate, accessible real-time data. Additionally, a new reporting system and custom templates were developed, improving intra-company analytics and client engagement.