Service
Data & AI
Industry
Healthcare
Technology
Azure Synapse, Azure Databricks, Azure Data Factory
Customer
This healthcare organization is one of the global leaders in developing and delivering feed and medicines for both farm animals and companion animals through bold vision and cutting-edge scientific innovation.
Business Challenge
The national and global sales performance of animal health products classes is consolidated through CEESA (an international non-profit organization) International Sales Survey (CISS). CEESA members track and review their national and global sales performance in animal health product classes and species against all other participating companies.
The animal healthcare leader, a CEESA member, was not satisfied with the efficiency of data delivery to CEESA. Additionally, the insights from CEESA reports were obtained too slowly, were not precise enough, and impacted business decision-making.
Key challenges
- The process of data collection is cumbersome, and the code run-time for pre-processing has increased from 12 hours to 16-24 hours.
- Manual tasks like data quality checks done in Excel and SQL queries make the process complex.
- The current legacy system had 21 processes that were manual and prone to errors.
- Inefficient logging system that requires humungous effort to identify the root cause of failure.
- Since processes are executed sequentially, performance wasn’t adequate and impacted sales estimation reports and eventually the customer experience.
- Managing and maintaining reports, delay in report delivery to business users was delaying critical business decisions.
WinWire Solution
Bringing together the fast-paced advances in Data Analytics. WinWire suggested automation of data submission and advanced data-analytics for effective reporting and processing leveraging Azure Databricks and Azure Synapse.
WinWire leverages its consultative approach backed by rich data to build a centralized logging system for comprehensive logging from all the components involved in the process.
It covers the pre-processing framework, automated processing of data based on Metadata Framework, and Optimized Databricks Estimation Process to help the customer:
- Automate manual process using MetaData Framework + Azure Data Factory
- Convert & group manual processes into logical sets of Azure Data Factory pipelines.
- As part of pre-processing, users would be notified of missing data in advance.
- Re-write notebook to make it more modular and configurable & re-usable comprehensive logging in detail with real-time documentation
- Robust documentation for glossary, diagrams, data model specifications, and user manual.
- Code Repository/maintenance & versioning control.
Business Value
- Faster analytical insights
- Visualization in the form of pre-defined reports
- Accelerated business decision making with improved reports/insights in quick time
- Consolidated multiple systems into single source to enhance developer’s productivity
- Streamline data processes and the ability to load the data for ease of maintenance
