Challenges
- Data acquisition complexity arises from diverse sources, including headwaters, requiring sophisticated integration strategies.
- Data visualization complexity stems from the sheer volume and intricacy of datasets, demanding substantial cost for meaningful representation.
- Performance bottlenecks during data loading, exacerbated by large dataset sizes, hinder operational efficiency and may delay new version releases.
Solutions
- Utilizing EMR and other AWS services to seamlessly transfer big data into our transactional Redshift tool for efficient storage and management.
- Leveraging our analytics solution to visualize data effectively in Tableau, enhancing accessibility and insights for stakeholders.
- Implementing the Katana framework to optimize data refresh performance in Tableau, overcoming limitations associated with handling extensive and bulky datasets.
Benefits
- Ensuring 100% information availability in near real-time, facilitating timely decision-making and strategic planning.
- Enhancing the accuracy of new device version releases through comprehensive dashboard creation, fostering informed decision-making and streamlined development processes.
US based Telecommunication company
The challenge lies in optimizing data acquisition and visualization processes while overcoming performance bottlenecks. Since they are associated with large dataset sizes, the necessity of a migration to AWS architecture for cost reduction and enhanced operational efficiency was
