Technologies Used
This client excels as a world-class provider of top-quality domestic and international transportation and logistics services, renowned for delivering their customers the highest quality freight solutions and services. They provide a wide range of services, including Full Truckload (FTL), Intermodal/Rail, Expedited/Domestic Priority, services to and from Mexico and Canada, Trade Show Logistics, Supply Chain Management, High Value/High-Risk Cargo Transport, Warehousing and Fulfillment, Value-Added Services, Customs Brokerage, and more
The client had implemented a Data Lake within the Microsoft Azure Cloud infrastructure. However, upon analysis of their current solution, several areas for enhancement were identified. These included refining the data model and optimizing table storage, whether physical or virtual. Moreover, challenges about automation, particularly in data ingestion and monitoring processes, were brought to light. Critical to these concerns was optimizing total costs, spanning cost structures, processes, and models. Furthermore, opportunities to enhance performance, streamline data workflows, and refine logic within and beyond defined views were identified as imperative areas for improvement
Challenges
Inefficient data lake architecture in Azure Cloud hinders scalable data management and impacts operational agility
Inadequate data model and table storage optimization lead to increased processing times and reduced data accuracy
Security weaknesses in data management create systemic vulnerabilities, impacting decision-making processes
Solution
Streamlined data processes by reviewing architecture and identifying automation opportunities
Examined and optimized decision-making elements and data models, significantly reducing the overall cost of ownership
Enhanced performance and scalability by addressing data gaps and improving security controls
Challenges
Inefficient data lake architecture in Azure Cloud hinders scalable data management and impacts operational agility
Inadequate data model and table storage optimization lead to increased processing times and reduced data accuracy
Security weaknesses in data management create systemic vulnerabilities, impacting decision-making processes
Solution
Streamlined data processes by reviewing architecture and identifying automation opportunities
Examined and optimized decision-making elements and data models, significantly reducing the overall cost of ownership
Enhanced performance and scalability by addressing data gaps and improving security controls
Business Impact
Improved Data Alignment and Dimension Assessment
The assessment recognized the potential for Product/Services as a global dimension, broadening the scope of data insights and improving decision-making capabilities
Analytical Data Workflow Enhancement
Refined data workflows, improving efficiency, accuracy, and overall decision-making processes by utilizing Azure pipeline instead of SSIS and implementing hierarchical Row-Level Security
Data Model Design Optimization
Identified missing data points and enhanced critical decision-making elements, such as KPIs, reports, and analysis, significantly elevating decision-making capabilities within the system
Streamlined Process Automation and Cost Optimization
Enhanced operational efficiency, streamlined operations and resource allocation, and ensured accuracy throughout the ETL process
Why Kanerika?
Kanerika is a premier provider of data-driven software solutions and services that facilitate digital transformation. Specializing in Data Integration, Analytics, AI/ML, and Cloud Management, Kanerika prides itself on its expertise in employing cutting-edge technologies and agile methodologies to ensure exceptional outcomes. With a proven track record across various industries, Kanerika maintains rigorous quality standards, backed by ISO 27701 certification, SOC II, and GDPR compliance. As a distinguished partner of Microsoft, AWS, and Informatica, Kanerika’s commitment to innovation and strong partnerships positions it at the forefront of empowering businesses for their growth.
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