Case Study



Modernized cloud data infrastructure conducive to sustained growth and longevity

How Systech’s data and analytics skills helped the leading automotive filtration and technology industry leader revamp their data framework and enabled automated analytics & insights.

Who we worked with:

Automotive filtration and technology industry leader of the past 50 years, offering products that increase the performance, protection, and longevity of thousands of vehicle applications for consumers worldwide. 

What the customer needed: 
  • Creation of a centralized, on-premises data warehouse, able to store their raw and filtered data. 
  • To enable self service analytics and insights across the entire breadth of their departments.
  • A scalable Cloud Solution, compatible with their existing data infrastructure. 
  • POS Management, Inventory Stock Management, K&N Mapping, and Vehicle Mapping functionalities. 
Modernized cloud data infrastructure

Innovation highlights 

Creation of a scalable data infrastructure, able to support the enterprise as they continue on their growth path trajectory. 

The ability to effortlessly synthesize massive quantities of datasets, for the seamless automation of analytics and actionable insights. 

Adapt or die. Read on to view the entire case study! 

THE CHALLENGE 

Several Waves of Transformation Spanning Over 5 Years 

 The industry leader designed and manufactured all their products onsite. As a result, they had a wide breadth of departments that include engineering, product design, manufacturing, warehousing, testing facilities, purchasing, sales, customer service, corporate offices, and marketing. They lacked a centralized data warehouse, resulting an inability to enable insights and analytics on their sales data. What’s more, it also resulted in an absence of POS and Inventory Stock Management systems, as well as a Vehicle and Product Mapping functionalities. 

 The client’s objective was to first create on-premises infrastructure to assess its value within the limited scope of their Sales Segment. Once validated, they would look to transition from their on-premises infrastructure to that of a scalable, cloud alternative. This shift would become instrumental in their ability to automate and streamline their analytic reporting functionality. If successful, this would enable the agility, scalability, and self-service capabilities necessary to sustain long-term growth and competitiveness in the market. The outcome of this data modernization would influence the entire trajectory of their growth and success for the years ahead.  

THE SOLUTION 

Creation of a Centralized, On-Premises Data Warehouse Fosters Future of Modernization 

At the time that Systech began working with the industry leader in 2019, they did not have a data warehouse to any capacity. Data warehousing is highly imperative in order to improve the speed of efficiency when broaching different datasets. Without it, the client lacked the clean data necessary to convert it into impact-driving insights and analysis. This infrastructure is essential in garnering insights that can foster sales and marketing strategies. 

For this first initiative, the client started small by limiting the scope to their sales data. Systech was able to establish Power BI which could facilitate the generation of custom insights and analytics. This foundational layer would enable business users to navigate the data, create their own automated analysis, and leverage new analytics and insights tools.  

Expansion into a Holistic View of Operational and Data Excellence 

The next phase of the business’s data transformation was to incorporate Operations Data into the model. Specifically, Sales was expanded to include POS Sales and Inventory Data. It was during this period that they first identified the value that could be added by switching to a cloud platform, as it was becoming increasingly expensive to stick with a non-scalable option. 

As an organization whose Data Warehouse was built with Microsoft products, it was a highly programmatic and lucrative to factor in the potential discounts and seamless migration of sticking with the same provider. Thus, the Azure Platform was the most logical prospect as it would provide the client scalability and self-service capabilities for a fraction of the cost. This also cut down on additional costs that would’ve been associated with new technology training sessions and project execution timing. The Azure Platform would offer the smoothest and most reliable outcome given the current needs of the organization. 

What’s more, Azure could now bring marketing data from various social media platforms to the organization’s internal data repository. With plug-and-play data from social media websites, business users could now generate highly accurate, data-driven insights in near-real-time. This not only saves the organization time – as the functionality is built into the infrastructure – but also saves money on what would’ve been the associated expenses and maintenance. 

Enhancement to Reporting and Management Systems 

The client was missing consistent reporting functionality across their different business segments. Once transitioned to the cloud, the organization could streamline various reporting activities. Thereafter, the industry leader was able to leverage the following offerings: 

  • Global Sales Reporting 
  • Operations Reporting 
  • POS Management Reporting 
  • Inventory Management Reporting 
  • Vehicle Product Mapping Reporting 
  • K&N Product Mapping Reporting 
  • Power BI Reporting 

This array of reporting options collectively offered agility, facilitating short, time-boxed iterations with only minor enhancement necessary over time.  

Data curation Batch Processing Implementation and Power BI Offers Key Benefits 

 Systech created and implemented data changes that resulted in a long-term solution to schedule data-driven workflows, stage data within the Azure Data Lake for faster availability of raw stage data, trigger pipeline execution, as well as monitor and configure processes and alerts. Azure Synapse Pipelines was instrumental for each step of the implementation. Automation and readymade reporting were more accessible and streamlined than ever before.  

THE BUSINESS IMPACT 

Systech was able to establish data solutions that resulted in measurable impact in the following areas:  

In a matter of four (4) months, Systech was able to bring power operations data into the mix of their current data onslaught – with the enablement of Power BI – before later modernizing them to the cloud. The solution executed the following: 

  • Development of a centralized reporting platform, enabling self-service analytics. 
  • Automation of the daily ‘Global Sales Report’ communication to the entire organization. 
  • A web interface designed to help facilitate sales forecasting at the product family level. 
  • Creation of analytic reports on POS and Inventory Management 
  • Transition to the Azure Platform that would be conducive to agility, scalability, and self-service capabilities. 

Automated Reporting and Insights Made Possible through a Modernized Data Framework 

 In choosing a partner with a long history of migration and modernization success, the client focused on their two main concerns: price for performance as well as speed to market. Systech was successful in accomplishing their data and analytic initiatives 2x faster for 2x lower cost than most providers in a matter of 4 months. Through the employment of their services, Systech was able to modernize and improve their current data warehouse environment, as well as create the foundation necessary to enable seamless access and analysis of a broad range of internal and third-party data. Not only was this critical for driving engagement with its members, but also empowered the organization to deliver on business performance objectives.  

 At the conclusion of this initiative, the client had the infrastructure required to support all their future data analytic needs. Without a doubt, the industry leader will continue to look to Systech for all future business and data conquests.