Article

Streamlining IFS Analytics for government contractors

Nov. 6, 2024 · Authored by Dave DuVarney

Implementing cloud-based analytics in any organization is complex. When a government contracting company faced the challenge of leveraging IFS Analytics amidst stringent security requirements and complex business processes, they turned to Baker Tilly for assistance. They focused on harnessing out-of-the-box analytics and ensuring a seamless integration with Azure Gov Cloud High (GCC High).

Standardizing business processes and navigating the Azure Gov Cloud

The organization aimed to standardize business processes across 11-13 business lines. Utilizing IFS Analytics would provide consistent visibility; however, deploying in GCC High introduced significant challenges, particularly when utilizing templated solutions, due to its restricted set of available resources and capabilities which meet specific security requirements.

The project team used Microsoft Data Factory to migrate data from IFS to the GCC High tenant, managing two environments: production (prod) and user acceptance testing (UAT). A significant technical hurdle was configuring the virtual private network (VPN) and securing key vaults to store credentials. Close collaboration with Microsoft and IFS engineers was crucial to overcoming these challenges and ensuring secure data transfer.

Additional hurdles included limited Power BI and service-based deployments expertise, a tight deadline of two months and the need to manage multiple environments. This required the team to spend additional time to learn and implement the necessary technologies and to work quickly and efficiently, prioritizing tasks effectively.

Aligning data for accurate reporting

After configuring the environment, the project’s emphasis shifted to aligning data for precise reporting. Measures were taken to ensure that the organization was using the fields in IFS correctly as they mapped into the analytical models. Changes were made to the organization’s IFS data to support the pre-built analytical models.

The team conducted design workshops with the client to understand user needs, including key performance indicators (KPIs), report usage and data governance. The workshops helped in standardizing reporting metrics and ensured that KPIs were consistently defined across departments, resulting in more reliable insightful reports.

Integrating legacy data for historical analysis

Integrating legacy data to allow for long-term trend analysis was critical in this project but brought some challenges along the way. The older data formats did not match the new data structures, complication integrations. The team used Azure Data Factory and other Microsoft tools to map and import legacy data in the Azure environment, ensuring comprehensive reporting capabilities. The integration provided the client with a complete view of business performance by combining historical and real-time data, enabling more informed decision making.