Creating Insight Through All Levels of Retail

Our customer’s employees are service delivery professionals distributed across a broad geography nationally within retail stores. The individual success of these professionals in this service delivery model is critical to the overall corporation’s performance and planning for long-term growth strategies.

Understanding such factors and impacts as productivity, turnover, training, compensation and market demographics can be used to build a better understanding of the services professional’s professional journey.

Solution: Develop Architecture to Track KPIs

Tail Wind developed the architecture to track key performance indicators (KPIs) for their service delivery professionals. This was accomplished through analytics of the POS system, Corporate CRM system (Microsoft Dynamics CRM) and other data sources.

Tools:

• The main components of the project include the Azure Data Lake, and Snowflake ODS and analytical databases. For data integration, the primary tools used are Azure Data Factory, Azure Data Lake Analytics U-SQL, and Azure Databricks.
• To support the data integration process, control and audit mechanisms exist in an Azure SQL Database. Alerts and Monitoring of the process are managed within Azure Source control for most processes exist in Microsoft DevOps.
• The purpose of the Data Lake is to serve as the single source of truth for corporate data and as a central repository of all (eventual) data sources. The purpose of the Snowflake databases are to better serve data analytics and to source Reports and Dashboards for Microsoft Power BI.

Results:

The corporation now has a better understanding of their data and the ability to view scorecards, dashboards and reports which will help their retail stores succeed. This also allows the corporation to successfully plan for expansion into other geographies, provide effective recruiting, training and retention programs for their services delivery teams.

How It Works:

The Corporate Data Lake we built in Azure supports the Data Science and Business Analytics teams by giving them the ability to easily and reliably explore all available data in its raw form. The Snowflake Analytical environments help turn the Data Lake data into information that can be consumed and analyzed by all levels of corporate data users; from direct querying data to Microsoft Power BI Reports and Dashboards.