Centralized Data Warehouse

Centralized Point of Sale Data Using Snowflake.

An Overview

The Challenge

Our client’s staff was spending a lot of time and effort to access and analyze data, particularly point of sale data, as it was spread across various on-prem databases.

The Solution

The 2nd Watch team automated the load of internal and external data sources, and we designed and built a data warehouse to be optimal for analytical use.

The Outcome

The client can now easily access their data whenever they need it. We also set them up for future analytics and data science projects.



This client’s disorganized data was stalling their ability to quickly build reports and impeding useful analysis. Business decisions rely on accurate insights, and this company lacked confidence in conclusions based on their data.

2nd Watch created and executed a data strategy plan that resulted in an integrated and centralized data warehouse using Snowflake. The 2nd Watch team then leveraged the new data warehouse to create insightful Tableau dashboards for our client’s sales teams and executives to help them regain confidence in using their data to make business-altering decisions.


The Challenge

Our client’s many types of data, including inventory, shipment, point of sale, and other internal financial data, were stored on disjointed on-premise databases and in Excel documents. To generate reports or conduct analysis, each team gathered data from different retailers and internal departments – a lengthy and inefficient process. As teams generated reports in silos and with a variety of methods, they were met with limited flexibility in analysis, inconsistent metrics and understanding of data, and uncertain conclusions across the company.

This organization first needed a strategic plan for managing their data. They then needed assistance centralizing all external and internal data sources into one enterprise data warehouse that would allow for quick and accurate report building and analysis with Tableau.


The Solution

2nd Watch used Azure Data Factory and their data ingestion framework to automate the load of all internal and external data sources into Snowflake, including retailer point of sale and inventory, census, weather, and other third-party data sources. Once the data resided in Snowflake and adhered to the business rules, the data warehouse was designed and built to be optimal for analytical use. 2nd Watch worked with our client’s sales and e-commerce teams to build several Tableau dashboards that met their reporting and analytical needs.


The Outcome

By automating the load into the data warehouse and ensuring data followed all business rules, we gave our client access to centralized data that all of their teams could trust. They no longer had to manually gather and prepare data from multiple resources; instead, they could focus on performing analysis. 2nd Watch also identified free third-party data that would be useful in demand forecasting and automated the ingestion of this data into the data warehouse.

Additionally, the dashboards we created provided insights into high-level KPIs and measures across all sales, shipment, outstanding order, inventory, and point of sale data. The client was able to use the dashboards to drill down to a line-level of detail, giving them deeper and more meaningful insights.

Throughout the project, we helped our client identify data necessary for future analytics and data science projects to help them further harness the benefits their data can provide.