UCO RECYCLING COMPANY
BUSINESS PROBLEM
This Used Cooking Oil (UCO) Recycling Company had a goal to triple its business in the next 2-3 years. To accommodate this growth projection, their IT infrastructure and core business systems needed to be modernized and moved into the cloud. In addition, they need to get actionable insights from their data to enable informed decision-making about growth potential and optimization or their operations.
SCALESOLOGY IN ACTION
Scalesology is this UCO Recycling Company’s data operations partner and continues to work with the company today. Scalesology projects and activities include the following:
Centralized data from disparate systems (on-premise and cloud) into one data lakehouse in Snowflake using Python.
Daily updates and email notifications when errors occur
Provides redundancy of data for their CRM, Financial, and HR systems
Allows scalable 3rd party cloud application integrations (e.g. push/pull from Salesforce)
Integrates historical data from new company acquisitions into the data warehouse
Built interfaces between legacy and new applications to transmit data seamlessly.
Developed dashboards from this data warehouse in Power BI using SQL and DAX for underlying data models.
Provide daily updates
Replace the current static reports
Display monthly forecast results
Created apps for different business users
Generated forecasts using Python and the Prophet library.
Forecast the amount of used oil for all locations based on a particular time period (every x weeks)
Forecast amount of used oil collected on a monthly and weekly basis
Forecast sales prices for used cooking oil on a monthly basis
Updated every month
Provide 3rd party application support for various company applications.
Support ongoing data operations.
Support Data lakehouse connections
Create new dashboards and reports for business users
Migrate data from companies that the UCO Recycling company has acquired
Routine maintenance and support on data assets
RESULT
This UCO Recycling Company now can scale and grow without the worry of impacting production or having the ability to continue to grow. Specific impacts to their operations were:
Data redundancy across all critical systems is updated daily.
The ability to create detailed reports with data from the data lakehouse without impacting production systems.
Analytical data warehouse is the foundation for current and future modeling and analytic initiatives.
A scalable data ingestion process can accommodate existing and new data sources.
Automated processing, which significantly reduced manual data entry and monthly report generation tasks.
The creation of executive and business unit management dashboards updated daily, thus giving visibility to critical KPI’s, budgets and route information.
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