What we did






Scaling Data Science Operations for a Utility Aggregator

Client Project
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Scaling The Business

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This client aggregates data from numerous electricity energy providers to determine the effectiveness of programs such as Energy Saves rebates targeted at consumers who purchase Smart Thermostats and other energy-saving devices. The client's #1 issue was being able to scale their data science operations & processes.


Our approach

Skylytics took the client through a Data Discovery process to identify key data processes & pipelines as well as related data transformations and data quality needs. Through this Skylytics identified a number of key areas where the data pipeline could be streamlined and improved. The overall result was a 50% increase in revenue-generating capacity with the same number of data scientists and personnel.
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Unified Data Pipelines

Skylytics took a number of existing discrete data pipelines and unified them into Microsofts Data Factory. This resulted in a more industrialized data pipeline with true scalability.

Standardized Data Processes

Through the Data Discovery Skylytics identified a number of repeated data processing steps being performed on an individual basis. Leveraging the new industrialized pipe line Skylytics was able to reduce the number of repeated & redundant process by a factor of 10x.

Reduced Operational Cost

Unifying the overall data pipeline and processing resulted in a >50% reduction in data costs and increased the clients revenue generating capacity by >50%.

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