Streamlining data flows to improve insights in adult social care using AWS

Transforming data processes with AWS to help plan, monitor and fund adult social care more quickly and accurately.

The project

There are thousands of adult social care providers in England. So there’s a huge amount of data to manage. To help inform the decisions made by the government and other stakeholders, DHSC asks Skills for Care to collect and analyse data on the workforce of these providers. Skills for Care have been performing this role since 2006 via the Adult Social Care Workforce Data Set (ASC-WDS) service.

At the moment, many of their data analysis processes are manual, which takes considerable time, and doesn’t maximise the insights that the team can get from that data. Skills for Care asked us to help them transform their data processes so they can provide the intelligence needed by the sector more quickly and accurately.

Our approach

We implemented the Amazon Web Services (AWS) data ecosystem to modernise Skills for Care’s data architecture and processing. The goal was to streamline processes, automate routine analysis and free up valuable analyst time.

We collaborated with the analytics team, implementing best practices in data engineering and applying machine learning to improve workforce estimates. We helped the team identify the system requirements to continue to develop this data pipeline, and build more as new data becomes available.

“The data engineering prototype developed in this project is the first step toward a new way of working. It will help us to report more frequently and accurately to support faster and better decision-making.”

Will Fenton, Analytics Manager

The results

An analysis that used to take 2 days, can be done in 15 minutes, and the datasets available for review are extended from one to 10 years. The team can now import data from many data sources automatically, helping enrich their data, fill data gaps and review at a more granular level, improving the quality of their workforce estimates.

Now, there’s no need to manually process data, saving time and effort. Data visualisations inform analyses, making it much easier to see trends over time.

It’s increasingly quick and easy to test new ideas, and identify and fix issues earlier when data changes outside of the organisation happen. Because the process is automated, it can be rerun with no extra effort.

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