Data and insight

Similar to on-premises data analytics, cloud analytics algorithms are applied to large data collections to identify patterns, predict future outcomes and produce other information useful to business decision makers.   The cloud has empowered users to generate insights through simple, easy to access tools for data ingestion, analysis, and visualisation.

Traditionally, data warehouses required specialist hardware and software, with high start up costs and lead times.  While on-premises analytics solutions give companies internal control over data privacy and security, they are difficult and expensive to scale. Traditional business intelligence tends to be IT-led, in the hands of a small number of specialist data analysts.

By contrast, cloud platforms provide databases, data lakes and analytics tools as ready to consume services, with the familiar cloud characteristics of on-demand availability, scalability, resilience, consumption-based pricing as well as robust security, governance and access controls.   The cloud levels the playing field for analytics organisations with limited resources, have access to the same tools as large enterprises.  Advanced data analytics, AI, and machine learning tools are available to help you elevate the experience for your customers, employees, and partners while easing constraints of scale, performance, and cost.

Cloud analytics systems are suitable for processing large data sets, particularly if the data already resides in cloud-based systems.  They are able to handle all data types and formats, incl. structured, unstructured and semi-structured data (for example video or image files), with real-time and near real-time ingestion and analysis.  Finally, the cloud hosts a plethora of modern business intelligence, visualisation and automation tools which allow business users to access real-time data to generate dashboards and workflows to drive their business. Common uses include:

• analysis of customer behaviour
• developing efficiency or growth strategies
• uncovering business problems
• optimising performance

Alongside cloud adoption, AI is becoming a more integral part of cloud analytics. Machine learning algorithms, in particular, enable cloud analytics systems to learn on their own and more accurately predict future outcomes. These tools become even more powerful when combined with the automation capabilities of the cloud to solve business problems.

Each of the cloud hyperscale providers offer an extensive range of tools and platforms which is constantly evolving.   The choice of tools and solutions will need careful consideration of the business and technical context of the application.

The NHS England Cloud Centre of Excellence (CCoE) can support you to develop solutions and proof of concept systems, by connecting you with pre-sales support available under the enterprise agreements with the cloud service providers.

Contact us by emailing [email protected].