Harnessing the power of data within your business can be a complex task. Once established, a modern data strategy can unlock insight and correlations which reduce bottlenecks in business process, reduce cost of sale and allow you to generate revenue streams based on detailed analytics. Common steps along this journey include;

• Assess; often linked to your data strategy, we explore what data (types, sources) exists in the business, what the sources of truth are, how important the data sources are, what are the priority use cases and understanding a road-map to modernize the use of data.
• Define a blueprint; follow an agile framework, leveraging a priority use case to establish a blueprint for modernizing the use of data. It will be challenging to imagine all future permutations so instead focus on establishing a baseline and evolving it thereafter.
• Establish a lighthouse; based on the blueprint build and expect to evolve, an initial data modernization platform, leveraging cloud first technology to allow you to centralize, correlate, analyze and report on the data.

Our data modernization quick start provides a framework to define a data modernization blueprint then deploys this leveraging cloud first technologies. The engagement is executed using two agile iterations, each usually 3-weeks.

• The first iteration, referred to as Data Strategy Sprint, explores priority use cases within your business, often based on existing challenges, for example, sprawling data sources, lack of analytics & reporting capabilities or lack of modern infrastructure to support such a strategy. One these use cases are established, we leverage our blueprints to design a lighthouse data platform architecture.
• The second iteration, referred to as Data Foundations sprint, leverages our site reliability engineers to automate, deploy and operationalize the data strategy including core components to support the capture and centralization of data in Cloud together with ability to report on its usage and thereafter engage your business analysts or data science team to further manipulate the data and understand the impact it can have within your business.

This includes knowledge sharing of the tools, code templates (through an agreed repository), techniques and processes we use with transparent sharing of documentation and awareness for your teams once the engagement is complete.

The process will be executed using the following key steps:

• Discovery & requirements gathering; review your existing data strategy and road-map.
• Analysis workshop; review our recommendations and draft plan based on your requirements.
• Finalize Data Strategy blueprint; as both an output of the first iteration and input to the second.
• Low level design; defining the configuration schematic to be deployed and dependent aspects such as test plan.
• Automated execution; build of the data foundations.
• Testing; following the agreed plan and leveraging our standard validation process.
• Handover; of the deployment including code sharing and knowledge transfer.

This is a collaboration with knowledge sharing, documentation, and resources to help your teams get the skills they need for long-term business agility and maturity on Cloud.