Many organisations understand the value of Cloud and also the value of Big Data. There is a trend in addressing both the Cloud and Big Data use cases as a combined project. These projects may start with a modest investment but can scale very quickly with overwhelming demand from the business and seemingly exponential increase in data volumes. The early stage of all projects requires an appropriate kickstart approach and seed investment. Understanding how to execute these initial pilots, while having a view on a 5 year TCO can be challenging for organisations with limited experience of either cloud or big data technologies.
Successful projects maintain flexibility in deployment patterns, this enables tuning for workloads, tuning for data and continued optimisation of resource use and costs. Driving projects from user-need, through a use-case catalogue can assist in managing the data ingest, management, governance and exploitation of data. The use-case catalogue also assists in managing changing priorities and feeds into budgets and financial plans. Based on a range of successful production deployments on AWS and Azure, this session will provide the foundations of the MVP and kickstarting your project, it will then discuss how growth can be planned, managed and budgeted effectively.
Technical practitioners will learn how to effectively size an initial MVP, as well as pragmatic methods of scaling to a 5 year long term foundation and growth plan. Business sponsors and program delivery will benefit from a pragmatic retrospective on lessons learned and techniques for managing the initial funding and longer term strategic budget and investment.
This session will include the high level themes:
Sizing and effective planning are one aspect of a successfully project, it is also dependant on the combination of Cloud and software components to deliver efficiencies in data storage and analysis.
More detailed topics will include:
Dr Christopher Royles is a Systems Engineer at Cloudera.
He holds a PhD in Artificial Intelligence from Liverpool University which he subsequently applied to voice recognition and voice dialogue systems. Chris has advised on Government Open Data initiatives as part of the Open Data User Group (ODUG) and sat on the quick wins stream of the UK Government Cloud Program (GCloud).
Chris has built out large scale data lakes on Amazon and Azure as well as assisted customers in their initial MVP through to full scale production.
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