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Create a Customized Big Data Architecture and Implementation Plan

Your Challenge

Big data architecture is different from traditional data for several key reasons, including:
Big data architecture starts with the data itself, taking a bottom-up approach. Decisions about data influence decisions about components that use data.
Big data introduces new data sources such as social media content and streaming data.
The enterprise data warehouse (EDW) becomes a source for big data.
Master data management (MDM) is used as an index to content in big data about the people, places, and things the organization cares about.
The variety of big data and unstructured data requires a new type of persistence.
Many data architects have no experience with big data and feel overwhelmed by the number of options available to them (including vendor options, storage options, etc.). They often have little to no comfort with new big data management technologies.
If organizations do not architect for big data, there are a couple of main risks:
The existing data architecture is unable to handle big data, which will eventually result in a failure that could compromise the entire data environment.
Solutions will be selected in an ad hoc manner, which can cause incompatibility issues down the road.

Our advice

Critical Insight

Keep your systems dormant until disaster strikes. Prepare as much of your environment as possible without tapping into compute resources. Enjoy the low at-rest costs, and leverage the reliability of the cloud in your failover.
Avoid failure on the failback! Bringing up your systems in the cloud is a great temporary solution, but an expensive long-term strategy. Make sure you have a plan to get back on premises.
Leverage cloud DR as a start for cloud migration. Cloud DR provides a gateway for broader infrastructure lift and shift to cloud IaaS, but this should only be the first phase of a longer-term roadmap that ends in multi-service hybrid cloud.

Impact and Result

Calculate the cost of your DR solution with a cloud vendor. Test your systems often to build out more accurate budgets and to define failover and failback action plans to increase confidence in your capabilities.
Define “good enough” performance by consulting with the business and setting correct expectations for the recovery state.
Dig deeper into the various flavors of cloud-based DR beyond backup and restore, including pilot light, warm standby, and multi-site recovery. Each of these has unique benefits and challenges when done in the cloud.