Will cloud computing centralize big data? I read an InfoWorld article by David Linthicum at the end of last year titled 5 key trends in cloud computing’s future, and it made me start thinking about information management in the cloud, specifically Linthicum’s 4th key cloud trend: Centralized data will become a key strategic advantage. As outlined by Jeb Horton, President, HP Information Management and Analytics in his new video titled Seize the Power of Connected Intelligence, data is growing at a rate of about 50% per month, reaching volumes hitherto unforeseen. The IT industry will continue coming up with new units of measurement that are more conducive to the quantification of the data volumes.
But, do enterprises have the requisite solutions in place to effectively manage such volumes? According to research from HP and Dimensional Research:
- Only 32% of companies say that deployed business intelligence solutions meet current business needs.
- Less than half believe current business intelligence solutions can handle large data sets.
- At least 50 percent of companies lack an effective information strategy.
Cloud computing needs to be an integral part of the enterprise information strategy. The characteristics associated with the cloud like elasticity, virtualization, etc., apply as much to storage as they do to compute and network. The cloud offers better alternatives to address the increasing (and fluctuating) data volumes and warrants strong consideration by enterprises to address their information management challenges.
Here are my top 5 strategies for effectively employing the cloud to address information management challenges:
1. Selective Migration: Move the right data to the cloud. Appropriate consideration needs to be given to compliance laws around data privacy before establishing the data that can be stored in the cloud. Data that is likely to grow in large volumes frequently must be given a higher priority over other types of data.
2. Modernization Approach: As outlined in my previous post on Applications Transformation and Information Analytics, legacy data needs to be selectively modernized so that the business intelligence can be effectively extracted across years of accumulated data.
3. Information Processing: Enterprises must employ tools that can process structured and unstructured data with context-based search to present information that directly addresses the needs of internal and external stakeholders.
4. Retention Policy: Data retention periods significantly impact the data in flux at any point of time. Clear definition of the retention policies is vital to ensuring that the right amount of information is being managed. Less clutter.
5. Storage as a Service: Applications must have the flexibility to consume storage in the as-a-service model and be designed to be agnostic to the manner in which storage is provisioned.
Some of these strategies are not new and could also apply to traditional environments. However, given the advent of cloud computing as an option for data storage, it is even more important that enterprises give strong consideration to adopting these strategies to address information management challenges.
What are some of the strategies that you are employing in this context? I would be interested to know.
Do you believe cloud will solve your big data challenges? If so, how are you integrating your cloud computing strategy with your information management challenges?
To learn more about how HP is helping its customers with both cloud computing and information management, check out these resources: