Using Cloud for Analytics Driven Innovation

Kumar Majety
In an increasingly big data intensive environment, most organizations want to crack the code on analytics driven innovation. They’re eagerly trying to get big data projects off the ground, but often run into hurdles according to eWEEK Enterprise 2014 Big Data Outlook. The key challenges include supporting large data volumes and new types of data (53%) with their existing corporate IT infrastructures and budgets, complexity of software/data integration (54%) and making analytics easier for business users (53%).

So, what is required to deliver big value from analytics to your business? A well-defined use case is a good first step but not enough.  Setting high expectations for your data analytics team and asking them to quickly generate conclusions by working with the IT department seldom translates into success.  A clean sheet approach to the underlying technology infrastructure (including database, compute & storage) and enterprise analytics/visualization software tools combined with deployment agility and flexibility is essential for successful innovations as described by Martha Bennett of Forrester Research. However, these enterprise grade analytics platforms are often anything but agile and carry a hefty price tag of complexity and inflexibility.  This leads to Catch-22:  to get investment dollars, you need to show proof of value but to have an air-tight business case, you will need to pilot the initiative and see if the idea can really generate value.

How do Cloud Analytics fit into this equation? Cloud analytics provide an ideal solution to get your big data initiatives up and running quickly and inexpensively.  These solutions offer high scalability, reliability, and flexibility to run any vendor’s analytics tools without lock-in or the headaches of managing hardware and software.  They allow you to only pay for what you need, and easily scale up or down.  “Software as a Service Offerings” from Analytics or Database software vendors are not ideal for innovation projects as they lack the flexibility to support your specific needs or tools of choice.  Cloud analytics solutions on the other hand are a better fit for innovation projects as they address end-to-end analytics lifecycle needs on a pay-as-you-go basis.  That means, specific advice on turning your data into business insight, hardware and software architecture designed for your analytics/data/business requirements, pre-built templates for agile deployment, end-to-end administration of analytics infrastructure & applications, data management and integration of different data sources in the cloud, and enterprise security and compliance.  A great way to start would be to kick tires with a partner that offers try-n-buy of the complete cloud analytics platform and service at no cost to you.

Lenovo is running Analytics Innovation Studio on Cloud Analytics.  A global manufacturer with more than $30+ billion in revenues is using SAS’s advanced analytics, text mining and visual analytics tools deployed on CoreCompete’s Agile Analytics Platform.  In 2 months, CoreCompete delivered the cloud analytics solution (on AWS) that enabled the client to pilot several big data solutions that integrate internal and external data in a cloud environment and prove innovations in: Quality Analytics, Channel Analytics, Sourcing Analytics, and Social Media Analytics.  In addition, Lenovo has also leveraged the analytics innovation platform to successfully scale these for enterprise wide usage.

We hope that these examples gave you some ideas on advancing big data innovation projects in your organization.  E-mail us to see how we might be able to help you get started.

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