What are the Challenges of Cloud Analytics ?

The need for fast and easy access to high-powered analytics has never been greater than it is today. Fortunately, cloud processing still holds the promise of making analytics more transparent and ubiquitous than ever before. Yet, a significant number of challenges still exist that prevent more widespread adoption of cloud analytics.

There are the standard issues in analytics applications, and the naysayers who do not trust the cloud for core applications, STILL, have something to say on the challenges. The fact that key business critical information will be stored and operated outside their corporate firewall does not go down well with a lot of enterprises. “Privacy and security are the major concerns that have contained the potential of cloud to a great extent,” says Garima Rai,Head of Marketing, Inside View technologies. Everything comes with a disclaimer and so does the cloud. Another adoption challenge with cloud-based apps is regarding interoperability and integrability. Even the smallest business today uses multiple applications and seamless integration between these applications is the key to operational effectiveness.”

Most enterprises agree that the challenge associated with analytics only get compounded with the draw backs of a generic cloud deployment, once it goes on the cloud. So data integration and structuring could pose a challenge, and Atul Batra, CTO – Manthan Systems says, “Some of the challenges associated with running analytics in general, and analytics on the cloud in particular,  include the difficulty of integrating data from a variety of diverse source systems, both business and infrastructure, both structured and unstructured. The effort and timeframe for executing analytics projects is directly proportional to the variety and complexity of data sources.”

Another big challenge to enterprise analytics is the time to execute an analytics projects and, in the meantime, managing associated risks. Traditional analytics projects have a high risk of failure since they typically take 12 to 18 months to implement and go live. Adds Batra,”The trend is now is “buy versus build” where businesses adopt fully packaged analytical applications on the cloud typically via a SaaS subscription model. The applications are tuned to be plugged into data sources and can go live in a very short timeframe. The applications come pre-built with all the required descriptive, predictive and prescriptive analytics use cases for consumption directly by business thereby providing high level of business value and ROI.”

While accepting that cloud analytics are the deal of the day, Mr. Moshe Kranc, Chief Technology Officer, Ness Software Engineering Services (SES), says, ”In the enterprise world, there are several risks to be considered:

• Security/Privacy: Since data management and infrastructure management in the cloud is provided by a third-party, it is always a risk to hand over the sensitive information to cloud service providers
• Security attacks may come from outsiders or from other tenants
• There are technical solutions, but it requires a leap of faith (and regulatory approval)
• Vendor Lock-In: It is very difficult for the customer to switch from one Cloud Service Provider (CSP) to another. This results in dependency on a particular CSP for service.

Despite these risks, most enterprises are running some applications in the Cloud, e.g., those applications that do not require access to customer-sensitive information.

The dawn of cloud analytics computing is still just beginning. Vendors are struggling with the challenges listed above and how to architect their software to accommodate the vision and needs of a true cloud environment. The good news is that SAS has a vision for the future that will meet and exceed all of these requirements.