Big Data Unleashed Part 6: Dream Big When Cloud Meets Big Data

Darren Cunningham of Informatica described a pivotal transition happening in an enterprise on Sandhill.com – From Cloud Skeptical to Cloud Curious to Cloud First. “For most people working in IT organizations today, cloud computing is very much the here and now.” But it wasn’t too long ago in most organizations that cloud computing was the point of contention:  business could not wait for IT to deliver what they needed so they tried to get up and running faster by resorting to cloud implementations.  Faster and cheaper was the king.  Many IT organizations were in a state of turmoil about how to respond to this possibility of cloud computing (and specifically software as a service (SaaS) applications, potentially making their jobs irrelevant.  With increasing economic pressures to content with, CIOs were asked to explain what cloud means to their organizations and present their plans to outsource applications, platforms and infrastructure to cloud providers.  Meanwhile, business executives were thinking that they could access better, cheaper, and more reliable services via cloud applications.

While it’s true that for many organizations these cloud politics are still the reality, just over half way through 2011, it’s apparent that line of business (LOB) adoption of cloud-based applications, including customer relationship management (CRM), sales force automation (SFA), human resources (HR), expense management and others is higher than ever. What might not have been obvious in the early days of cloud adoption is how Hybrid IT would become the new normal. Now the business impetus to leverage Big Data is fueling the need for IT to become more flexible – managing both cloud and on-premise business requirements.  Not surprisingly, interest in all aspects of cloud data management is also on the rise.  With big business expectations around Big Data, here are five reasons why it is an opportune time for IT to embrace the Hybrid IT reality by taking advantage of data integration delivered as an on-demand service:

  • Speed of on-boarding new data sources – Big Data means a greater variety of data.  Business now expects that more data types are incorporated into decision making and operational improvement.  The cloud is a highly virtualized infrastructure and helps Big Data projects complete faster. Furthermore IT is looking for more agile ways to integrate data in a variety of ways to accelerate onboarding of new data that can be in the cloud or on-premise.
  • Multi-tenant, scalability –To manage Big Data, hybrid IT must be ready to provide continuous availability of up-to-date, relevant data to the business. This requires mission-critical scalability for data integration, replication and synchronization tasks with high volume and uptime requirements.
  • Interoperability and control across on-premise and cloud applications –Big Data projects are also about connecting existing silos of data repositories and systems.  So interoperability across on-premise and cloud applications and platforms is the key. Business analysts need to rapidly specify mappings and submit to development for completion and deployment on-premise while developers can build logic and provision to Business analysts in the cloud to complete tasks without losing governance and control.  It is also important to ensure that business analysts can detect data quality issues and correct them as part of the data and analytical processes.
  • Enterprise-grade security– One of the inhibitors to cloud adoption has been the concerns from IT about security and governance. The need to rapidly integrate data across the enterprise securely with proper versioning is getting escalated as more organizations are incorporating Big Data. It is crucial to have an on-premise data integration solution that is compatible with cloud data integration services via a secure, downloadable agent that provides local access to applications, databases, and files.
  • Enable various business models– With Big Data, organizations are experimenting and deploying business models that vary from highly distributed to centralized, and somewhere in between.  With the ability to embed data integration natively into cloud stacks, IT is now empowered to deploy on-premise and cloud applications to respond to such business changes.

A Hybrid IT organization is empowered to take advantage of the best of both worlds – public/private cloud applications, platform and infrastructure services that are tightly integrated with on-premise systems. In the same article, Darren Cunningham interviewed Andrew Bartels, Director of IT at a US financial services firm who explained the change taking place in IT. He responded:

“With the evolution of solutions like Amazon Web Services (AWS), salesforce.com and Informatica Cloud, my thinking has evolved to the point where I believe corporations can build out their entire application infrastructure in the Public Cloud. With the deployment by AWS of their Virtual Private Cloud Solutions along with third-party vendor solutions like CohesiveFT’s VPN Cubed solution for AWS you can not only build out a private and secure private virtual infrastructure, but you can ensure security and deploy encryption between nodes within that infrastructure.”

The bottom line? Now is the time for IT innovators to rethink their information management portfolio and envision how their overall architecture can evolve to tackle Big Data – both on-premise and in the cloud.

To discuss more, please visit Informatica booth #1115 at Dreamforce ’11, August 30- September 3 in San Francisco as Darren and other cloud experts are looking forward to meeting with you to explore and learn your cloud computing strategies as part of hybrid IT.

This entry was posted in Big Data, Cloud Computing and tagged , , . Bookmark the permalink.

Leave a Reply

Your email address will not be published. Required fields are marked *

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong>