Tag Archives: cloud
Hosting Big Data applications in the cloud has compelling advantages. Scale doesn’t become as overwhelming an issue as it is within on-premise systems. IT will no longer feel compelled to throw more disks at burgeoning storage requirements, and performance becomes the contractual obligation of someone else outside the organization.
Cloud may help clear up some of the costlier and thornier problems of attempting to manage Big Data environments, but it also creates some new issues. As Ron Exler of Saugatuck Technology recently pointed out in a new report, cloud-based solutions “can be quickly configured to address some big data business needs, enabling outsourcing and potentially faster implementations.” However, he adds, employing the cloud also brings some risks as well.
Data security is one major risk area, and I could write many posts on this. But management issues also present other challenges. Too many organizations see cloud as an cure-all for their application and data management ills, but broken processes are never fixed when new technology is applied to them. There are also plenty of risks with the misappropriation of big data, and the cloud won’t make these risks go away. Exler lists some of the risks that stem from over-reliance on cloud technology, from the late delivery of business reports to the delivery of incorrect business information, resulting in decisions based on incorrect source data. Sound familiar? The gremlins that have haunted data analytic and management for years simply won’t disappear behind a cloud.
Exler makes three recommendations for moving big data into cloud environments – note that the solutions he proposes have nothing to do with technology, and everything to do with management:
1) Analyze the growth trajectory of your data and your business. Typically, organizations will have a lot of different moving parts and interfaces. And, as the business grows and changes, it will be constantly adding new data sources. As Exler notes, “processing integration or hand off points in such piecemeal approaches represent high risk to data in the chain of possession – from collection points to raw data to data edits to data combination to data warehouse to analytics engine to viewing applications on multiple platforms.” Business growth and future requirements should be analyzed and modeled to make sure cloud engagements will be able “to provide adequate system performance, availability, and scalability to account for the projected business expansion,” he states.
2) Address data quality issues as close to the source as possible. Because both cloud and big data environments have so many moving parts, “finding the source of a data problem can be a significant challenge,” Exler warns. “Finding problems upstream in the data flow prevent time-consuming and expensive reprocessing that could be needed should errors be discovered downstream.” Such quality issues have a substantial business cost as well. When data errors are found, it becomes “an expensive company-wide fire drill to correct the data,” he says.
3) Build your project management, teamwork and communication skills. Because big data and cloud projects involve so many people and components from across the enterprise, requiring coordination and interaction between various specialists, subject matter experts, vendors, and outsourcing partners. “This coordination is not simple,” Exler warns. “Each group involved likely has different sets of terminology, work habits, communications methods, and documentation standards. Each group also has different priorities; oftentimes such new projects are delegated to lower priority for supporting groups.” Project managers must be leaders and understand the value of open and regular communications.
Since the advent of middleware technology in the mid-1990’s, data integration has been primarily an IT-lead technical problem. Business leaders had their hands full focusing on their individual silos and were happy to delegate the complex task of integrating enterprise data and creating one version of the truth to IT. The problem is that there is now too much data that is highly fragmented across myriad internal systems, customer/supplier systems, cloud applications, mobile devices and automatic sensors. Traditional IT-lead approaches whereby a project is launched involving dozens (or hundreds) of staff to address every new opportunity are just too slow. (more…)
OppenheimerFunds Dreamforce Story: Lay a Foundation of Trusted and Complete Customer Information for Salesforce
Imagine you are rolling Salesforce out to more than 500 users today. What will be their first impression? Will they be annoyed when they encounter duplicate customer records during their first experience? Will they complain when they need to access other systems to get all the relevant customer information they need to do their job? How will that impact your goals for Salesforce adoption? (more…)
Just five years ago, there was a perception held by many in our industry that the world of data for enterprises was simplifying. This was in large part due to the wave of consolidation among application vendors. With SAP and Oracle gobbling up the competition to build massive, monolithic application stacks, the story was that this consolidation would simplify data integration and data management. (more…)
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. (more…)