Archive for Cloud

The big issue in enterprise big data: linking massive number of data islands

 

Reports are coming on studies that suggest organizations started to see the opportunity and benefits of big data technology adoption for driving business decisions (Forbes on IDG survey). While IDG survey suggests that the investment related to big data analytics in the enterprise will increase steadily in 2014, other surveys still do not show signs of rapid growth in investments by organizations (CNN iReport on Bain & Company survey).

The real issue that may be underlying this observation is the nature of big data problem in the enterprise that have to be understood and addressed to support greater adoption. The enterprise big data is characterized as enabling analytical tools and technique to process large volume of data efficiently (mainly on top of the stack of HDFS, Hadoop, noSQL, etc.), however, arguments emerging that the enterprise big data problems is not about size, or even small data analysis is the next big thing, and the fact the loosely coupled small data could be more interesting aspect of big data in the enterprise.

Philippines-Hundred-IslandsWhile I strongly assert the importance of small data in the enterprise, I would go a step beyond by saying the big data problem in the enterprise today is how to make sense of massive number of data islands, a lot of small and some large, some centered around employees and generated by them, some shared in group settings using sharing and social media inside the enterprise, some stored in large enterprise application databases and document repositories and other information outside of the enterprise wall that the enterprise may care about to serve their customer better. The overarching problem in this context is how to link this data, interpret and understand it and make it available for data and business analytics purposes.

One trend to watch for in this space is development in the graph databases and graph knowledge representation, and how they are evolved to intelligently discover entities, and their relationships and make the graph available for analysis. The graph database providers are focused and advanced a great deal in improving the performance of data analysis on top of knowledge graphs, but more innovation needed on forming knowledge graphs over data islands.

Casebook: analytics and social collaboration to support adaptive case management in the enterprise

While advances in collaboration and communication technology have facilitated interaction among people, the main burden of managing the work is left on knowledge workers, as the collaboration and communication tools are un-aware of the work context. In addition to the heavy use of communication and collaboration technologies by knowledge workers, case management is supported by tools from vendors in the business process management, enterprise content management and customer relationship management domains, each tailored their solution to fit specific case management domains. The new push towards adaptive case management aims to bring flexibility, adaptability and responsiveness to the practice of case management.

The state of the art in technology for supporting case management can be described as systems of record: they rely on people maintaining consistent information, using disparate applications and manually tracking pieces of information related to a case across different systems. These case management applications do not support knowledge workers in a flexible and adaptive manner. As a result, substantial information related to cases lives outside the applications, and is isolated and fragmented. Often it is archived in the personal inboxes of knowledge workers without being shared within the organization. This results in complex and inefficient work practices due to the lack of systematic support for knowledge-intensive and people-driven processes, as well as the lack of proper means for capturing and sharing knowledge within the organization. Consequently, organizations fail to learn from the experience of previous cases and struggle with information loss during hand-offs between individuals and teams.

We argue that any solution for adaptive case management should be centered on cases and embrace advances in social and collaboration technology, analytics and intelligence in order to advance the state of the art in case management from systems of record to systems of engagement. In such a future state, while people continue to drive the work, they are able to actively engage and interact with other people and information entities in their work environment. Semi-autonomous systems can offer intelligent and automated support to workers to free them from record keeping and provide them with guidance on case handling. Such a system should be adaptive to changing work practices, keeping the workers informed about the latest updates and share the right information with the right people at the right time to foster collaboration among colleagues, partners and customers.

Continue to read our following article on Casebook as a system of engagement for adaptive case management, and specifically on how it leverages advanced analytics and social collaboration technologies to address the quality, consistency and efficiency issues in existing case management systems by automatically capturing and codifying flexible processes, so that teams can benefit from process evolution and enhancement (published in Sept./Oct. 2013 issue of IEEE Internet Computing titled “Casebook: A Cloud-based System of Engagement for Case Management”).

The Future of Enterprise IT and CIOs in the Cloud World

Enterprise IT has witnessed a series of changes over the past decades. With the rapid move towards adoption of cloud services, the impact of changes on enterprise IT has never been more profound. This is changing the traditional role of enterprise IT as the main entity for providing and supporting IT systems and services to becoming a broker and manager of IT services for a hybrid portfolio of IT services acquired externally or provisioned internally. Currently, much of IT service innovation in cloud services domain is focused on the service provider side. Not much attention has been given to the challenges at the service consumer side for designing, acquiring, operating and managing a portfolio of services.
In the following article, we discuss the trends and the changes that cloud services bring to enterprise IT and present a framework for a novel technology solution that supports the service consumer role of IT (published in IEEE Computer, and slightly modified version available as an HP Labs Technical Report)