Infotech Lead Asia: The growth in information volume, velocity, variety and complexity, and new information use cases is making the role of information governance increasingly important.
Gartner has identified the top technology trends that will play key roles in modernizing information management (IM) in 2013 and beyond.
The ability to share and reuse information using real-time channels and mobile devices has become crucial. New internal and external sources of information must be available for delivery through varied, multiple and concurrent.
According to Gartner, big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making. As the volume of data increases, so does the need for innovative processing solutions for a variety of new and existing data.
IM is a discipline that requires action in many different areas, most of which are not technology specific. An enabling technology infrastructure that helps information producers and information consumers organize, share and exchange any type of data and content, anytime, anywhere is essential. Such an enabling technology infrastructure is what Gartner calls a modern information infrastructure.
Organizations that establish a road map for cohesive, application-independent and information-source-independent set of IM technology capabilities are best placed to achieve long-term enterprise IM (EIM) goals.
Semantic technologies help extract meaning from data, ranging from quantitative data and text, to video, voice and images using techniques that have existed for years and are based on advanced statistics, data mining, machine learning and knowledge management. As businesses begin to look at information as a strategic asset that can be monetized, semantic technologies are garnering more interest. Semantic technology makes sense out Increasing volumes, variety and velocity — big data — in IM and business operations.
Data warehouse (DW) architecture is evolving from competing repository concepts, to include fully enabled data management and information processing platforms. These new warehouses support transformation and integration. It introduces a governance model that is only loosely coupled with data models and file structures, as opposed to the very tight, physical orientation used before.
Data analysis can be done by commercially supported NoSQL DBMSs and open-source projects that have only community support. The latter remain immature and are used by Web developers for applications that are not mainstream.
Commercial products use their added funding to build sales, support and marketing and add enterprise-class features intended to widen adoption and win new business. Due to limited awareness, leading players stay away from the direct sales field and are slow to penetrate corporate IT strategic plans. As a result, business impact in 2012 was moderate, but in 2013 is increasing as more organizations investigate and experiment.
In-memory computing enables user organizations to develop applications that run advanced queries on very large datasets, or perform complex transactions at least one order of magnitude faster than when using conventional architectures. In-memory computing makes way for business innovation and cost reduction.
EIM requires dedicated roles and specific organizational structures that have specific roles, such as chief data officer, information manager, information architect and data steward. The fundamental objectives of the roles remain to structure and manage information throughout its life cycle, and to use it in the best possible way for risk reduction, efficiency and competitive advantage. Enterprises that take the initiative to create these roles, and to train for them, will be the first to benefit from information exploitation.
Governance of data is a people-and process-oriented discipline that is a crucial part of any EIM program. This means that this technology is needed to help formalize and combine the day-to-day stewardship processes of (business) data stewards into part of their normal work routines. The continued high growth and interest in master data management (MDM) programs and other initiatives, such as data quality improvement and broadening information governance goals, are also driving demand is driving interest in such technology.
Information valuation is the process of assigning relative value or risk to a given information asset or set of information assets. It is important to treat information as an asset and value and treat it as such. Organizations have begun to approach information valuation more formally.