The explosive growth of the ‘Internet of Things’ (IoT) continues to generate an ever-increasing volume of data, from sources as diverse as industrial equipment, smart appliances, and fitness trackers. Similarly, business processes have become increasingly distributed, and often involve personnel and resources in multiple teams and locations, which results in a higher volume of more complex business data. These challenges have led an increasing number of businesses to find new ways to improve their data management strategies.
DATA CHALLENGESData-driven businesses require proactive data management strategies
According the 2016 Global Data Management Benchmark Report from Experian:
- 23% of customer data is believed to be inaccurate.
- All types of data errors increased from 2015 to 2016.
- 75% of businesses say they can detect and resolve data issues in a timely manner.
- 65% of businesses say they wait until specific data issues are identified before any action is taken to fix them.
- Over half of all polled organizations attribute these data errors to human mistakes.
Unfortunately, instead of addressing the vast number of challenges associated with managing information in large organizations, most technology solution providers focus on a very narrow range of data-related problems. Their solutions often rely on outdated, multi-million dollar legacy technologies with high maintenance costs that take months or even years to implement, and often lead to unforeseen problems of their own in the long run.
Our Client Work Done Analytics, Distribution Optimization, Supply Chain Management
PURPOSE-BUILT SOLUTIONSData management technologies that dovetail with existing business processes
Many expensive software packages promise to solve all of your data management problems. Purchasing solutions of this kind might seem like an easy fix, but they usually force businesses to modify their operational processes to conform to the requirements of specific software applications. At Visionet, we believe that technology should adapt to the needs of users, and not the other way around. For this reason, our EDM strategy involves a thorough analysis of your business processes and entities, resulting in a solution design and implementation that align with your organization’s specific data management needs.
Visionet believes that it is essential to take a long-term, holistic view of how companies currently acquire, correct, use, and manage their data, as well as how these processes should be implemented – Enterprise Data Management (EDM). EDM is a centralized collection of activities that a business uses to manage its data, processes, and rules with the fewest number of data stores and the most cost-effective technologies that produce positive results. Visionet’s EDM approach centers on making your information more valuable to executives and other decision makers in your organization, and is based on the four strata of enterprise architecture in the TOGAF Architecture Development Method: Business Architecture, Data Architecture, Application Architecture, Application Architecture, and Technical Architecture.
HOLISTIC APPROACHA comprehensive understanding of your data management needs
Visionet’s holistic approach to EDM is driven by the belief that:
- Nothing can be improved unless it can be measured.
- Specific data quality improvement goals can be achieved in weeks – not months or years.
- Unless already purchased and in-house, data quality improvement should always begin with no-/low-cost open source software.
- Only move to expensive options when gaps in open source alternatives cannot be overcome.
- For true EDM, all company data must be aligned around a single semantic data model, i.e. what things mean, and not their technical details (size, format, etc.)
For these reasons, we always begin our EDM engagements with an assessment of the current state of your technology infrastructure, your goals and objectives, and any restrictions that might become limiting factors. In order to minimize deployment time and avoid unnecessary expenditure, we use all existing assets identified in the technology assessment that satisfy your business objectives instead of blindly introducing new technologies. The assessment also generates a hierarchy of semantic entities that are pertinent to your business, and we use this semantic model to ensure that your data is organized and processed in ways that best serve the goals of your organization.