Failure is integral to data projects
Sometimes it is difficult to understand the value of new products or technologies. Originality comes with its set of struggle and failures. Several IT projects falter and are deserted in the hope that new ones will not hit the paver blocks. Even the genius musician Mozart said, “I have never tried to be original. I simply built upon what others have done before.” Likewise, even Thomas Edison said, “I have not failed but found 10,000 ways that do not work.” Any IT engineer who is stuck on the master data management journey should relate to these expressions. Today, the amount of big data that is emerging fast and furious has created several disruptions. Failure in some projects is an open secret. But experiments need to continue.
Some lessons are worth learning during this difficult trip. It is wise to build on the failures of others as they will guide the data project.
Adapting to the changing face of MDM
All technologies that come within the framework of data management practices in an enterprise can be clubbed together. This encompasses all company information that is related to the clients, vendors, products prospective business deals, networking, and securities. The entire information eventually pertains to all the end users and applies to external and internal sources of data.They also relate to social media and other online channels. There are some trends that have forced enterprises to make changes. The trends have emerged due to the information that the Big Data reveals. The emerging patterns make the enterprises to switch their strategies and re-engineer the systems to align with the master data management. Some of the changes that have evolved have thrown up some lessons for leaders.
The domains where the MDM trends (or hard lessons) have come fast and furious are:
Safety and security of data keep any enterprise on its toes. This is one of the motivating factors that make one switch to cloud technology. All the information is safe in the cloud rather than onsite where it can be tampered with. As a leader, choosing systems that are aligned with this system should be adopted. All data can be transferred from the internal servers to the cloud. Not all industries seem to be receptive to this idea. Customer-sensitive information is still locked on site and guarded by vigilant IT teams. But this depletes the resources as new ways are being used by hackers to break through or attack servers. Financial institutions, banks, and large stock exchanges continue to buck the trend. They may need to learn lessons from breakaways, attacks, and compromised data (like passwords, pins, or personal details) of their clients. Many software vendors try to introduce projects were integrating network designs to insulate the data on site with SaaS. It is now best to switch to a more hybrid technique to manage the data.
Today a single product design is not sufficient to manage the entire data of an enterprise. Certain legacy disruptions breakdown and result in failure. One cannot combine the customer data and product data together. One requires an entity solution, and the other requires a semantic string. It becomes essential for the vendor to provide products with diverse capabilities. This is another area where failures occur and projects are abandoned. Master data management requires a mesh of several products that can be tailor-made for an enterprise. It will need to create a synergy that works in a very niche integrated system. This is one way of ensuring that resolutions can be found when any data errors occur. The resolutions also need to be in sync with the relationships with the other entities.
Addressing government policies and other regulations
Vendors are required to develop systems that will not clash with the existing systems approved by the law of the land. One big disruption that is still evolving and clashing with the authorities is the blockchain technology and the cryptocurrency sectors. Any enterprise that closely works with a relationship resolution stands to gain. This is another hard lesson that is tumbling or cascading down on enterprises. The resultant data needs strict and controlled management. Regulatory frameworks continue to block technologies that do not meet their rules. Any data management framework that hovers around illegal activity can be detrimental to the enterprise.
Ensuring data stewardship
Data loss can be very disappointing and affects the entire enterprise network. All systems need to ensure that the data is available for analysis and reviews. It can be used at any location and used with integrity. In such a scenario, a core hub or a central place will be instrumental to MDM.
When these lessons are learned, automation and experimentation get a green signal. It is time to turn into the Edison or Mozart that your company needs.