Data-redundancy: A method fraught with risks

Business-world today is fraught with uncertainties and in a bid to counter uncertainties, the dependence on data has overwhelmingly increased. Businesses are heavily involved in collecting, processing and utilizing various data and information to carve their own space in the market. But then, data-cleansing and filtering, data-visualization and data-efficiency, all of them become so important; otherwise data-redundancy is also a reality existing in the business-arena.

Data-redundancy is a term which defines repetition of data in a database at two or more different places. A composite multiple software-platform or a single database, anywhere if there is a recurrence of data, it is called data-redundancy. The deluge of data at every level in businesses or the propensity to grab as many of them as possible makes it sometimes an inadvertent event. And sometimes it is done on purpose as a conscious step to construct a structure of a solid backup in case of an emergency or recovery.

Different facts and figures are your tools to gain insights on different facets of your business. If their repetition at different places helps you solve some specific problems, data-redundancy becomes an effective method to leverage on data. If analyzing the business-course becomes easier with the data-redundancy, then it is a good process to have to manage the database. But if it occurs without any proper need and due to disorganized and clumsy coding, it becomes unwarranted and waste of resources. Sometimes, convolution or vague processes present in the database-management also cause data-redundancy.

There are different schools of thoughts as far as the utility of data-redundancy is considered. But on the whole, if you have a solid system to preserve your data, you don’t need their repetition at other places. Storing them in varied places may confuse a specific analysis. Updating them all through a central access point can keep you away from the confusion. But, why not keep the data secured and have a proper data-filtering to keep the system efficient! If not, then data-redundancy can push you to data-discrepancy and inaptness, which would further jeopardize your business and efforts.

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