Significance of Data Reduction for Optimization of Customer Data

Jul 26,2021 by Manoj Yadav

In modern data driven business scenario, almost every organization is found to retain customer data in terms of purchase or browsing history, personal information, and so forth. Although, this may sound to be a prudent approach from a variety of perspectives, there are grave concerns to be addressed including costs and other issues. 

Time has come to relook into data storage policies because such an approach can severely impact confidence of your customers who may not appreciate the idea of their personal information being stored by a commercial organization, falling into wrong hands of cyber criminals. Moreover, one should also consider huge costs of securely storing such voluminous as well as sensitive information 

Cost considerations

Growth in data storage requirement is always directly proportional to the business growth. This can be attributed to following factors:

  • Addition of new customers
  • Growth in personal data pertaining to past customers

The rate of growth can be extremely higher than imagined, thereby putting severe strain on the budget for storage and security of the customer data. Sustained growth in data can even exceed the storage space offered by some of the most well equipped data centers.

Customer data needs a large array of support systems in addition to servers and high security storage systems. You should also consider staffing expenses for hiring programmers, sysadmins, and administrators of databases for management and handling of the data. 

Cost of secure storage

One of the most concerning aspects of storage costs is related to provisioning of security measures for maintaining integrity of the customer data. No enterprise is immune to cyber attacks or hacking attempts and these events have potential to bring the organization to standstill, apart from loss of customers’ trust and confidence. 

According to a well documented research the normal cost incurred for every customer records that is compromised, can cross one hundred dollars. Although, the cost per se may not ring warning bells, one must consider the extent and volume of data breach with potential of impacting thousands of records in a single year.

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Mitigation of data footprint

Reduction of data storage costs can be achieved only by implementing shrinkage of data footprint. Conventional data storage applications may not be ideal for combined accommodation of data that is exponentially growing due to big data and traditional data.  

Dark data is also an extremely overwhelming factor which gives rise to incremental costs of data storage. It is generated due to presence of semi-structured as well as structured data files. Dark data is also produced by unnecessary and uncontrolled multiplication of data that resides at several locations. 

A large number of files may remain untouched for years, thus adding to the ever expanding data footprint. There may be regulatory compulsions for retaining some data files. However, on should try to get rid of excess and unused data files for reduction of data footprint. 

Data archival is a reliable way to minimize data bloat effect. Large volumes of unnecessary data can be responsible for consumption of more power and other utilities. It has been observed that four out of ten files deserve archiving. Data storage space can be effectively optimized by archiving and de-duplication processes. 

Duplicated data can result in incorrect segmentation of markets or sending same emails or other forms of communication to same customer over and over again. This can severely impact an organization’s reputation. 

Data costs can include the expenditure incurred for management, migrating, processing, archiving, securing and accessing the data. It is highly difficult to compute these costs. However, one can simply find ways to reduce overall data footprint for an assured cost reduction.

Data reduction techniques

There are a number of technologies available to achieve data reduction including the data deduplication to get rid of excess data. This is the most sought after technique for eliminating redundant blocks of data.

Other blocks of data can be modified to facilitate sharing by other files and moved to caches or memory. Data archiving eliminates rarely used data and can be leveraged by using cloud storage or disk based storage systems. 

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Elimination of excess data by way of deduplication is usually related to secondary data storage. However it can also be applied to primary storage by using many systems of flash storage. 

Compression is yet another way of reducing data footprint. It attempts to minimize an overall size of the file with removal of redundant data so the resultant file would require smaller space. It is achieved by using formulae and algorithms that are compress data by identifying and removing the excess information. Most of the advanced storage systems offer this as a default facility. 


No matter how many customers you propose to serve, you cannot afford to let your data being hacked or breached. Redundant and vulnerable data adds to costs and even multiplies prospects of losing reputation. Data reduction aims at reducing costs by securing business continuity. 

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