The technological advancement and globalization has surely benefited the business environment immensely. While the use of advanced machinery, optimum use of resources and quick access to information has made many companies achieve great heights; competition, corporate scandals, sudden machinery downtime, administrative and technical changes often obstructs the growth of businesses. Though some of these setbacks can be avoided or managed with effective planning, preventive measures can see the light of the day only when the information used is reliable and consistent. Accessibility to quality information is a necessity for every business organization. Though companies can use data quality management tools to improve the quality of allocated information, it is important for them to first estimate the quantity of poor data that lies in their system.Before implementing a master data management software to cleanse data, it is important to understand what is quality data and the effect of bad data present in the company’s repository. Clear understanding of the business requirements is essential to derive appropriate solutions. It can be alarming, if the email addresses of most of the customers are missing in the customer service catalog. However, the situation wouldn’t be that grave, if the email address is not used for communication purpose or if the process does not require them for operations.In order to analyze and evaluate the quality of data, you should ask your business the following questions:Was the information properly fed into the system at the origin?
Was the information maintained as per the strategy proposed by the team?
Are the objects identified clearly? Does all the information known about an object helps provide an accurate representation of the object?
Was the data utilized and decoded properly at the time of access? Has the data been updated recently?
Based on the technique the organization uses to create and understand data, can the same data be used between two systems?The first step of Mro data cleansing starts with the analysis of entry quality. Though its often easy to identify the problem at this phase, it is difficult to correct. Entry issues are mainly caused by manual entry of data. Typo errors and false information create confusion and corrupt the data. Profiling tools and queries can be used to fill the missing information. Again its important to analyze if the missing information is required for the business processes. If the missing values create less impact on the business growth then their existence can be ignored.Verifying the quality of data at its source can be difficult, if the data is sourced from third parties. There are many applications that provide internal information at an additional cost. The companies can use these services and get updated information. However the simplest of all is to ask the individuals who fill the data into the systems to cross-check their authenticity. This way corruption of data can be prevented at the origin itself. To enhance the quality of data and get an organized database that meets the business requirements, companies should make effective use of master data management tools.