Use data analyzing to achieve organizational excellence

For the usage of data in decision making and planning operations, it is necessary to ensure that the data is of high quality. Generally, when the volume of available data is high, the guarantee of the data being highly consistent in terms of quality is low. There can be simple errors in the data that can be rectified but with great difficulty. Quality includes the validity, accuracy and also the consistency of the available data for usage in specific purposes. It is absolutely necessary to make sure that the quality of data is high. Quality Improvement systems, tools and techniques aim at bringing the quality to its full potential. There are several tools that aid in Quality Improvement. • Profiling of data: The defects in a collection in terms of quality need to be calculated by carefully evaluating the data or profiling it. • Standardization: It is necessary to make sure that the data available qualifies set standards for better performance. • Linking: Comparing data for the purpose of aligning similar data by removing duplicity using fuzzy logic. • Monitoring the data: It is necessary to observe and keep a record of the variations in quality of data over periods of time for quality Improvement. To ensure the quality, consistency and to make sure that the data meets the requisite standards, along with the necessary rules and constraints, Data Governance is used to control the entry of data both by a person and by an automated system. It is a collection of methods that helps in managing crucial data. The principal government is to guarantee that low data quality leading to issues is accounted for. It is merely a set of rules, or guidelines to ensure efficient data management. Numerous Governance case studies regarding various functions of an organization are performed to evaluate and asses the current situation and implement new techniques for the improvement of Data Governance. The functions or the aim of governance is to increase the standards and the consistency in the data, to ensure and improve security and to optimize efficiency. Another technique called Data Cleansing that mainly involves finding errors and correcting or replacing incorrect or corrupt records from the main database. This method is used to improve the quality of data by removing or modifying even the smallest of errors. Data cleansing is mainly correction of errors by comparing to an existing list of correct records. These errors, mainly caused by entries from users can be made free of validation and other quality errors using Cleansing.