In simple words, data cleansing or the data scrubbing tools are the software applications which clean all the records and contact information present in the company database in order to make it free of errors and imperfections. They are highly essential in any business as the data is thoroughly analysed and is used as the key to the decision-making process. The detailed analysis of the data aids in locating the duplicate, irrelevant, incomplete, inaccurate and incorrect information entered, which leads to the inconsistent data entry. After finding the irrelevant data, they are removed, replaced or deleted to obtain the fresh set of records.
Why Use the Data Cleaning Tools
The best data cleansing tools migrate and integrate different types of data from various sources, which are competent with the master database. The enriched data helps an organisation in many ways. These can be listed as follows:
- Boosts the order tracking process.
- Manages the inventories.
- Enhances the relationship with the clients.
- Enriched data can be utilised in contacting the targeted consumers.
- Saves the time involved in searching the relevant information.
- Saves the funding involved in contacting the wrong person.
- Replaces the null values and fills the gap with the accurate information.
- Duplicate data is removed.
- Unwanted characters are removed from the database to make it appear clean and tidy.
- When a competent operation is used for scrubbing the data, it identifies the duplicate data in an expert way. It recognises the repetitive information even if the spelling and cases are different from each other.
- Case sensitive information is sorted and made according to the required case, as due to incorrect cases, data tends to get duplicated.
- Unnecessary tabs and spaces are removed to save the storage space.
- The confidentiality of the cleaned database is maintained by the data cleaning company.
- It allows the firm to maintain a high-quality of integrated data.
- Information of the clients is consolidated in a single place to access it easily.
- The data accumulated from different sources have various formats. However, after cleaning the data it is converted into the format of the master database.
- It maintains the internal integrity of the data, which can be considered as the most important function of the scrubbing operation.
The Techniques Involved in the Data Cleansing Process
A few business houses tend to ignore the data refining process, as the importance is unknown to them. But in the long run, it might lead to the inaccuracy and inconsistency of the data, which will promote various business failures and adverse effects that are irreparable. The process involved in data cleansing demands complex analysis along with the computation that is time-consuming and needs a considerable amount of activity. These processes can be explained by the below-mentioned points:
- Auditing – The entire set of record is analysed for the recognition of the incorrect information; this process is also termed as profiling.
- Workflow specification – Finding the irrelevant and inaccurate data that needs to be sorted.
- Execution of the corrections – The recognised errors are replaced and modified to get a set of data that is accurate, according to the standard of the firm.
- After processing the corrections – Once the revised data is obtained, it is checked again for the existence of any anomaly that was not detected by the automated process.
- Checking the data – The refined data in checked on a regular basis to identify any new mistake or error to maintain the accuracy.
- Avoiding the duplication – The emails and telephone numbers are strictly checked to recognise any repetition.
- Works irrespective of the size – The data is cleaned irrespective of the size, which is an additional benefit as this facility can be availed by any size of concern.
Another important aspect of the data cleaning procedure is to maintain the efficiency of the data obtained. If it is not maintained then gradually the accuracy will be lost and so will the efficiency.
Data Transformation Mechanisms
The market has various types of data transforming operations, which help in gaining the above-mentioned advantages. But, before selecting the best data cleansing tools for the enterprise it is essential to know the functions and advantages of those applications. Let’s check out the functions of a few data cleansing companies and tools in brief:
- Ab Initio – It is a high-performance software application that transforms the data with high efficiency.
- AMADEA – It extracts the data and cleanses it with the help of the program based reporting software.
- Analytics Canvas – It automates the insight data flow by interconnecting the various sources of the data. Along with this it also performs the calculation and refining in an expert way to obtain the data for storage and visualisation.
- Data Manager – In this mechanism, data mining is done after which it uses the windows GUI application for cleaning the data.
- Data Ladder – Primarily, it profiles, matches, de-duplicates and enriches the data to get an error-free resultant.
- Data Flux – It provides the data augmentation and profiling, which improves the quality of the data.
- Datatect – It is a very powerful operation to generate realistic test data by analysing the various programming languages.
- DQ Now – It provides a clear view of the data that profiles and cleans the data in an efficient way.
- OpenRefine – It is a very strong application to clean the messy and unorganised set of information. It also transforms the data into a required format and extends it with other web services.
- WinPure – It removes the duplicate data and also includes the email suggestion.
- ProMISS – It removes all the duplicate data very efficiently and replaces the null values with relevant information.
The best data cleansing tools have great importance in the successful operation of an enterprise. It not only provides accurate data to reach the potential clients with ease but also saves the time and money involved in contacting the obsolete consumers. In order to get the perfect information, the usage of these mechanisms should be increased along with the regular monitoring. As with the passing time the data is likely to accumulate unwanted errors, which is not desirable.