Data matching is the comparison of computer records from two or more different sources. The process is based on programmed loops or algorithms, otherwise, it can be done in several different ways. For example, a retired person is drawing unemployment benefits or welfare and he is also appearing in a list of employees currently employed by the federal government. There is a possibility that he is drawing benefits fraudulently, or the deviation might be the existence of the person in one data set and absence in another. These searches mostly involve in looking for matches among hundreds of millions of records, and the government uses these matches to increase the revenue and to control the cost. Many countries are using matching to detect possible cases of abuse and fraud.
In United Kingdom, a data matching project has reviled that more than 6,000 ineligible immigrants are receiving benefits in the country. In UK, the government undertook the exercise of using data matching software on tax, benefits, and border control data. The results stated that around 361,000 claimants of benefit were non-UK nationals when they applied for a National Insurance number.
Configuration of Data
It configures the sources that are more trusted than others to score high and this enables the configuration of field level priority, to get more trusted data for a particular area. The professionals refer this concept as the trust framework because it has the ability to work well for acquisitions and mergers. It can be also applied, where connecting disparate, yet potentially duplicate data source is essential.
Searching involves the implementation of master data management by using the cloud, through this process it is easy to search duplicate as they enter. It matches with the batch job settings to identify the duplicate and then enter this logic into the search of records, to provide the details of possible duplicate at the point of entry.
Those businesses who have limited funds are found to be wasting a large number of their limited resources by using wrong records to get in touch with organizations and people. The main focus of data matching is to improve accuracy levels, across every section of a company and to increase the efficiency of operations as a result. Data matching can be used by organizations that are operating in diverse sectors such as banking, retail, marketing, and education. Every single organization relies on computing to survive nowadays and they likely to have a vast database, where a new information is added to the databases every day. To keep the useful and relevant data, it is important for the organization to use cleansing and matching tools regularly.
Everyone is connected to the internet through a computer or a smartphone with a unique MAC address and a traceable, non-unique, IP address. A person collaborates using specific identifications like email addresses, and the dates and time of communications are pretty easy to compile. To acquire the answer for their big question, the organizations are focusing towards big data because many leaders think they will unlock the secrets of data which reveals more profit-making opportunities
What is Record Matching?
Record matching is something that helps in finding the duplicate records in the same database, or it can crossmatch in other databases also. This enables an individual to join databases together or allows the databases to connect with each other, which simply raise the amount of automation that can be used at work. Following are the benefits of record matching:
- The deterministic record matching helps in recognizing a record by using a unique string of characters. For example, a bank account number refers to one account at the bank, and government departments often find the information using national insurance number or unique transaction reference. This is an example of a one-way search and a simple data match.
- The fuzzy record matching helps in finding a non-identical duplicate record by matching a common piece of data, although they may not be alike. Any information is usable as long as, it is in both the records, but it is important to check secondary information to make sure that the record is duplicate and not an incorrect positive match.
- It releases the staff from the routine
- It links the systems together.
- It reduces the waste.
- It makes databases leaner and purer.
- Limited budgets are used effectively in this process.
Record matching can also be used in cleansing the terminated duplicates. To create a single record view, a person can match and merge the multiple records to enhance the quality of data. Record matching has many names, it depends on who is talking about it. Some people call it data linkage or record linkage.
More Benefits of Data Matching
Efficient Database with Data Matching:
Data matching can be used commercially, to identify the shopping habits of a consumer in order to build a strong relationship with them. Data matching is also useful for the government departments, as it helps in finding any inconsistencies that are alarming. Data matching allows the organizations to keep their inaccuracies to a least as with a large amount of data, chances of errors are high.
- The organizations who are working in various sectors, data matching is a powerful tool for them as it provides a higher level of accuracy.
- Data matching helps the organizations to save a large amount of money but removing the inaccurate records from the systems.
- The data matching software’s allow the companies to correct several records within seconds.
- It helps the government to check for fraudulent activity, in order to save public money.
Data matching is vital for any organization of any size, saving resources and increasing customer support is essential for any company, from a multinational to a local food chain. Many organizations are using both fuzzy algorithms and data matching to make sure that each can provide a fast and reliable service. It is a tool which helps keeps incorrect records away from choking the business.