Data Mapping is essential and one of the early steps of data integration. It creates a data map using unstructured, crude, raw data and helps in eliminating errors, reducing the wastage of storage space and decreasing overall computation costs. It leads to clean and good quality data by matching to weed out errors, repetitions and inaccuracies. Here are some of the top tools of data mapping as recommended by the experts.
Python Record Linkage Toolkit
Offering an extensive library and collection of toolkits, Python Record Linkage Toolkit is extremely useful to link records within internal as well as external data sources. It also provides a huge choice of accessories which are necessary for the processes of record linking and de-duplication. The way this toolkit was designed, it works best when used to analyze and link files of small to average sizes. It has advanced data manipulation tools, intelligent indexing methods, and a number of built-in data sets. These advanced features help it integrate its processes and link the necessary records directly with the data manipulation projects available. It has been designed to regulate and produce clean data using simple but effective techniques.
MapForce by Altova
MapForce, the data mapping tool created by Altova, is a powerful graphical mapping tool. It can perform data mapping and integration of offering extremely efficient results. What makes it such an effective tool is its extreme flexibility as it is designed to process with various data types such as Excel, XML, XBRL, JSON, Google Protocol Buffers, Database data and many more. Its unique feature is that it offers a user-friendly graphical interface which is more visual, and thus clearer to work with. One can map, and visualize, manipulate data, as well as execute complex mapping projects on a visual interface where the execution file or the source code is generated by this tool itself for recurring all the data conversions. All current data transformation codes can be imported and utilized as well.
Dedupe is a Web-based API library that makes use of machine learning techniques to implement the processes of de-duplication and entity resolution which is performed instantly on any given structured data. It helps to remove all the duplicate entries in a spreadsheet consisting of names and addresses. It is also designed to link a list of user information with another list consisting of its organizational history without the need for any individual customer id. This library processes instructions as fed by the data and creates a regulation as per the needs of the process. It is great especially for smaller companies and startups as it is designed to run perfectly on personal computers without advanced servers. It integrates itself to the user applications and runs this tool as a library, and maps data as per the client needs.
These are some of the most popular data mapping tools as preferred by industry experts. However, it is important to do thorough research, understand your own company needs and budget before you pick a data mapping tool or application.