Individuals, companies, and even government departments are always trying to extract data from various websites so that they can have concrete information that can help in decision making. However, data extraction is not an easy undertaking as the amount of data from the target websites is so huge. Multiple methods have been brought about that can be used in data extraction. The problem is that most of these methods are very complex and time-consuming.
Simplified Data Extraction Techniques
However, there are new simplified data extraction techniques that have been brought about for companies and government bodies to use. The simplified scientific methods are being preferred because they can help in extracting a massive amount of data within a short period. Some of the experimental data extraction techniques include logical extraction and physical data extraction
1. Logical Data Extraction
Logical data extraction uses two methods to extract data from a vast amount of data. One of the methods used in logical data extraction is known as full extraction. This is a method that involves extracting data entirely from the source. This means that there will be no traces of data that will remain at the source after data has been extracted.
The information that will remain from the source will no longer be useful, which means that there will be no logical explanation as to why individuals should track any changes from the source. An example of full data extraction involves importing a particular table from the source as a file. This means that the table will no longer be seen or traced from the source. It will also be recorded as a file in its final destination.
The second data extraction technique that is involved in logical data extraction is known as incremental extraction technique. This means that all the changes that have happened from the source need to be tracked after extracting data. The problem is that tracing all the changes that have happened after extracting a particular file is a complex process. The best method of tracking changes is ensuring that a change table is created so that it can help in tracking all the changes that have occurred in a particular file.
2. Physical Data Extraction
The second method of data extraction is known as a physical extraction technique. This method uses two processes in the data extraction process, which are different but both methods serve the ultimate function of data extraction. One method of physical data extraction techniques is known as online data extraction. This means that one must be connected to the source so that they can be able to extract data from the source.
The work of a website scraper is one of the most common techniques that is used in extracting data from various websites. However, the process is only possible when there is internet connectivity. All the tools involved will only be able to retrieve data from the source if they are supported by the internet. The marketing companies mostly use online data extraction technique as they analyze social media marketing and the traffic flow in their websites.
The offline data extraction technique is a physical method of extracting relevant information from a particular source without individually connecting with the source. Most of the database use offline data extraction technique when they are retrieving necessary information from a specific source. This method of extracting valuable information does not require internet support. It can quickly be done when there is no internet.
Data mining is becoming one of the most critical aspects of different organizations around the world. Marketing companies want to mine essential details about a particular population, and it’s consumption habits before they can start marketing their goods and services. Data extracted helps various organizations and individuals in planning and also in making critical decisions. The simplified scientific methods of data extraction that have emerged will be a significant boost to those companies that are continually mining data.
Author’s Bio: Kevin Gardner graduated with a BS in Computer Science and an MBA from UCLA. He works as a business consultant for InnovateBTS where he helps companies integrate technology to improve performance.
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