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It eliminates some anomalies and allows more complex data to be analyzed. Some of these exceptions can be displayed as deleting data, inserting more information, or updating existing information.
So what is standardized data? It is not difficult to find a definition for data standardization, but settling on a specific definition can be a bit complicated. With all interpretations, data standardization is essentially a process of reorganizing data in a database in this way so that users can use the database appropriately for further query and analysis.
There are some goals to keep in mind when performing the data standardization process. The first is to remove any duplicate data that may be present in the dataset. Doing so effectively eliminates any redundancy that might occur in the database. Redundancy has a negative impact on data analysis because these values are not fully required. Removing this data from the database helps to clean up the data and make it easier to analyze. Another purpose is to organize the data logically together. You want to store the relevant information. This can happen in a database of data specifications. If the data are interdependent, they should be very close.
With a comprehensive overview, let's take a closer look at the process itself. Although this process may vary depending on the type of database and the type of information being collected, there are usually some steps that need to be performed. Such steps are repeated data as described above. The other step is to resolve all conflicting data. Sometimes there is conflicting information in a data set, so data normalization is about resolving this conflict before moving on. The third is to set the data format. It requires data and puts it into a format that allows for further processing and analysis. Finally, the data is standardized and integrated to form a more orderly structure.
Let's look at the state of big data today, and how much of it is unstructured. Today, it is necessary to organize and put it into a structured form, and data standardization can help achieve this goal.
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