Traditional Data as Category of Data Analysis
Data means collecting different from different resources. This is the starting phase of data science. Firstly, Data is classified in two broad senses:
A. Traditional Data :
B. Big Data:
In this Blog, I am going to tackle the answer to the question “When, Why, What, Where, How, Who” about traditional Data.
Traditional Data is based on a fixed schema( representation of a plan or theory in the form of an outline or model) that is static in nature. This deal with the less and small amount of Data in a simple and structured form. For example, the data is in table format. This is the step to be applied while collecting the data.
“You may have Questioned about why the traditional type of Data is necessary?”
This type of Data is required because different data-driven decisions do not work on unorganized data, it requires well-organized data which is stored in a digital format with mismatched order. It requires preprocessing after the collection of data before storing it in the dataset. The preprocessor is the method or operation which is done before the main process occurred. It consists of class labeling and data cleaning: In which data cleaning of the combined form of categorical(Data on which the mathematical analysis cannot be applied) and Numerical(Data on which mathematical operation can be applied easily).
Data cleaning refers to removing some data with missing suitable values. This is a general idea but the specific data balancing and shuffling (the shuffle here ) come into the picture.
The answer of Where: This type of data is mainly found in small-scale companies, static websites, Basic Customer Data, and historical price Data.
This type of data can be obtained by the use of tools SQL(structured Query language), and Matlab (as the programming language). The most common use software is (excel ) be used.
Who: Data Architect, Data Engineer, and Data administrator use the traditional for the operation of the collected data from the different resources for the further processing and manipulating of the data.
In summary, traditional data is used before data analytics, it is used because the data-driven decision takes the well-organized data. It refers to data preprocessing(a task done before applying the real operation on data) including data cleaning, dealing with missing values, and the specific balancing of the data. Such type of data is found in the static website and the historical stock price. The language for this manipulation (python, Matlab, SQL) and Excel as the software is used by the Data Architect, Data Engineer as well as Database Administrator.
I am sure that You got the Answer to all the above questions.