The field of Data Science and its study is totally incomplete without ‘data’. Though used as an individual word ‘data’, it hides a huge amount of importance and meaning in it. As we know, data is nothing but a piece of information, whether in raw form or derived as structured. But this data can be collected, visualized, analyzed, processed and then used for big and small purposes in industries. It will not be wrong if we say that data is a fundamental unit of the whole data science field and an integral part of cornucopia industry. It is because of this fact that it takes a lot of hard work to actually derive important information from raw data and these hardships are done by the data scientists, analysts and many workers working for the same.
How the Data is Stored Actually?
We all say that data is a piece of information, whether structured or unstructured, and the information is derived from it and what not. A data can be in any form, as text files or as numbers or binary files. It can also be in the form of structured (a processed form of raw data which is stored in tabular form), unstructured and semi-structured. But the question is how the data is actually stored. There must be some techniques or methods that can be used to actually store these loads of data. All computers detect data, pictures, videos, sounds, text, images, etc. in the binary form i.e. 0 and 1 bits. Being the smallest value of data, a bit represents a single value. This data is then processed by the CPU that uses some logical operations in order to derive new data from the existing source data. It is in the size of several Exabytes and Zettabytes. But as the amount of data continuously grows, the bigger units of memory are not enough to represent it. So, a new unit ‘Brontobyte’ is deduced which is equal to 10 raised to the power 27 of bytes of data.
VSAM and ISAM are used to store data in file formats (in mainframe systems). Further, Databases and Database Management Systems are used to smoothly store, manage and process huge loads of data.
Machine Readability
Apart from its numerous uses, data is also used to separate textual human-readable information from binary machine-readable information. For instance, there are certain applications that do this separation job between text files (files having ASCII data) and data files (binary data files).
Another important aspect of this is the Database Management System (or DBMS). All the data files that are having particular information regarding database and some other files like data dictionaries and index files stores information which is known as metadata (i.e. data of a data).
Resource Box
The knowledge and learning of data are never-ending and from the past several years, it has grown a lot in terms of importance. Hence, anyone who wants to dive in the world of data and is eager to know more can join a course of data science certification, Singapore.
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