Data science: conquerer of the world

Yes. Data is the most powerful tool today, in terms of agricultural, industrial, socio-ecological, economic, financial, science and technology. When you are dealing with such huge amount of data, it is important to know the standard framework in which data has to be organized. Data science uses the concept of algorithms that holds the abstract framework. To manage this, Business knowledge is required.

Types of business knowledge that lead to a proper business analysis are:

• Company related knowledge: it is about the level of competitiveness, target market, revenue ratios and business process of the company.
• Industry related knowledge: it is about the industry your company resides in. When you are running a company of your own, you need to consider the regulations that keep updating and act accordingly. There might be few norms you need to follow, in a way that your data never goes against these norms.
• General business knowledge: it is the knowledge of the present standards of different industries, which is almost similar to industrial knowledge. But this adds on to the knowledge about the customer support count for efficient sales/service of your products.

A business involves several statistical and mathematical analyses, the profits and losses. Where do you store so much data? The repository called "database". It is an organized collection of related data. Data can either be processed or unprocessed here. Nowadays, data is stored in mobiles, personal computers that holds data upon simple software. Database represents data about the real world objects (or) according to textbook terms called the universe of discourse (UOD).

A database can be stored with a large number of data in it. For Example, the details of a large number of students and staff of a university. The data stored in it can be made up of categories. The reason behind this is because of the capability for easy access and retrieval of data. It is composed of various operations that can be done under it such as adding elements, deleting entries and updating the data already stored. All of these operations can be given to the computer as commands in the form of queries.

Components of database architecture-

• Database Definition: this consists of certain DDL (data definition language) statements along with a compiler that performs some preliminary operations on raw data and sends it to the stored database repository.
• Software: this is the software that is used to access the data that was previously stored in the repository. It provides all the resources that are needed for the operations and provides a platform for these operations.
• Query processing: this is where the user’s queries are processed. This also requires a separate software rather than the software for stored data. Resource box:
• As we see that the need for efficient processing of data by using DBMS and many such vast applications of data science is increasing day-by-day, the knowledge about such concepts is in complete scope and is a much-recommended career path. For this reason, 360DigiTMG brings up data science course, to help you build a better future of you and the future.
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Rajesh Mishra is a passionate blogger and digital marketer from India. He loves to share his ideas through this blog to help readers.