DBMS basic terminology and concepts




Basic Concepts:
Data is organized in a data storage hierarchy of increasingly complex levels: bits, bytes (characters), fields, records, files, and databases. A character is a letter, number, or special character. A field consists of one or more characters (bytes). A record is a collection of related fields. A file is a collection of related records. A database is, as mentioned, an organized collection of integrated files. Important to data organization is the key field, a field used to uniquely identify a record so that it can be easily retrieved and processed.



Introduction to database

Every one deals with data every day. When anyone wants to listen to his/her favorite songs, he opens his playlist from the smartphone. In this case, the playlist is a database.

When you take a photo and upload it to your account in a social network like Facebook, your photo gallery is a database.

Databases are everywhere. So what is a database?  By definition, a database is simply a structured collection of data or you can say – a collection of information.

The data relates to each other by nature e.g., a product belongs to a product category and associated with multiple tags. This is why we use the term relational database. In the relational database, we model data like products, categories, tags, etc., using tables. A table contains columns and rows. It is like a spreadsheet.
A table may relate to another table using a relationship e.g., one-to-one and one-to-many relationships.
Because we deal with a large amount of data, we need a way to define the databases, tables, etc., and process data more effectively. In addition, we want to turn the data into information.


 SQL

SQL – the language of database SQL stands for structured query language. SQL is the standardized language used to access the database.
ANSI/SQL defines the SQL standard. The current version of SQL is SQL:2003. Whenever we refer to the SQL standard, we mean the current SQL version.



SQL contains three parts:


  1. ·         Data definition language contains statements that help you define the database and its objects e.g., tables, views, triggers, stored procedures, etc.
  2. ·         Data manipulation language contains statements that allow you to update and query data.
  3. ·         Data control language allows you to grant the permissions to a user to access a certain data in the database.


 MySQL

MySQL is an open source relational database management system (RDBMS) based on Structured Query Language (SQL). It is used to manage the relational database by exploiting SQL. Its name is a combination of "My", the name of co-founder Michael Widenius's daughter,[8] and "SQL", the abbreviation for Structured Query Language. MySQL is a database management system that allows you to manage relational databases. It is open source software backed by Oracle. It means you can use MySQL without paying a dime. In addition, if you want, you can change its source code to suit your needs. MySQL is pretty easy to master in comparison with other database software like Oracle Database, or Microsoft SQL Server. MySQL can run on various platforms UNIX, Linux, Windows, etc. You can install it in a server or even in a desktop. In addition, MySQL is reliable, scalable, and fast.


Difference between Data Mining and Knowledge Discovery (KDD)



Data Mining and KDD are the important terms that related to context of huge data. Before learning the basic difference between them. Let's have a look on DIKW pyramid.

 DIKW: It stands for the Data / Information / Knowledge / Wisdom pyramid. Sometimes it is also referenced as “DIKW Hierarchy”, “Wisdom Hierarchy”, “Knowledge Hierarchy”, “Information Hierarchy” or “Knowledge Pyramid”.

Data is a given fact or a set of qualitative or quantitative variables of a certain issue. These bits of pieces values are still raw, and is insignificant unless they are collected and arranges in a certain manner which will now give you an information. 
Information then is a collection of data, which can be used to answer a certain question or describe a concept.
Well knowledge and wisdom, are bit different from data and information, since
knowledge is the awareness or the conscious understanding of information or a concept. Thus, knowledge is more on the intellectual or cognitive ability of a being to possess and interpret information.
wisdom is usually defined as the application of knowledge. Wisdom is the used of knowledge to formulate a judgement or to make sense of a certain situation or concept. It is also used for formulate ideas, and the creation of new things.
Example: Imagine the string “WifiPassword”. The string alone is data. Understanding that it is a string is information. Knowing it is your wifi password is knowledge. And using is to access your wireless is wisdom.



Data Mining and KDD:
Data Mining is the process of finding or analysis of data from large amount of data where as KDD is the process of finding the knowledge from the large amount of data by making the use of data mining as shown in figure below.
Conclusion:
The part of KDD dealing with the analysis of the data has been termed data mining. and it is a very crucial step of the KDD process.


ASSISTANT PROFESSOR RECRUITMENT AND QUALIFICATIONS | ASSESSMENT CRITERIA AND METHODOLOGY FOR UNIVERSITY/COLLEGE TEACHERS

The NET (National Eligibility Test), or an accredited test (State Level Eligibility Test  SET/SLET) shall be remained the minimum eligibility for appointment of Assistant Professor in higher education. It is stated further, if those candidates are awarded PhD with the regulations of UGC are exempted from the NET/ SET.
A minimum of 55 % marks shall be required at the master level. A relaxation of 5% shall be provided at the graduate and master‘s leve. Candidates belonging to Scheduled Caste/Scheduled Tribe/Differently-abled, Other Backward Classes (OBC)

ASSESSMENT CRITERIA AND METHODOLOGY FOR UNIVERSITY/COLLEGE TEACHERS

Criteria for Short listing of candidates for Interview for the Post of Assistant Professorsin Universities

# However, if the period of teaching/Post-doctoral experience is less than one year then
the marks shall be reduced proportionately.
Note:
(A) (i)M.Phil + Ph.D Maximum– 30 Marks
(ii) JRF/NET/SET Maximum - 07 Marks
(B) Number of candidates to be called for interview shall be decided by the concerned
universities.
(C) Academic Score - 80
 Research Publications - 10
Teaching Experience - 10
Total : -100
(D)SET/SLET score shall be valid for appointment in respective State
Universities/Colleges/Institutions only

Criteria for Short listing of candidates for Interview for the Post of Assistant Professors in Colleges

# However, if the period of teaching/Post-doctoral experience is less than one year
then the marks shall be reduced proportionately.
Note:
(A) (i)M.Phil + Ph.D Maximum- 20 Marks
 (ii)JRF/NET/SET Maximum - 10 Marks
(B) Number of candidates to be called for interview shall be decided by the concerned
universities.
(C) Academic Score - 84
 Research Publications - 06
Teaching Experience - 10
Total : -100
(D)SET/SLET score shall be valid for appointment in respective State
Universities/Colleges/Institutions only

All about journals and research paper | What is impact factor? | how the impact factor is calculated? | who calculate the impact factor? Scopous journals

Figure 1: One of my Research Papers When the Scholars are in their Master or PhD or in any research field. They are supposed to writ...