3. Data may be logically organized into characters, fields,
records, files, and databases , just as writing can be
organized into letters, words, sentences, paragraphs,
and documents.

4.  A database is an integrated collection of logically related
data elements.
 The data stored in a database are independent of the
application programs using them and of the type of storage
devices on which they are stored.

5.  It is basically a computer based record keeping system
(program).
eg: MySQL, Microsoft Access, Oracle, Sybase. Etc
 A database is not generally portable across different
DBMSs, but different DBMS can interoperate by
using standards such as SQL, ODBC or JDBC to allow a
single application to work with more than one DBMS.
 DBMSs provide various functions that allow management
of a database and its data which can be classified into four
main functional groups:
1. Data definition
2. Update
3. Retrieval
4. Administration

6.  Data Models
1. Relational 2. Network
3.Hierarchical

8.  Some application areas of DBMS
1. Banking: Customer information, accounts, loans and banking
transactions.
2. Airlines: For reservations and schedule information. Airlines were among
the first to use databases in a geographically distributed manner.
3. Universities: For student information, course registrations and grades.
4. Telecommunication: For keeping records of calls made, generating
monthly bills, maintaining balances on prepaid calling cards, and storing
information about the communication networks.
5. Sales: For customer, product, and purchase information.
6. Manufacturing: For management of supply chain and for tracking
production of items in factories, inventories of items in warehouses and
orders for items.
7. Human resources: For information about employees, salaries, payroll
taxes and benefits, and for generation of paychecks.

9.  It is a class of information systems that facilitate and
manage transaction-oriented applications.
 Some examples of OLTP systems include order entry,
retail sales, and financial transaction systems.

10.  It provides a mechanism for storage and retrieval of data
that is modeled in means other than the tabular relations
used in relational databases.
 It was triggered by the needs of Web 2.0 companies such
as Facebook, Google and Amazon.com
 Motivations for this approach include: simplicity of design,
simpler scaling to clusters of machines, which is a
problem for relational databases, and finer control over
availability.

11.  Big data analytics is the process of examining large data
sets containing a variety of data types.
 The primary goal of big data analytics is to help
companies make more informed business decisions.
 Big data needs to be updated frequently or even
continually. As a result, many organizations looking to
collect, process and analyze big data have turned to a
newer class of technologies that includes Hadoop as well
as NoSQL databases.

12.  Database administrators (DBAs) - set up databases according
to a company’s needs and make sure they operate efficiently.
 Data Management Analysts – Generating, Tracking and
Maintaining the reports. Analyze the reports to determine
appropriate resolutions.
 System Specialists - This position functions as the system
administrator, first-line technical support contact, and trainer.
 Production Support Engineers – They support DBAs, Data
Management Analysts and System Specialists round the clock
and ensure smooth running..