2. Introduction
The term database‘ is defined as any
collection of electronic records that can be
processed to produce useful information. The
data can be accessed, modified, managed,
controlled, and organized to perform various
data-processing operations. The data is
typically indexed across rows, columns, and
tables that make workload processing and
data querying efficient. Different types of
databases include object oriented,
relational, distributed, hierarchical, network,
and others.
3. In enterprise applications, databases
involve mission-critical, security sensitive,
and compliance-focused record items that
have complicated logical relationships with
other datasets and grow exponentially over
time as the user based increases. As a result,
these organizations require technology
solutions to maintain, secure, manage and
process the data stored in databases. This is
where the Database Management System
comes into play.
5. OBJECTIVES/COMPETENCIES:
Understand what is database?
Identify the different databases types
Understand the Database Management
System
Identify the various widespread databases
Understand the data warehousing concepts
Define what is data warehouse
Understand the basics of data science and
data mining
6. What is database?
A database is an organized collection of
structured information, or data, typically
stored electronically in a computer system. A
database is usually controlled by a database
management system (DBMS). Together, the
data and the DBMS, along with the
applications that are associated with them,
are referred to as a database system, often
shortened to just database.
8. 1. Centralized database
The information(data) is stored at a
centralized location and the users from
different locations can access this data. This
type of database contains application
procedures that help the users to access the
data even from a remote location.
10. 2. Distributed database
Just opposite of the centralized database
concept, the distributed database has
contributions from the common database as
well as the information captured by local
computers also. The data is not at one place
and is distributed at various sites of an
organization. These sites are connected to
each other with the help of communication
links which helps them to access the
distributed data easily.
12. 3. Personal database
Data is collected and stored on personal
computers which is small and easily
manageable. The data is generally used by
the same department of an organization and
is accessed by a small group of people
14. 4. End User Database
The end user is usually not concerned about
the transaction or operations done at various
levels and is only aware of the product which
may be a software or an application.
Therefore, this is a shared database which is
specifically designed for the end user, just
like different levels’ managers. Summary of
whole information is collected in this
database.
15. 4. End User Database
https://slideplayer.com/slide/5297526/17/images/3/Figure+The+DBMS+Manages+the+Inter
action+between+the+End+User+and+the+Database.jpg
16. 5. Commercial Database
These are the paid versions of the huge
databases designed uniquely for the users
who want to access the information for help.
These databases are subject specific, and
one cannot afford to maintain such a huge
information. Access to such databases is
provided through commercial links
18. 6. NoSQL Database
These are used for large sets of distributed
data. There are some big data performance
issues which are effectively handled by
relational databases, such kind of issues are
easily managed by NoSQL databases. There
are very efficient in analyzing large size
unstructured data that may be stored at
multiple virtual servers of the cloud.
20. 7. Operational Database
Information related to operations of an
enterprise is stored inside this database.
Functional lines like marketing, employee
relations, customer service etc. require such
kind of databases.
22. 8. Relational Databases
These databases are categorized by a set of
tables where data gets fit into a pre-defined
category. The table consists of rows and
columns where the column has an entry for
data for a specific category and rows
contains instance for that data defined
according to the category.
24. 9. Cloud Databases
Now a day, data has been specifically getting
stored over clouds also known as a virtual
environment, either in a hybrid cloud, public
or private cloud. A cloud database is a
database that has been optimized or built for
such a virtualized environment.
26. 10. Object-Oriented Databases
An object-oriented database is a collection of
object-oriented programming and relational
database. There are various items which are
created using object-oriented programming
languages like C++, Java which can be stored
in relational databases, but object-oriented
databases are well-suited for those items.
29. Object-Oriented Databases
is the software that is used to manage
databases. Examples are MySQL, Oracle, etc.
These are some commercially popular DBMS
used in various applications.
DBMS allows users the following tasks:
30. Data Definition
It helps in the creation, modification, and
removal of definitions that define the
organization of data in the database.
Data Updation
It helps in insertion, modification, and
deletion of the actual data in the database.
31. Data Retrieval User Administration
It helps in retrieval of data from the
database, which can be used by applications
for various purposes.
It helps in registering and monitoring users,
enforcing data security, monitoring
performance, maintaining data integrity,
dealing with concurrency control, and
recovering information corrupted by
unexpected failure.
User Administration
33. A. Data Integrity
maintains the correctness and consistency of
the data.
1. Domain Integrity
- All categories and values in a database are
set, including nulls (e.g., N/A). The domain
integrity of a database refers to the common
ways to input and read this data.
35. 2. Entity Integrity
It depends on the making of primary keys or
exclusive values that classify data items. The
purpose is to make sure that data is not
recorded multiple times (i.e., each data item
is unique), and the table has no null fields.
36. 3. Referential Integrity
refers to the accuracy and consistency of
data within a database relationship. Data is
linked between two or more tables. This is
achieved by having the reference a primary
key value.
37. B. Data Accessibility and Responsiveness
even when it crosses traditional
departmental restrictions, the end-users
without programming knowledge can often
recover and display data.
C. Data Security
the data saved in the database is secured
with appropriate access control.
38. Data Warehousing Concepts
The concept of a data warehouse was initially
developed by IBM and called information
warehouse. It is presented as a key for
accessing data saved in non – relational
systems. The information warehouse was
projected to let organizations use their data
archives and help them have a business
advantage. Bill Inmon is the latest advocate for
data warehousing and most successful. Because
of his active promotion of the concept, He was
called the father of data warehousing.
40. Data warehouse (Inmon)
Subject-oriented as the warehouse is organized
around the primary subjects of the enterprise
(such as customers, products, and sales) rather
than the significant application areas (such as
customer invoicing, stock control, and product
sales).
They are integrated because of the coming
together of source data from different enterprise-
wide applications systems. The combined data
source must be made consistent with presenting a
unified view of the data to the users.
41. Data warehouse (Inmon)
Time-variant because data in the warehouse is
only accurate and valid at some point in time or
over some time interval. The time-variance of the
data warehouse is also shown in the extended
time that the data is held. The implicit or explicit
association of time with all data and the fact that
the data represents a series of snapshots.
42. Data warehouse (Inmon)
Non-volatile as the data is not updated in real-
time but is refreshed from operational systems
regularly. New information is always added as a
supplement to the database, rather than a
replacement. The database continually absorbs
this new data, incrementally integrating it with
the previous data.
44. What is Data Mining
Data mining is a process of gathering mass of data
and turning it into a valuable information that will
help a company. It is the way a machine or a
program gathers information to solve a problem,
predict revenue, know what the consumer wants,
and etc.
45. How Does it Work?
Data Mining works by gathering information and
making that information valuable. It gathers data
and a machine or a program process all the data
and it will evaluate all the data, then the
algorithm will give you the result. It’s important to
know that a poor data leads into to a poor result
that’s why you need to know what kind of data
you’re looking for.
46. Who Uses it?
Data mining can be use in all sorts of business, it
can change the way a company approach their
tactics.
47. Who Uses it?
Example of industry that uses data mining:
Marketing- by the use of data mining they able to
predict the consumers behavior. They can also
predict who’s likely to be interested to a certain
product. And with the help of data mining, they
can know what kind of advertisement would be
the best for their product.
48. Who Uses it?
Example of industry that uses data mining:
Medicine- with all the data that they can gather
they can predict more effectively what kind of
decease does a certain person has.
Media- it can personalize your show
recommendation based on what you recently
watched or listen to.
