TRADITIONAL DATA
•Data is the foundation of data science; it is the material on
which
all
the analyses
are based. In the context of data
science, there are
two
types of
data:
traditional
and
big data.
which
all
the analyses
are based. In the context of data
science, there are
two
types of
data:
traditional
and
big data.
•Traditional data is
data
that
is
structured
and
stored
in databases which can be managed from one computer;
it
is in
table
format, containing numeric
or text values.
data
that
is
structured
and
stored
in databases which can be managed from one computer;
it
is in
table
format, containing numeric
or text values.
BIG
DATA
DATA
•This
is
extremely
large
data,
distributed across a
network of
computers, but
it is
not just
characterized
by its
volume. This
data can
be in
various
formats;
it
can
be
structured,
semi-structured or unstructured.
is
extremely
large
data,
distributed across a
network of
computers, but
it is
not just
characterized
by its
volume. This
data can
be in
various
formats;
it
can
be
structured,
semi-structured or unstructured.
•You
will
often
see
big
data
characterized by the following;
will
often
see
big
data
characterized by the following;
-Variety – numbers, text, but also images, audio,
mobile
data, etc.
Big
data
can
be
in
various
formats
mobile
data, etc.
Big
data
can
be
in
various
formats
-Velocity – it is retrieved and computed in real time
-Volume
–
big
data
is
measured
in
tera-, peta-,
exa-
–
big
data
is
measured
in
tera-, peta-,
exa-
bytes
(that’s
1
million
terabytes).
WHAT DO YOU DO TO DATA
Class Sessions
1- Introduction to Data Analytics
2- What is Data Science
3- Overview
4- Data preprocessing
5- Data Quality Assessment and Use Case
6- Where does Data come from?
7- Who handles th Data
8- BUSINESS INTELLIGENCE
9- Traditional Methods
10- Traditional Forecasting uses
11- Content
12- Machine Learning Uses
13- Introduction to Large Language Model and Generative AI
14- Data protection
15- Data Management practises
16- Tools and Frameworks