Data science lecture3_doaa_mohey

Presented by:
Doaa Mohey Eldin
PhD researcher in information Systems
Faculty of Computers and Artifical intelligence – Cairo University
IEEE Society Member
d.mohey2020@gmail.com

Agenda
• What is Data science?
• What is data Analysis?
• What is Data Analytics?
• What is Business Intelligence?
• What are common between them?
• What are the Differences between them?
• What is a big data?
• Data science Job Roles
• What is data scientist? 2
Data_Science_lecture3_by_Doaa_Mohey

1. What is Data Science?
• Data Science is
– “an informative science that extracts knowledge from
various domains. That requires to use many
algorithms, methods, systems or techniques for
scrapping this data and interpret it”.
– Related to data mining, machine learning and big
data.
– Based on using statistics, analysis, or informatics, and
their related methods
3

1.1 Data Science Life Cycle processes
Data_Science_lecture3_by_Doaa_Mohey 4

1.2 Data Science Applications

2. What is Data Analysis?
• Data Analysis is
– “A process of cleaning, transforming, and modeling
data to relieve useful information for business
decision-making”.
– The main objective of Data Analysis is to extract
useful information from data and taking the decision
based upon the data analysis.
6

2.1 7 Types of Data Analysis (DA)
Data Analysis Types
Exploratory DA (EDA)
Explanatory DA
Predictive DA
Inferential DA
Decision Trees
Descriptive DA
Mechanistic DA

2.2 How use Data Analysis?

2.3 Why use Data Analysis?
• It uses for understanding challenges facing an
organization, and to explore data in meaningful
ways.
• Making predictions and Making decisions
• Interpreting text analysis.

3. What is Data Analytics?
• Data Analytics is
– “A process of raw data analysis finds new trends and
answer questions.
– The essential definition of data analytics captures its
broad scope of the field. However, it contains many
techniques with many different objectives.
10

3.1 Why use Data Analytics?

Data Analytics processes

3.2 What are Data Analytics Types?

4. What is Business Intelligence?
• Business Intelligence is
– “it comprises the strategies and technologies used by
enterprises for the data analysis of business information.
– BI technologies provide historical, current, and predictive
views of business operations.
– It is a technology-driven process for analyzing data and
delivering actionable information that supports executives,
managers and workers make informed business decisions.
14

4. What is Business Intelligence?
4.1 Business Intelligence classifications

5. What are common between them?
Common
Data science Data analysis Data analytics Business
intelligence
They use for
1. Improving decision making
2. Analyzing large amount
3. Understanding risk management
4. Saving cost
It relies on many algorithms:
1. machine Learning
2. Exploratory Analysis
3. Data Mining
4. Modeling Visualization
5. Software Development

6. What are Difference between
them?
Differences
intelligence
It uses for
extracting data
with various views
from structured or
unstructured
data.
It refers to an
examining process
for arranging input
data in with
respect to specific
ways that uses for
extracting useful
information.
It relies on an
algorithmic
process is used for
deriving insights
that uses for
interpreting the
meaningful
correlations.
It refers to a set of
processes,
architectures, and
technologies that
convert raw data
into meaningful
information that
drives profitable
business actions.

6. What are Advantages between
them?
Advantages
intelligence
1. Powerful of
higher effect in
interpreting
data
2. It is a demand
1. Faster analysis
required
2. Better
performance
3. Increased
awareness risk
4. Effective
market analysis
5. More efficient
operations.
1. detects and
correct the
errors from
data sets.
2. Removing
duplicates
3. Reducing risks
1. Improving
productivity
2. Improving
visibility
3. Improving
automatic
analytics

6. What are Disadvantages between
them?
Disadvantages
intelligence
1. Privacy problem
2 Career high level.
1. Reduce cost 1. Difficulty
analytics tools
2. Privacy
challenges
3. Hardness of data
analytics cost
1. Cost
2. Complexity
3. Limited use
4. Time
consuming

7. What is a big data?
• Big Data refers to the large amounts of data which is
pouring in from various data sources and has different
formats.
• Even previously there was huge data which were being
stored in databases,
– but because of the varied nature of this Data,
– the traditional relational database systems are
incapable of handling this Data.

7. What is a big data?

7. What is Big Data?
7.1 What are Big Data Formats?
• The three different formats of big data are:
– Structured: Organized data format with a fixed
schema. Ex: RDBMS
– Semi-Structured: Partially organized data which
does not have a fixed format. Ex: XML, JSON
– Unstructured: Unorganized data with an
unknown schema. Ex: Audio, video files etc.

7. What is Big Data?
7.2 What are types of data?

8. Data Scientist Job Roles
• Many job titles of Data Science are:
– Data Scientist
– Data Engineer
– Data Architect
– Data Administrator
– Data Analyst
– Business Analyst
– Data/Analytics Manager
– Business Intelligence Manager

9. What is a Data Scientist ?

26

Data science lecture3_doaa_mohey

More Related Content

What's hot

Similar to Data science lecture3_doaa_mohey

More from Doaa Mohey Eldin

Recently uploaded

Data science lecture3_doaa_mohey