Data Science course - lecture 3

Data Science full course for beginners

Transcript

1. 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
2. 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
3. 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 Data_Science_lecture3_by_Doaa_Mohey
4. 1. What is Data Science? 1.1 Data Science Life Cycle processes Data_Science_lecture3_by_Doaa_Mohey 4
5. 1. What is Data Science? 1.2 Data Science Applications Data_Science_lecture3_by_Doaa_Mohey 5
6. 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 Data_Science_lecture3_by_Doaa_Mohey
7. 2. What is Data Analysis? 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 Data_Science_lecture3_by_Doaa_Mohey 7
8. 2. What is Data Analysis? 2.2 How use Data Analysis? Data_Science_lecture3_by_Doaa_Mohey 8
9. 2. What is 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. Data_Science_lecture3_by_Doaa_Mohey 9
10. 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 Data_Science_lecture3_by_Doaa_Mohey
11. 3. What is Data Analytics? 3.1 Why use Data Analytics? Data_Science_lecture3_by_Doaa_Mohey 11
12. Data Analytics processes Data_Science_lecture3_by_Doaa_Mohey 12
13. 3. What is Data Analytics? 3.2 What are Data Analytics Types? Data_Science_lecture3_by_Doaa_Mohey 13
14. 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 Data_Science_lecture3_by_Doaa_Mohey
15. 4. What is Business Intelligence? 4.1 Business Intelligence classifications Data_Science_lecture3_by_Doaa_Mohey 15
16. 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 Data_Science_lecture3_by_Doaa_Mohey 16
17. 6. What are Difference between them? Data_Science_lecture3_by_Doaa_Mohey 17 Differences Data science Data analysis Data analytics Business 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.
18. 6. What are Advantages between them? Data_Science_lecture3_by_Doaa_Mohey 18 Advantages Data science Data analysis Data analytics Business 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
19. 6. What are Disadvantages between them? Data_Science_lecture3_by_Doaa_Mohey 19 Disadvantages Data science Data analysis Data analytics Business 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
20. 7. What is a big data? Data_Science_lecture3_by_Doaa_Mohey 20 • 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.
21. 7. What is a big data? Data_Science_lecture3_by_Doaa_Mohey 21
22. 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. Data_Science_lecture3_by_Doaa_Mohey 22
23. 7. What is Big Data? 7.2 What are types of data? Data_Science_lecture3_by_Doaa_Mohey 23
24. 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 Data_Science_lecture3_by_Doaa_Mohey 24
25. 9. What is a Data Scientist ? Data_Science_lecture3_by_Doaa_Mohey 25
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