1. What is data

2. Data Explained with Real Life Example

3. types of data &catageries of data

4. Structured data

5. Unstructured data

6. Revision And Semi Structured Data

7. Sources of Data

8. Remaining Sources of Data and Importance of Data Collection

9. Data Explained with Further Examples

10. Ethical Consideration in Data Collection

11. MCQs

Class Activity

1. Introduction to Data Analytics(vvs)

2. Data Analytics cycle(vvs)

3. Real life example Of Data Analytics(vvs)

4. Another example Of Data Analytics(vvs)

5. Data analytics stage intro & Descriptive Analytics(vvs)

5.1 Diagnostic Analytics(vvs)

5.2 predictive Analytics(vvs)

5.3 prescreptive Analytics(vvs)

6. Real life example of Qurshi Industries(vvs)

7. Aplication of data Analytics(vvs)

8.Chapter 3 Mcqs(vvs)

1. Big Data intro(VVS)

2. Charactersitcs of big data(VVS)

3. Sources of big data(VVS)

4.Method of big data

5.Application of big data

6.Challanges of big data

7. Emerging trends(VVS)

8. Chapter 4 Mcqs(VVS)

1.intro Data governance

2.Key objectives of data governance

3.1 key components of data governance

3.2 key components of data governance

3.3 key components of data governance

3.4 key components of data governance

4.1 level of data governance

4.2 level of data governance

4.3 level of data governance

5. Common data clasifaciation

6. data classification frame work

7. Data storage

8.Emerging trends

9.Data integrity

10. data security

11. Complince and stewerd ship

12. Meta data

13.Emerging Technologies in Data Governance

14.Drivers of Data Governance

15.Data governance chanllenges

16.data governance best practices and implimentation stages

17.Chapter 2 overview

18.MCQS

1.intro to DBMS

2.Components of DBMS

3.Data base components&Atomicity

4.consistancy

5.isolation

6.durability

7.Additional charactersitcs of DBMS

8.DBMS Arthitecture external level

9.Conceptual level

10.internal level

11.key benefits of three architecture

12.types of data independance

13.physical independance

14.ER Model

15.types of DBMS

16.overview of chapter

17.MCQS

1.Data wreahousing

2.online transaction process

3.Eaxtract,transform,load process

4.Data whaerehouse Architecture

5.Schema in data whaerhouse

6.Snowflake schema

7.Data mart

8.1Data normalization

8.2 Data normalization

8.3 Data normalization

1.intro to it system Architecture

2.1 key components of it system architecture,hardware

2.2.soft ware

2.3. network

2.4. storage

3. scalability&flexibilty

4.1. it system layyers

4.2 it system layyers

5. it system interaction & dependence

6.1 best practices for desienging it system architecture

6.2 best practices for desienging it system architecture

7.1. intro to programing language,types of language

7.2 papular language

8. key consideration for chosing programing languages

9. Emerging trends in programing languages

1.intro Emerging technologies And AI &ML

2.key features of AI and ML

3. Application of AI and ML

4. IOT devices

5.components of IOT

6.Application of IOT

7. Challanges in IOT

8. 5G technologies

9. Edge Computing

10. intro to AR and VR

11. key features of AR and VR

12. Benefits

13.1 Quantum computing

13.2 Quantum computing

14. Robotics process

15. Benifits of PRA

16. MCQS

1. intro to ERP system

2. key components of ERP system

2.1 key components of ERP system

3. Real life Example

4.ERP implimentation

5.benefits of ERP system

6.types of ERP system