1. ENHANCEMENT OF BIG DATA INTEGRATION METHOD MAISARAH BINTI ZORKEFLEE 814594

2. STRUCTURE OF PRESENTATION Introduction Problem Tree Problem Statement Significance of Study Research Questions Research Objectives References

3. INTRODUCTION What is data integration? Data integration can be defined as combination of data from different sources and be presented to the users in unified form (Calvanese & Giacomo, 2005).

4. INTRODUCTION Where does data integration been used? It has been used in several domains such as websites, education, social networks and astronomy (Dong & Srivastava, 2013).

5. INTRODUCTION Why data integration is used? Data integration provides convinience to the users that need fast, current and clean data (Louie, Mork, Martin-Sanchez, Halevy & Tarczy-Hornoch, 2007)

6. INTRODUCTION How does research in data integration is significant? The arising issue among the researchers of data integration community is big data integration which is different from traditional data integration (Dong & Srivastava, 2013).

7. PROBLEM TREE Big Data Incomplete Data Heterogeneous data sources Non-uniform quality requirements Inconsistency Data Temporal inconsistency Spatial inconsistency Text inconsistency High- Dimensional Data Set Entity-name clustering Entity-name matching Overlapping data Contain closely related Missing dataLosing value

8. Big DataIncomplete Data Heterogeneous data sources Non-uniform quality requirements Inconsistency Data Temporal inconsistency Spatial inconsistency Text inconsistency High- Dimensional Data Set Entity-name clustering Entity-name matching Overlapping data Contain closely related Missing dataLosing value

9. PROBLEM STATEMENT Incomplete data Heterogeneity data sources Quality data analysis

10. SIGNIFICANCE OF STUDY Contribution to the development of big data integration in the domain of education.

11. RESEARCH QUESTIONS How to integrate heterogeneous data sources? How to increase the quality of data analysis? How to evaluate the methods performance?

12. RESEARCH OBJECTIVES To find out the method to integrate heterogenous data sources To enhance the method to increase the quality of data analysis. To evaluate the performance of the enhanced methods by comparing the algorithm from previous method.

13. REFERENCES Calvanese, D., & De Giacomo, G. (2005). Data integration: A logic-based perspective. AI magazine, 26(1), 59. Dong, X. L., & Srivastava, D. (2013). CONFERENCE: Big Data Integration. ICDE Conference 2013, pp. 1245–1248. Louie, B., Mork, P., Martin-Sanchez, F., Halevy, A., & Tarczy-Hornoch, P. (2007). Data integration and genomic medicine. Journal of biomedical informatics, 40(1), 5–16.

14. THANK YOU