Table of Contents Introduction 2 Assumptions 3 Data Availability 3 Overnight processing window 3 Business sponsor 4 Source system knowledge 4 Significance 5 Data warehouse 6 ETL: (Extract, Transform, Load) 6 Data Mining 6 Data Mining Techniques 7 Data Warehousing 8 Data Mining 8 Technology in Health Care 9 Diseases Analysis 9 Treatment strategies 9 Healthcare Resource Management 10 Customer Relationship Management 10 Recommended Solution 11 Corporate Solution 11 Technological Solution 11 Justification and Conclusion 12 References 14 Health Authority Data (Appendix A) 16 Data Warehousing Implementation (Appendix B) 19 Data Mining Implementation (Appendix B) 22 Technological Scenarios in Health Authorities (Appendix C) 26 Technology Tools 27

Data Management Technology
Introduction

The amount of information offered to us is literally astonishing, and the worthiness of data as an organizational asset is widely acknowledged. Nonetheless the failure to manage this enormous amount of data, and to swiftly acquire the information that is relevant to any particular question, as the volume of information rises, demonstrates to be a distraction and a liability, rather than an asset. This paradox energies the need for increasingly powerful and flexible data management systems. To achieve efficiency and a great level of productivity out of large and complex datasets, operators need have tools that streamline the tasks of managing the data and extracting valuable information in a timely fashion. Fading to do so may incur an elevation cost of attaining it and managing it which may exceed the worth that was derived from it.

Data Analytics Systems have been used intensively and extensively by numerous industries. Data mining techniques are pleasant increasingly widespread and ever more essential in the areas of