1. Pengantar Sistem Informasi Data Resource Management

2. Outline 1.Data Governance 2.Master Data vs Transaction’s Data 3.The Database Approach 4.DBMS 5.Data WareHouse 6.Big Data 7.Career @Database Skill

3. Data Governance is an approach to managing information across an entire organization. DAMA International Tata Kelola Data IBM(Sunil Soares, 2011)

4. Master Data vs Transaction’s Data Master data are a set of core data, such as customer, product, employee, vendor, geographic location, and so on, that span the enterprise information systems. Transaction data, which are generated and captured by operational systems, describe the business’s activities, or transactions.

5. The Database Approach Minimizes the following problems: Data redundancy Data isolation Data inconsistency Data security Data integrity Data independence

6. Data Model integration of concepts that used for data explanation, data relation and data constraint to keep data integrity. Data Model = Logical Data Structure Data Model types: – Hierarchy – Network – Relasional – Objek Oriented

7. The Database Approach

8. Aplikasi Penggajian Laporan Berkas Gaji Berkas Pegawai Aplikasi Pelatihan Laporan Berkas Pelatihan Berkas Pegawai

9. The Database Approach Aplikasi Penggajian Laporan Berkas Gaji Berkas Pegawai Aplikasi Pelatihan Laporan Berkas Pelatihan

10. Designing the Database A data model is a diagram that represents entities in the database and their relationships. Entity-Relationship Modeling

11. Various methods of ER-D

12. ER-Diagram example

13. DBMS Software used to create and manage a database; it also provides tools for ensuring security, replication, retrieval, and other administrative and housekeeping tasks. Examples:

14. Database in Action - Ms. Access

15. DBMS in Action Aplikasi Penggajian Berkas Pegawai Aplikasi Pelatihan Laporan DBMS Permintaan Pemutahiran

16. Data Warehouse A central data repository containing information drawn from multiple sources that can be used for analysis, intelligence gathering, and strategic planning.

17. E xtract, T ransform, L oad Extract data from its home database Transform and cleanse it so that it adheres to common data definitions. Load to the data warehouse location

18. Big Data “collections of data that are so enormous in size, so varied in content, and so fast to accumulate that they are difficult to store and analyze using traditional approaches” The 3 V concepts: Volume. Data collections can take up petabytes of storage, and are continually growing. Velocity. Many data sources change and grow at very fast speeds. The nightly ETL process often used for data warehouses is not adequate for many real-time demands. Variety. Relational databases are very efficient for structured information stored in tables, but businesses can benefit from analyzing semi-structured and unstructured data as well.

22. Career @Database

23. Explore this… 1)Normalization method 2)DDL vs DML 3)Data Mining 4)Data Mart 5)OLTP vs OLAP 6)ORM

24. Referensi 1)Patricia Wallace, Introduction to Information Systems, Prentice Hall (2014). 2)R. Kelly Rainer, Brad Prince & Casey G. Cegielski, Introduction to Information Systems Supporting and Transforming Business,Wiley (2013).