Database Introduction for MIS Students.pptx

Database in MIS systems

1. Foundation concepts Database Deepanjal Shrestha, School of Business

2. Fundamental Data Concepts Data is raw bits and pieces of information Quantitative – numeric Qualitative – descriptive Alone is not useful Information is when data is given context and more specific Knowledge is developed when information has been aggregated and analyzed to make decisions, set policies, and spark innovation Wisdom is the combination of knowledge and experience May take years to develop Data Information Knowledge Wisdom

3. Basics of a Database Databases are made up of: -files -records -fields Files: A file is a collection of related database information . Ex. A Movie Collection, Address Book Records: A record is a collection of data about a single product, activity, or transaction. Ex. Titanic, Person in the Address Book Fields: A field is each separate piece of information (but related) in a record. Fields are the “building blocks” for records containing the data you want to store, find, sort and print. Ex . Name, Address, City, Phone # This record has four fields.

4. What are Databases Good For? Easy way to organize and sort information Use the information (mail merge) Analyze information Group information Find specific information Look at patterns and relationships between information Take up less space Help you manage large collections of information

5. Traditional File System Problems

6. Database Advantages over Traditional File System

7. A database is a collection of information that is organized so that it can be easily accessed, managed and updated.  Computer databases typically contain aggregations of data records or files, containing information about sales transactions or interactions with specific customers. Database

8. Database Management System (DBMS)  is a software for storing and retrieving users' data while considering appropriate security measures. It consists of a group of programs which manipulate the database. The DBMS accepts the request for data from an application and instructs the operating system to provide the specific data. In large systems, a DBMS helps users and other third-party software to store and retrieve data. Database Management System (DBMS)

9. Database Management System (DBMS)

10. Disadvantages of DBMS DBMS implementation cost is high compared to the file system Complexity: Database systems are complex to understand Performance: Database systems are generic, making them suitable for various applications. However this feature affect their performance for some applications

11. Traditional file system The  traditional  filing  system  (TFS) is a method of storing and arranging computer  files  and the information in the  file  (data). Basically it organizes these  files  into a database for the storage, organization, manipulation, and retrieval by the computer's operating  system . Database Management System (DBMS)

12. ACID Properties of a DBMS

13. Applications of DBMS

14. Types of Databases

15. Data Model It defines the data elements and the relationships between the data elements. Data Models are used to show how data is stored, connected, accessed and updated in the database management system. Here, we use a set of symbols and text to represent the information so that members of the organization can communicate and understand it.

16. Types of Database Models Data Model Hierarchical Network ER model Relational Multi-dimensional Object Oriented

17. Hierarchical Model This model organizes the data in the hierarchical tree structure. The hierarchy starts from the root which has root data and then it expands in the form of a tree adding child node to the parent node. This model easily represents some of the real-world relationships

18. Hierarchical Model Advantages of Hierarchical Model It is very simple and fast to traverse through a tree-like structure. Any change in the parent node is automatically reflected in the child node so, the integrity of data is maintained. Disadvantages of Hierarchical Model Complex relationships are not supported. As it does not support more than one parent of the child node so if we have some complex relationship where a child node needs to have two parent node then that can't be represented using this model. If a parent node is deleted then the child node is automatically deleted .

19. Object Oriented Data Model Data and their relationships are contained in a single structure which is referred as object in this data model Object Attributes Methods C lass Inheritance

20. Network Data Model A network database model is a database model that allows multiple records to be linked to the same owner file. Many-to-many relationship Easily accessed because of the linkage between the information Great flexibility among the information files because the multiple relationships among the files

21. Relational Data Model Relational Model (RM) represents the database as a collection of relations. A relation is nothing but a table of values. Every row in the table represents a collection of related data values. These rows in the table denote a real-world entity or relationship

22. ER- Data Model Entity-relationship diagrams ( ERD ), or entity-relationship models are modeled as components (entities) that are connected to each other by relations that express the dependencies and requirements between them.

23. Multi-Dimensional Data Model A multidimensional model views data in the form of a data-cube. A data cube enables data to be modeled and viewed in multiple dimensions. It is defined by dimensions and facts

24. Database Types

25. DBMS Language

26. DDL : Data Definition Language A data definition language ( DDL ) is a computer language used to create and modify the structure of database objects in a database. These database objects include views, schemas, tables, indexes, etc. This term is also known as data description language in some contexts, as it describes the fields and records in a database table .

27. DML : Data Manipulation Language A data manipulation language ( DML ) is a family of computer languages including commands permitting users to manipulate data in a database. This manipulation involves inserting data into database tables, retrieving existing data, deleting data from existing tables and modifying existing data. DML is mostly incorporated in SQL databases.

28. DCL: Data Control Language It is used to control access to data stored in a database (Authorization). In particular, it is a component of Structured Query Language (SQL). Data Control Language is one of the logical group in SQL Commands. 

29. Transaction Control Language Transaction Control Language (TCL) commands are used to manage  transactions  in the database. These are used to manage the changes made to the data in a table by DML statements. It also allows statements to be grouped together into logical  transactions .

30. Types of DBMS Language

31. Data Warehouse

32. Data Warehouse

33. Benefits of a Data Warehouse

34. Data Mining Data Mining is defined as a process used to extract usable data from a larger set of any raw data. It implies analysing  data patterns in large batches of data using one or more software.  Data mining is also known as Knowledge Discovery in Data (KDD). Data mining is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs.

35. Data Mining Process

36. Applications of Data Mining

37. Data Marts A data mart is  a simple form of data warehouse focused on a single subject or line of business . Using a data mart, teams can access data and gain insights faster, because they don't have to spend time searching within a more complex data warehouse or manually aggregating data from different sources.

38. Decision Support System

39. Levels of Decision Making

40. Components of DSS Model Management System The model management system stores models that managers can use in their decision-making. The models are used in decision-making regarding the financial health of the organization and forecasting demand for a good or service. User Interface The user interface includes tools that help the end-user of a DSS to navigate through the system. Knowledge Base The knowledge base includes information from internal sources (information collected in a transaction process system) and external sources (newspapers and online databases).  

41. Components of DSS

42. Goals of Decision Support Systems

43. Use of Decision Support Systems Using a decision support system involves an interactive analytical modeling process Decision makers are not demanding pre-specified information They are exploring possible alternatives What-If Analysis Observing how changes to selected variables affect other variables Sensitivity Analysis Observing how repeated changes to a single variable affect other variables Goal-seeking Analysis Making repeated changes to selected variables until a chosen variable reaches a target value Optimization Analysis Finding an optimum value for selected variables, given certain constraints

44. Types of DSS Communication-driven DSS Its purpose are to help conduct a meeting, or for users to collaborate. The most common technology used to deploy the DSS is a web or client server. Examples : chats and instant messaging softwares , online collaboration and net-meeting systems. Data-driven DSS It is used to query a database or data warehouse to seek specific answers for specific purposes. It is deployed via a main frame system, client/server link, or via the web. Examples : computer-based databases that have a query system to check Document-driven DSS The purpose of such a DSS is to search web pages and find documents on a specific set of keywords or search terms. The usual technology used to set up such DSSs are via the web or a client/server system.

45. Types of DSS Knowledge-driven DSS : Knowledge-driven DSSs or 'knowledgebase' are they are known, are a catch-all category covering a broad range of systems covering users within the organization seting it up, but may also include others interacting with the organization - for example, consumers of a business. It is essentially used to provide management advice or to choose products/services. The typical deployment technology used to set up such systems could be slient /server systems, the web, or software runnung on stand-alone PCs. Model-driven DSS Model-driven DSSs are complex systems that help analyse decisions or choose between different options. These are used by managers and staff members of a business, or people who interact with the organization, for a number of purposes depending on how the model is set up - scheduling, decision analyses etc. These DSSs can be deployed via software/hardware in stand-alone PCs, client/server systems, or the web.

46. MIS vs DSS

47. Online Transaction Processing An  OLTP system  is a common data processing  system  in today's enterprises. Classic examples of  OLTP systems  are order entry, retail sales, and financial transaction  systems . These programs, which run in the background while users continue to work on other tasks, may require a large number of data-intensive computations. OLTP  database systems are commonly  used  for order entry, financial transactions, customer relationship management and retail sales via the Internet.

48. OLTP vs OLAP

49. OLTP vs OLAP

50. Microsoft Access Microsoft Access  is a  database  management system (DBMS) from  Microsoft  that combines the relational  Microsoft  Jet  Database  Engine with a graphical user interface and software-development tools. Microsoft Access  stores data in its own format based on the  Access  Jet  Database  Engine. It allows us to create the framework (forms, tables and so on) for storing information in a database.  Microsoft Access  allows opening the table and scrolling through the records contained within it.  Microsoft Access  has capabilities to answer more complex requests or queries

51. Components of MS Access

52. Why to Prefer MS Access

53. Thank You!