1. ICT Database Lesson 1
What is a Database?

2. Objectives 9.1.1: Describe the functions of a relational database.
9.1.2: Distinguish between databases and spreadsheets.
9.1.3: Identify advantages of using a database instead of alternatives (e.g., spreadsheets, electronic documents, paper).
9.1.4: Describe real-world uses for databases, including search engines, schools, hospitals, retail.
9.2.10: Identify and compare various database applications, including Microsoft Access, MySQL, Oracle.
9.2.9: Describe Structured Query Language (SQL) and discuss its use with databases.
9.1.5: Define "big data" and describe how it is used in advertising.

3. Database
A file that stores data in an organized fashion so that information can be retrieved from it.
Examples:
iPod playlist
Netflix movie list
Contacts in cell phone

4. Table – Flat-file Database
A collection of data organized in rows and columns that can be used to store and manage information
Work great with small lists of data (information) that is all related.
A simple way to create a flat-file database is to use a spreadsheet.
Store information in cells created by using columns and rows of data

5. Spreadsheets - Advantages
Great for analyzing and sorting related data.
Easy to learn and use
Suitable for storing and "crunching" relatively small volumes of numerical data.
Able to present numerical data in the graphical form to quickly analyze data.

6. Spreadsheets - Disadvantages
Require that you enter the same information in multiple places
Have simplistic sorting and querying capabilities
Contain only a finite number of records
Changes to data in the computer memory and are not complete until the file is saved

7. Data Integrity
The validity of the data “Garbage in, garbage out.” Arizona / ARIZONA / Ariz / ARIZ / Az / AZ.

8. Creating Tables Identify duplicate data
If duplicate data exists, create a separate table just for that data
Relate it back to the original table

9. Relational Database
Consists of multiple tables of information related through common fields

10. Advantages
Hold as much as 2 gigabytes of data and are only limited by server operating system.
Allows for the simultaneous access and query of data by multiple individuals in multiple locations.
Data is protected against inadvertent corruption so you no longer need to keep redundant data.
We don’t have to manually enter the information reducing time, effort and mistakes.
Entering information is minimalized which reduces input time, resources and opportunities for human error. This reduces cost and increases data integrity.
Reduced processing time for large amounts of data.

11. Disadvantages
They are more complex and harder to learn and use than spreadsheets.
Designing relational tables can be more difficult and time- consuming.
Software and hardware costs are higher than a spreadsheet.

12. Database Management Systems
A program used to store, access and manipulate database information
Microsoft Access is an end-user DBMS that you can use to create and manipulate fairly small and uncomplicated databases
Graphical user interface
Wizard
Oracle, MySQL, IBM’s DB2 and Microsoft SQL Server are high-end DBMS programs used to create and manipulate large, complex databases used in large organizations

13. SQL – Structured Query Language
A sub-language commonly used for developing and managing databases
SQL pronounced “sequel”
Used primarily in a database to retrieve, update, insert or remove information
Sufficiently powerful and can create tables, restructure tables and remove tables, among other very complex tasks

14. ODBC - Open Database Connectivity
An open standard application programming interface (API)
Allows us to use the MS Access interface tools to access the DBMS data.
Using a simplified graphical user interface (GUI) like MS Access to build queries and reports is a flexible way for a relative novice to gain access to a wealth of company data.

15. Big Data
A term that describes enormous volumes of data that are too huge for regular database programs
Unlike data in a database, big data is unstructured and unrelated.
Analysis of big data requires specialized tools.