DATABASE CONCEPTS

• DATA

  • discrete or continuous values that convey information.
  • raw facts
• TWO CATEGORIES OF DATA

  UNSTRUCTURED DATA

  STRUCTURED DATA
• UNSTRUCTURED DATA

  • doesn’t have a predefined data
  • difficult to process and analyze using traditional methods.
• STRUCTURED DATA

  • Information organized in a predefined way.
  • data arranged in tables with rows and columns
  • Easier to access, manage, and analyze.
• INFORMATION

  -         Organized data

  -         Processed data used to make decisions and take action
• PROCESS DATA MUST BE:

  o   Accuracy: info must accurate

  o   Completeness: info must be complete

  o   Timeliness: info must be available when it’s needed.
• DATA PROCESSING CYCLE


  STEP 1: COLLECTION

  STEP 2: PREPARATION

  STEP 3: INPUT

  STEP 4: PROCESSING

  STEP 5: OUTPUT

  STEP 6: STORAGE
• STEP 1: COLLECTION

  -         Collection of raw data
• STEP 2: PREPARATION

  -          known as data cleaning

  -         process of sorting and filtering the raw data to remove unnecessary and inaccurate data.

  -         Purpose is to remove bad data (redundant, incomplete, or incorrect data).
• STEP 3: INPUT

  -         raw data is converted into machine readable form and fed into processing unit.
• STEP 4: PROCESSING

  -         the raw data is subjected to various data processing methods using machine learning and A.I algorithms to generate a desirable output.

  -         Manipulation of data.
• STEP 5: OUTPUT

  -         data is transmitted and displayed to the user in a readable form like graphs, tables, vector files, audio, video, documents, etc.

  -         presented data.
• STEP 6: STORAGE

  -         data and metadata are stored for further use.

  -         For quick access and retrieval of information whenever needed

  -         Allows it to be used as input in the next data processing cycle

  -         storing of data