capturing-selecting-managing-and-exchanging-data as

Capturing Data

How can data be captured?

• Data can be captured by a computer in many forms, these include:

  • Forms

  • OMR (Optical Mark Recognition)

  • OCR (Optical Character Recognition)

  • Sensors

  • Barcodes

  • Data Mining

Forms

• Collect user input

• Organise data in structured format

• Common in web applications

A data capture form

OMR (Optical Mark Recognition)

• Detects marked areas on paper by using a special machine to read the marks

• Used for exams, surveys, lottery tickets

• Automates data collection and entry

An OMR form being filled in

OCR (Optical Character Recognition)

• Converts printed or handwritten text into digital format

• Useful for digitising documents

• Assists in searching and editing text

Sensors

• Devices that detect and respond to changes in environment

• Convert physical signals into digital data

• Facilitates automated data collection and real-time monitoring

• Used in various applications:

  • Temperature sensors

  • Pressure sensors

  • Proximity sensors

  • Light sensors

  • Motion sensors

  • Humidity sensors

  • Gas sensors

  • Force sensors

  • Acoustic sensors

  • Magnetic sensors

Different Types of Sensor

Barcodes

• Machine-readable representation of data using parallel lines of varying widths and spacings

• Commonly used for tracking items, inventory management, and point-of-sale systems

• Two main types:

  • 1D (One-dimensional) barcodes: represent data using parallel lines (e.g. on products in shops)

  • 2D (Two-dimensional) barcodes: use geometric patterns like squares, dots, or hexagons to store data (e.g. QR code)

• Advantages of Barcodes

  • Fast and accurate data entry

  • Reduces human error

A Typical Barcode Scanner

Data Mining

• Process of discovering hidden patterns, correlations, and insights from large datasets

• Involves techniques and algorithms from fields like machine learning, statistics, and artificial intelligence

• Supports decision-making by transforming raw data into valuable information

• Applications of data mining

  • Marketing: Customer segmentation, market basket analysis, and targeted advertising

  • Finance: Fraud detection, credit scoring, and portfolio management

  • Healthcare: Disease prediction, patient clustering, and drug discovery

  • Manufacturing: Quality control, predictive maintenance, and supply chain optimisation

  • Telecommunications: Network monitoring, customer analysis, and service improvement

Selecting Data

Query By Example (QBE)

• User-friendly method for constructing database queries using a visual interface

• Allows users to search for data by providing an example of the desired output

• Key Features

  • Visual representation: QBE uses a grid or form-based interface, where users can enter criteria in columns representing database fields

  • Intuitive: Users don’t need to learn complex query syntax, making it accessible for non-technical users

  • Flexible: Allows for simple to complex queries, including filtering, sorting, and joining multiple tables

• How QBE Works

• Users enter criteria in the appropriate columns or fields in the QBE grid or form

• The QBE system translates the user’s input into an equivalent SQL query or other query language

• The query is executed against the database, and the results are displayed to the user

• Common Query Operations

• Filtering: Users can specify conditions or criteria in the QBE grid to retrieve specific records (e.g., all customers from a particular city)

• Sorting: Users can indicate the desired sorting order for the results (e.g., ascending or descending by last name)

• Joining: Users can combine data from multiple related tables by specifying relationships between the tables in the QBE grid

• Aggregation: Users can perform calculations or summaries on the data (e.g., counting the number of records, calculating averages, or summing values)

Benefits and Drawbacks of Query By Example (QBE)

Managing & Exchanging Data

Managing data

• After a database has been created, there must be easy ways of being able to manage the data, this includes:

  • Add new data

  • Edit/modify existing data

  • Delete data

• This can be achieved by:

  • A database manipulation language (DML) such as SQL

  • Built in facilities of a Database Management System (DBMS)

Exchanging data

CSV (Comma Separated Values)

• Simple data exchange format

• Stores tabular data in plain text

• Uses commas to separate values

• Widely supported and easy to parse