LO3

• Data

  Unprocessed facts or statistics that have no context
• Information

  Data that has been processed, organised and structured into context
• Categories of Information for Individuals

  • Communication
  • Education and Training
  • Planning
  • Financial
  • Entertainment
  • Research
  • Location Dependent
• Categories of Information for Organisations

  • Knowledge Management & Creation
  • Management Information Systems (MIS)
  • Financial Analysis & Modelling
  • Contact Management
  • Internal and External Communication
  • Big Data
  • Marketing, Promotion & Sales
  • Decision Making
• Stages of data analysis


  • Identify the need
  • Define the scope
  • Identify potential sources
  • Source and select information
  • Select the most appropriate tools
  • Process and analyse data
  • Record and store information
  • Share results
• Identify the need

  1. Objectives are set for what the data analysis will hope to achieve

  2. Aims must be clear and well defined

  3. Define what information will be needed

  4. Define what exactly they want to find out by the end of the process (the purpose of the data analysis)
• Identifying the need

  • Not clearly defining the required information or purpose could lead to worthless results and a waste of the entire data analysis process
• Define the scope

  1. Restrictions of the project are defined

  2. Factors such as budget, content, detail, timescales (deadlines) and any further constraints
• Identify potential sources

  1. Identify a wide range of sources for the potential information

  2. Ensure the information is unbiased and covers the objectives

  3. The specific data will depend on the project but it could include sales figures or customer surveys for example
• Source and select information

  1. Information is gathered from the identified sources

  2. Any unsuitable data is excluded so that results are not unreliable

  3. Poor quality information can lead to numerous negative consequences

  4. Determine the accuracy and reliability of any identified sources and select the best
• Select the most appropriate tools

  1. Many different data analysis tools can be used

  2. Select the most appropriate tool for the project

  3. Examples include methods of presentation such as charts and graphs, regression analysis, trend analysis
• Process and analyse data

  1. Data is inputted into software such as spreadsheets or databases to further analyse

  2. Putting collected data into a spreadsheet allows for analysis to begin as graphs can be created from the data and any patterns or trends discovered
• Record and store information

  1. Findings are written into a report

  2. Any patterns, trends or findings can be described with statistical evidence generated from the analysis
• Share results

  1. The report is shared with the stakeholders

  2. Sharing can take different forms such as a typed document, an email, or a post on a website
• What are the methods of Data analysis tools?

  Data Tables

  Visualisation of Data

  Trend & Pattern Identification

  Data Cleaning

  Location Mapping
• Data Tables are easier to update, view and manipulate. It allows for simpler editing and also allows for the display of basic patterns. They are a good method of speedy, short-term data analysis. However, they present data in its current format and cannot show change or trends over time.
• Visualising data


  Producing a chart or graph makes it easier for an audience to see trends and patterns and easier to understand, quicker to interpret.
• Trend & Pattern Identification


  Allowing trends and patterns to be viewed as a visual format.
• Statistical analysis


  Linked to trend and pattern identification, it allows data analysts to examine numerical data and hgihlight relationships between different data elements
• Regression analysis


  Discovering links between variables
• Data cleaning


  Ensuring any stored data is up-to-date and accurate with the DPA. E.g. removing old customers. It would reduce the size of any data table by removing redundant, incorrect or unnecessary data making it easier to work with and improve the data quality by removing irrelevant data.
• Location mapping


  Can be used to add geographic data to any analysis such as location of items or staff. Its known as real-time data.
• Open information systems


  Interact with other information systems (another database), or different platforms, to exchange data.
• Disadvantage of open information systems

  More risk of data loss or hacking
• Closed information systems are..

  Private and cannot exchange data with other systems. Access is limited but more secure that open systems
• Benefit of communication information

  Communicate easily around the world
• Limitation of communication

  Requires internet connection, bullying
• Benefit of education and training

  Useful information easy to access
• Limitations of education and training

  Costs money for resources
• Benefit of entertainment


  Helps people decide what to watch/ do
• Limitation of entertainment

  Bias reviews
• Benefits of planning

  People are more organised,

  People can function in groups a lot easier,

  People are aware of each other's commitments
• Limitations of planning

  Takes up a lot of time to find when people are available

  Many not be accurate
• Benefit of financial information

  Simplify complex information to create better informed decisions
• limitations of financial information

  Services interpretations may be incorrect so people create wrong financial decisions
• Benefit of research information

  Limitless amount of information thats readily accessible
• Limitations of research information

  Misinformation creates unreliable sources
• Benefits of location information

  Can locate where things are to assist with systems
• Limitation of location information

  Requires an internet connection or else its inaccessible