Data Management and Analytics

Understand data management.

• Purpose of data analytics and processes involved
• Examine large amounts of data to identify patterns, correlations or insights
• Data can be used to reduce costs
• Decisions can be made quicker
• New products and services can be tested through analytics
• Improving health care
• Machine Learning, Data Management, Data Mining

Data management decision-making:

• Strategy planning
• Productivity
• Product/service benchmarking

Legal, ethical and security issues:

• Data protection legislation
• Individual rights
• Security of commercial and personal data

Storing data:

• Structure/unstructured
• Security
• Data warehouse

Accessing data:

• Security
• Sharing

Assessment Criteria

• 1.1

  Outline the purpose of data analytics and the processes involved.

• 1.2

  Explain how an organisation can use a data management system to improve performance.

Be able to carry out data analytics for a given purpose.

• Statistical Techniques and Probability:
• Discrete data
• Continuous data
• Spreadsheets, statistical software eg SPSS
• Mean, median and mode
• Measures of dispersion, variance, standard deviation, range, interquartile and inter-percentile ranges
• Normal distribution
• T-Test
• Linear relationship
• Equality of the line of regression and correlation coefficient
• Regression line for non-linear relationship
• Presentation of data eg – bar charts, pie charts, histogram

Present findings:

• Prepare the data for analysis
• Analyse the data
• Validity, accuracy, relevance
• Presentation appropriate format to meet brief and audience
  Graphical and numerical data
  Reports, presentations, verbal communication

Assessment Criteria

• 2.1

  Analyse relevant data using appropriate statistical and probability operations.

• 2.2

  Summarise and present relevant findings from the data analysis in an appropriate format.