Data Management

Learning outcome 1: Understand the concepts and fundamentals of data

1.1                       Explain the differences between a range of data types used in organisations

1.2                       Describe how organisations use various types of data

1.3                       Describe the advantages and limitations of different search algorithms

1.4                       Describe the advantages and limitations of different data storage methods and technologies

1.5                       Analyse the differences between a database, data warehouse and data lake

1.6                       Explain the considerations for an organisation when storing data

1.7                       Explain the principles of organising data

Learning outcome 2: Understand the purpose and process of backing up data

2.1                       Explain how data can be classified

2.2                       Explain the benefits of backing up data

2.3                       Explain the differences between a range of backup approaches

2.4                       Explain considerations to make when backing up data

2.5 Perform a backup, following a backup plan (Virtual Box)

The actual lesson to install Windows Server is here

Learning outcome 3: Understand how organisations use information systems

3.1                       Describe the benefits to an organisation of using information systems

3.2                       Describe the purpose of a range of common information systems

3.3 Describe functions of information systems 

Learning outcome 4: Be able to use data and information systems effectively, appropriately and securely

4.1                       Describe the differences between a data system and an information system

4.2                       Demonstrate how to secure a data system (Virtual Box)

4.3                       Demonstrate how to use a data system effectively  (Kaggle.com and Excel)

4.4                       Demonstrate how to link an information system to a data system  (Google Sites + Sheets)

Learning outcome 5: Understand the importance of preparing data for data analysis

5.1                       Explain how to ensure the quality of data

5.2                       Describe the stages of the ETL data integration model

5.3                       Discuss the considerations to make when selecting a data analysis tool

5.4 Source, cleanse and save a data set for analysis (Power BI)

Learning outcome 6: Be able to use visualisation to present information about data

6.1                       Explain the purpose of data visualisation 

6.2                       Explain the differences between a range of data visualisation methods  

6.3                       Select, create and present data visualisations based on a dataset (Power BI)