Data Processing and Manipulation

The "Data Processing and Manipulation" course provides students with a comprehensive understanding of various data processing and manipulation concepts and tools. Participants will learn how to handle missing values, detect outliers, perform sampling and dimension reduction, apply scaling and discretization techniques, and explore data cube and pivot table operations. This course equips students with essential skills for efficiently preparing and transforming data for analysis and decision-making.

Skills Covered by the Course

• Handling missing values

• Outlier detection

• Sampling methods

• Dimension reduction

• Data scaling

• Discretization techniques

• Data cube operations

• Pivot table creation

• DEC2 L2: Determine which tools and techniques to use to explore or solve a variety of business issues and communicate the results of analysis with impact to a range of audiences.

• DEC2 L1: Recognise where external data sources can be integrated with own datasets.

• DSC1 L2: You apply a range of techniques to transform data into valid and purposeful information. Undertakes analysis and data science activities to deliver analytical outputs in accordance with customer needs and as tasked within the project team.

• DSC2 L2: Provides quality assurance of data science work using appropriate guidance and frameworks and takes account of ethical considerations.

• DSC5 L2: Applies robust and ethical techniques in the transformation of data from one format or medium to another in line with organisational policies and procedures.

• DSC5 L2: Uses data exploration techniques to help evaluate the characteristics of a dataset and its suitability for subsequent analysis.