Data Acquisition, Preparation and Evaluation

In this practical, interactive workshop participants will build their knowledge of the processes required to acquire, clean and integrate from various sources and evaluate its quality.

This workshop allows participants to apply what they learned in the Analytical Thinking for Decision Making and Data Visualisation Principles and Best Practices workshops to acquiring and preparing data for analysis. Participants will work in small groups to clean, integrate and evaluate real-world data sets using the techniques taught in the workshop.


This course is intended for people who are required to acquire, evaluate and prepare high quality data for analysis, either for themselves or for other people.

Learning Outcomes

At the end of the course participants will be able to:

  • Choose the most appropriate data for an analysis project
  • Describe the various types and formats of data available for data analysis
  • Explain the relative merits of each type and format for data analysis
  • Evaluate the quality of a data set and identify if a data set biased and unbiased
  • Apply a range of techniques to minimise or eliminate data quality errors
  • Enrich data by integrating, transforming and aggregating various data sets

Course Agenda

Module 1 – Obtaining and Evaluating Data

  • Sources of Data for Analysis
  • How to determine what data is needed?
  • Data that exists vs does not exist
  • Internal vs external data
  • Structured, semi-structured and unstructured data
  • Data Quality Concepts
  • What is data quality?
  • How to assess data quality
  • How to identify biased data
  • How much data quality is enough?
  • How to Assess Data Quality?
  • Overall data set quality
  • Row data quality
  • Column data quality
  • Data quality and bias

Module 2 – Preparing, Integrating and Enhancing Data

  • Preparing Data
  • Improving/ correcting row-level data quality
  • Improving/ correcting column-level data quality
  • Standardising data values
  • Integrating Data
  • Joining multiple data sets
  • Handing time series data
  • Aggregating data across multiple dimensions
  • Enhancing Data
  • Derive new data by splitting, joining and calculating
  • Create new categories by grouping values
  • Pivoting and unpivoting data sets
  • Data Acquisition, Preparation & Evaluation Mini-Project


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Why study with Alpha?

Innovation and creativity born from experience

We are thought leaders in instructional and learning journey design and holistic solution architects. We have extensive finance and investments experience combined with skills application to deliver performance improving results. We develop immersive learning environments that maximize time to productivity, support talent retention and added value to improving quality of hires.

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We are focused on mining the embedded organisational intellectual capital for the benefit of the next generation. We create and curate best in class practice gathered from our experience with the leading financial institutions. We design our programmes with the end in mind – what results are you trying to achieve with this intervention? What metrics will we set ourselves to achieve that?

Generation Proof

Quality and innovation, using current market and industry best practices, have made us a trusted partner in delivering dynamic and motivating training for the financial and capital markets. Our programmes are generation proof and responsive to evolving learner needs and styles. Our solutions use a multi-stakeholder engagement strategy that expands beyond relationships between the learner and learning provider. We create connections with managers, peers and the wider business to drive impactful return on investment..

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