Data Analytics and Technology

Learning Outcomes

1.Importance of Data Analytics for Accountants.

              a.Data Analytics and Business

  • Identify and explain the effects of data analytics on:
    1. Businesses
    2. Accounting

              b.Data Analytics Process

  • Describe the IMPACT cycle.
  • Explain why the order of processes of IMPACT cycle make sense.

             c.Data Analytics skills for Accountants

  • Describe the data analytical skills needed by accountants.

2. Connect, Collect and Clean Data

            a. Extract, Transform and Load Data (ETL)

  •         Explain what is ETL and why it is important for an Accountant.

           b.Application of ETL

  •       Apply and demonstrate ETL skills to:
    1.  Import data from files and folders.
    2. Aggregate data from Excel, CSV and TXT files.
    3. Import data from Databases.
    4. Import data from web.
    5. Merge queries and tables.
    6. Transpose and Unpivot complex data
    7. Use conditional logic in ETL process.
    8. Group and summarize data.

3.Data Modelling and Data Analysis Expressions.

       a. Data Analytics approaches

  •  Understand various approaches of data analytics – Classification, Regression, Similarity matching, Clustering,             Profiling, Link Prediction, Data reduction.

        b. Calculated Columns and Measures in Data models

  •        Understand the difference between a calculated column and a measure in data models.
  •        Demonstrate an understanding of when to use a calculated column or a measure in data models.

       c. Data Analysis and data modelling skills

  •       Demonstrate how to create relationships in data models
  •      Apply slicer technique to use disconnected tables in data models
  •      Understand the importance of data granularity in data modelling.
  •      Demonstrate an understanding of using Calendar for Time Intelligence analysis.
  •      Apply various data analysis expressions in data modelling.

4.Data Visualization and Business Intelligence.

a. Purpose of Data Visualization

  • Determine the purpose of data visualization.
  • Demonstrate an understanding of what type of data to use for data visualization. [Qualitative or Quantitative data].

b. Selecting the right visual and working with visuals.

  •   Understand what type of chart or graph to choose for data visualization.
  •  Demonstrate how to create and manage data hierarchies and data drill-down in a visual.

c.Business intelligence and Online services

  •    Define business intelligence.
  •    Demonstrate how to publish analysis and reports on cloud services.
  •    Understand how to create dashboards and insights from datasets using online services.

d.Data Visualization and Artificial Intelligence

  •   Understand how to use natural language query in a BI tool to explore datasets.
  •   Understand how to use Q&A feature of a BI tool to create a visual.


5.Data Analytics in Auditing and Accounting

a.Different types of analytics in auditing

  • Understand various types of analysis for auditing.
  • Understand descriptive audit analysis.
  • Demonstrate an understanding of predictive and prescriptive analytics.

b.Identify useful KPIs with Data Analytics.

  • Identify useful KPIs considering the management requirements.
  • Evaluate underlying data used for KPIs.
  • Understand how to create a dashboard using KPIs.

6.Data Mining

a.Relational Databases and SQL

  • Describe a relational database and its anatomy.
  • Understand how to create relationships in a database. 

b.SQL Basics

  • Use SELECT statement to query a database.
  •  Eliminate duplicate rows and sort the dataset.
  •  Demonstrate how to use Expressions in a SELECT statement.
  • Refining datasets using WHERE clause with multiple conditions.

c.Working with multiple tables

  • Understand Operations on datasets (Intersection, Difference and Union).
  • Demonstrate how to use INNER & OUTER JOINS and UNIONs.
  • Understand how to create Subqueries.

d.Summarizing and Grouping data

  • Demonstrate an understanding of how to use aggregate functions in a query.
  • Understand how to use GROUP BY clause.

e.Modifying Datasets

  • Demonstrate an understanding of how to UPDATE, INSERT and DELETE statement.

7.Cyber Security

  • Define Cybersecurity.
  • Identify unique traits of advanced malware.
  • Analyzing modern cyberattack strategy.
  • Recognizing opportunities to limit and counter threats.à
  • Understand how to keep an organization safe from malware infections.
  • Understand how to create advanced threat protection policies.

8.Analyze Big Financial Data with Python

  • Identify the importance of Python to analyze big financial data.
  • Understand 2D and 3D plotting of financial data with Python.
  • Understand how to retrieve and analyze data with Pandas.



  1. Power Query (in MS Excel)
  2. Microsoft Power BI – Free tool
  3. Microsoft Access
  4. Python