Data Analytics and Technology
1.Importance of Data Analytics for Accountants.
a.Data Analytics and Business
- Identify and explain the effects of data analytics on:
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:
- Import data from files and folders.
- Aggregate data from Excel, CSV and TXT files.
- Import data from Databases.
- Import data from web.
- Merge queries and tables.
- Transpose and Unpivot complex data
- Use conditional logic in ETL process.
- 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.
a.Relational Databases and SQL
- Describe a relational database and its anatomy.
- Understand how to create relationships in a database.
- 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.
- Demonstrate an understanding of how to UPDATE, INSERT and DELETE statement.
- 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.
- Power Query (in MS Excel)
- Microsoft Power BI – Free tool
- Microsoft Access