Difference between revisions of "Professional Practices and Data Analysis Division"

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Audit, Evaluation, and Risk Branch (AERB)<blockquote>Return to [<nowiki/>[[Audit, Evaluation, and Risk Branch (AERB)|AERB]]] homepage</blockquote>
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'''<code>Return to [<nowiki/>[[Audit, Evaluation, and Risk Branch]]] homepage</code>'''
  
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=== Data Analysis section ===
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== Data Analysis ==
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The Data Analysis (DA) section assists in the identification, acquisition, preparation, and analysis of data from CRA's data stores (e.g., Agency Data Warehouse, Data Marts, Mainframe, Corporate Administration System, Revenue Ledger, and local systems). The DA section generates data analytics reports and assists in identifying new data requirements in support of internal audits, program evaluations, and risk assessments.
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Greetings!
  
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The data analytics produced by the DA section helps to study key risk and fraud indicators, to identify errors or misuse, to improve business efficiencies, to verify process effectiveness, and to influence business decisions. Data analytics is typically used as evidence in support of findings and conclusions during the execution of engagements and other value-added consulting and continuous auditing activities.
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We are a small team of data analysts in the Audit, Evaluation, and Risk Branch at the Canada Revenue Agency. We produce data analytics and business intelligence for enterprise risk management and the assurance and advisory domains of internal audit and program evaluation.
  
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The DA section helps to ensure compliance with the ''Institute of Internal Auditors (IIA) Standards (1210.A3)'', which states: "Internal auditors must have sufficient knowledge of key information technology risks and controls and available technology-based audit techniques to perform their assigned work".
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Our hope is that this GCwiki platform will enable us to share our data analysis practices with you, and to connect with the artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) community of professionals to learn and discover new things.
  
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According to the recent book, Data Analytics (Institute of Internal Auditors Research Foundation, 2016), there are four broad categories of data analytics: descriptive, diagnostic, predictive, and prescriptive. The DA section currently produces the first two types of data analytics. Descriptive analytics involves reporting on past events to characterize and summarize what has happened through the use of statistics, trends and patterns, classification, and stratification. Diagnostic analytics provides insight into why certain trends or specific incidents may have occurred through the use of metrics, attributes, and duplication/gap analysis.  
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If our articles and podcasts inspire you, please reach out to us to let us know, and let's start a discussion! We are eager to learn new things.  
  
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Through the power of data analytics, the DA section continues to help management with oversight, insight, and foresight.
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Data Analysis Section<br>
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Professional Practices and Data Analysis Division<br>
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Internal Audit and Evaluation Directorate<br>
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Audit, Evaluation, and Risk Branch<br>
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Canada Revenue Agency<br>
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Email: aerbdatag@cra-arc.gc.ca
  
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=== Professional Practices ===
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=== Data Watcher Articles ===
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<li>Article</li>
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<li>Article</li>
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=== Data Watcher Podcast ===
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<ol reversed>
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<li>Podcast</li>
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<li>Podcast</li>
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<li>Podcast</li>
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<li>Podcast</li>
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<li>Podcast</li>
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== Professional Practices ==
 
The Professional Practices Section actively supports audit/evaluation/advisory practitioners with methodology, tools and guidance to perform their work to the high standards of competence and value-added espoused by the Branch.
 
The Professional Practices Section actively supports audit/evaluation/advisory practitioners with methodology, tools and guidance to perform their work to the high standards of competence and value-added espoused by the Branch.

Latest revision as of 15:13, 27 August 2021

Return to [Audit, Evaluation, and Risk Branch] homepage

Data Analysis

Greetings!

We are a small team of data analysts in the Audit, Evaluation, and Risk Branch at the Canada Revenue Agency. We produce data analytics and business intelligence for enterprise risk management and the assurance and advisory domains of internal audit and program evaluation.

Our hope is that this GCwiki platform will enable us to share our data analysis practices with you, and to connect with the artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) community of professionals to learn and discover new things.

If our articles and podcasts inspire you, please reach out to us to let us know, and let's start a discussion! We are eager to learn new things.  

Data Analysis Section
Professional Practices and Data Analysis Division
Internal Audit and Evaluation Directorate
Audit, Evaluation, and Risk Branch
Canada Revenue Agency
Email: aerbdatag@cra-arc.gc.ca

Data Watcher Articles

  1. Article
  2. Article
  3. Article

Data Watcher Podcast

  1. Podcast
  2. Podcast
  3. Podcast
  4. Podcast
  5. Podcast
  6. Podcast

Professional Practices

The Professional Practices Section actively supports audit/evaluation/advisory practitioners with methodology, tools and guidance to perform their work to the high standards of competence and value-added espoused by the Branch.

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