AIN3701
LEARNING UNIT 5
DATA ANALYTICS
5.1 INTRODUCTION, OUTCOME AND ASSESSMENT CRITERIA
5.2 THE WORLD OF DATA
5.3 DATA ANALYTICS FOR ACCOUNTING AND RELATED SERVICES
5.4 THE DATA ANALYTICS PROCESS
5.5 STEP 1: IDENTIFY THE QUESTIONS (I)
5.6 STEP 2: MASTER THE DATA (M)
5.7 STEP 3: PERFORM TEST PLAN (P)
5.8 STEP 4: ADDRESS AND REFINE RESULTS (A)
5.9 STEP 5: COMMUNICATE INSIGHTS (C)
5.10 STEP 6: TRACK OUTCOMES (T)
5.11 CLOSING REMARKS
5.12 REFERENCES
2|P a g e
,5.1 INTRODUCTION, OUTCOME AND ASSESSMENT CRITERIA
Your studies in AIN1501 introduced you to the concept of data. In AIN2601, you explored data in the
computerised system process, the database environment, relational database terminology, and how
databases are utilised in the business world (this included concepts like data warehouses, data
marts, data mining and OLAP). It is important to understand these concepts very well before
attempting to perform and understand data analytics. It is therefore advisable to revise this content
before continuing with this learning unit.
We will kick off with a discussion of the world of data. Herein we will also discuss an emerging
technology called big data. Once you understand these two concepts, we will focus on the data
analytics cycle.
Let’s explore the world of data …
5.2 THE WORLD OF DATA
In the current age, you will agree that data are all around us. Figure 5.1 indicates the increase of
data, from 2 zettabytes in 2010 to a forecasted 175 zettabytes in 2025. You will notice from this
graph that data are increasing exponentially, so imagine how much data will be generated by 2030.
Figure 5.1 Volume of data/information created, captured, copied, and consumed worldwide from
2010 to 2025 (Reinsel, Gantz & Rydning, 2018)
In September 2015, Marr (2015) stated the following:
“The data volumes are exploding; more data has been created in the past two years than in the
entire previous history of the human race.”
3|P a g e
,Look again at figure 5.1, and you will agree that this is still the case. To makes matters more complex
it is estimated that 90% of data are unstructured (Drury, 2022:671). For an explanation on structured
vs unstructured data, refer to learning unit 2.
This enormous increase in data gave rise to an emerging technology called big data, which can be
analysed by making use of data analytics tools. Examples of data analytic tools are machine learning
and deep learning.
Big data is covered in detail in AIN1501. Please study this section in AIN1501 before continuing to
the next topic in this section.
In your AIN1501 learning material, you would have noticed that there are numerous benefits that
big data offers. Unfortunately, certain risks also come with these benefits (also discussed in your
AIN1501 material). To mitigate or limit these risks, it is necessary to implement internal controls.
*** SPECIFIC CONTROLS TO BE IMPLEMENTED REGARDING BIG DATA ***
For organisations to limit their risks regarding big data, it is important for them to
implement the following (Richard et al, 2021: 8/74):
• The organisation should have a big data strategy that should:
o be agreed and signed off by top management
o aligned with the overall business strategy
o incorporate data security, privacy, measures, data landscape,
storage, cloud computing and cyber security
• Documented business and technical requirements should align with big
data projects and with the organisation’s strategy.
• Management should review that the analysis of the data extracted is
meaningful and that the organisation is reviewing and using the findings of
the analysis.
• If big data poses a risk to the organisation, it should be addressed in the
risk management process by updating the risk register.
• Service level agreements (SLA) entered between the organisation and third
parties should be scrutinised if third parties are analysing big data on the
organisation’s behalf.
• Roles and responsibilities should be defined for big data processing as well
as ownership.
4|P a g e
, • Make sure that access management controls (covered in AIN1501) are
implemented over big data.
• Change management controls (covered in AIN1501) should be
implemented over big data.
• Backup and disaster recovery controls (covered in AIN1501) should be in
place over big data.
• Staff should be trained on how to use big data, as well as the privacy
concerns regarding big data.
Activity 5.1
Ms Duma, the CEO of Ikhishi Likagogo, the company that manufactures breads, cakes, and South
African delights, has called a meeting with you, Ms Jansen (financial director), Ms Tau (product
manager of the cake division) and Mr de Villiers (CIO).
Ms Duma displayed the following slide in her meeting:
Figure 5.2 Revenue per division 2012–2022 (Van Staden, 2022)
5|P a g e
LEARNING UNIT 5
DATA ANALYTICS
5.1 INTRODUCTION, OUTCOME AND ASSESSMENT CRITERIA
5.2 THE WORLD OF DATA
5.3 DATA ANALYTICS FOR ACCOUNTING AND RELATED SERVICES
5.4 THE DATA ANALYTICS PROCESS
5.5 STEP 1: IDENTIFY THE QUESTIONS (I)
5.6 STEP 2: MASTER THE DATA (M)
5.7 STEP 3: PERFORM TEST PLAN (P)
5.8 STEP 4: ADDRESS AND REFINE RESULTS (A)
5.9 STEP 5: COMMUNICATE INSIGHTS (C)
5.10 STEP 6: TRACK OUTCOMES (T)
5.11 CLOSING REMARKS
5.12 REFERENCES
2|P a g e
,5.1 INTRODUCTION, OUTCOME AND ASSESSMENT CRITERIA
Your studies in AIN1501 introduced you to the concept of data. In AIN2601, you explored data in the
computerised system process, the database environment, relational database terminology, and how
databases are utilised in the business world (this included concepts like data warehouses, data
marts, data mining and OLAP). It is important to understand these concepts very well before
attempting to perform and understand data analytics. It is therefore advisable to revise this content
before continuing with this learning unit.
We will kick off with a discussion of the world of data. Herein we will also discuss an emerging
technology called big data. Once you understand these two concepts, we will focus on the data
analytics cycle.
Let’s explore the world of data …
5.2 THE WORLD OF DATA
In the current age, you will agree that data are all around us. Figure 5.1 indicates the increase of
data, from 2 zettabytes in 2010 to a forecasted 175 zettabytes in 2025. You will notice from this
graph that data are increasing exponentially, so imagine how much data will be generated by 2030.
Figure 5.1 Volume of data/information created, captured, copied, and consumed worldwide from
2010 to 2025 (Reinsel, Gantz & Rydning, 2018)
In September 2015, Marr (2015) stated the following:
“The data volumes are exploding; more data has been created in the past two years than in the
entire previous history of the human race.”
3|P a g e
,Look again at figure 5.1, and you will agree that this is still the case. To makes matters more complex
it is estimated that 90% of data are unstructured (Drury, 2022:671). For an explanation on structured
vs unstructured data, refer to learning unit 2.
This enormous increase in data gave rise to an emerging technology called big data, which can be
analysed by making use of data analytics tools. Examples of data analytic tools are machine learning
and deep learning.
Big data is covered in detail in AIN1501. Please study this section in AIN1501 before continuing to
the next topic in this section.
In your AIN1501 learning material, you would have noticed that there are numerous benefits that
big data offers. Unfortunately, certain risks also come with these benefits (also discussed in your
AIN1501 material). To mitigate or limit these risks, it is necessary to implement internal controls.
*** SPECIFIC CONTROLS TO BE IMPLEMENTED REGARDING BIG DATA ***
For organisations to limit their risks regarding big data, it is important for them to
implement the following (Richard et al, 2021: 8/74):
• The organisation should have a big data strategy that should:
o be agreed and signed off by top management
o aligned with the overall business strategy
o incorporate data security, privacy, measures, data landscape,
storage, cloud computing and cyber security
• Documented business and technical requirements should align with big
data projects and with the organisation’s strategy.
• Management should review that the analysis of the data extracted is
meaningful and that the organisation is reviewing and using the findings of
the analysis.
• If big data poses a risk to the organisation, it should be addressed in the
risk management process by updating the risk register.
• Service level agreements (SLA) entered between the organisation and third
parties should be scrutinised if third parties are analysing big data on the
organisation’s behalf.
• Roles and responsibilities should be defined for big data processing as well
as ownership.
4|P a g e
, • Make sure that access management controls (covered in AIN1501) are
implemented over big data.
• Change management controls (covered in AIN1501) should be
implemented over big data.
• Backup and disaster recovery controls (covered in AIN1501) should be in
place over big data.
• Staff should be trained on how to use big data, as well as the privacy
concerns regarding big data.
Activity 5.1
Ms Duma, the CEO of Ikhishi Likagogo, the company that manufactures breads, cakes, and South
African delights, has called a meeting with you, Ms Jansen (financial director), Ms Tau (product
manager of the cake division) and Mr de Villiers (CIO).
Ms Duma displayed the following slide in her meeting:
Figure 5.2 Revenue per division 2012–2022 (Van Staden, 2022)
5|P a g e
