Identify business requirements relating to big data

Analysts need to learn key aspects of business operations (including industry terminology and jargon) to understand the data generated from the business. They also need to determine how much of this domain knowledge needs to be implemented in the analysis for operational decision-making.

For example, suppose the business is in the transport industry. In that case, there are key terminology and business processes that are specific to that industry that an analyst needs to be familiar with, such as mileage, logistics and delivery times.

Key skills of a data analyst

The first section of the following video discusses the key skills of a data analyst. Pay close attention to the five (5) essential skills, what it means to have these skills and why they matter.

Based on what you learnt from the video segment, ‘Key Skills Data Analysts Possess’, answer the following two (2) questions. Click the arrows to navigate between the questions.

Check your understanding

Foundation skill: Learning

Analysts must have the ability to learn new industry-related information. Each data analyst project will differ greatly based on different industries and types of business operations. Therefore, analysts need learning skills that enable them to modify their behaviour following exposure to new information in each project.

Access resources to learn the domain knowledge of business processes

Analysts need to assess the resources available to support the project. This includes evaluating the technology, tools, systems, data and people available for the project. To obtain this knowledge, analysts need to:

• access various sources of information made available to them by the organisation (e.g. various types of documentation, policies, procedures, legislative requirements and guidelines)
• participate in kick-off meetings to gain key information that sets out the purpose of the project
• identify and collaborate with key stakeholders of the project (e.g. CEO, CFO, supervisors, department managers and other project team members)
• take an inventory of the resources required for the project to identify any gaps.

Foundation skill: Reading

Analysts must be able to read, understand and interpret information from various sources. Each data analysis project is based on different information that relates to the business. This information is obtained from various sources such as policies, procedures, legislation, instructions, specifications, guidelines etc. Therefore, analysts need reading skills that enable them to go through various information sources and interpret this information accurately to complete their work.

The second section of the following video discusses how analysts need to assess information through an analytical lens. When watching the video, pay close attention to the following skills:

• visualisation
• strategy
• problem-oriented
• identify relationships between data
• big-picture and detail-oriented thinking.

Based on what you learnt from the video segment, ‘Assessing Information Through an Analytical Lens’, complete the following task.

Check your understanding

Case study scenario

XYZ Manufacturing

XYZ Manufacturing is a global manufacturer of household furnishing products. They have production facilities in several countries, including Canada, France, Mexico, Germany and the United States.

XYZ Manufacturing documentation:

• XYZ Manufacturing_Operations and Procedures_v1.pdf
• XYZ Manufacturing_Dataflow diagram_v1.pdf

Case study activity 1

Read the case study scenario and refer to the organisational documents provided to learn about how XYZ Manufacturing conducts its business operations. Practise using your analytical skills to learn about the business domain of XYZ Manufacturing focusing on the big picture.

Based on your understanding, answer the following two (2) questions. Click the arrows to navigate between the questions.

Case study activity 2

Focus on the ‘Production department’ of XYZ Manufacturing and read through the documents to find relevant information about this work area.

Based on the domain knowledge you’ve obtained regarding the workflow and operations of the production department, answer the following three (3) questions. Click the arrows to navigate between the questions.

The fundamental purpose of analytics is to help managers solve problems and make decisions. ¹⁹

The first step for using big data in any business is to identify the opportunities to use it. Businesses need to ensure that the effort put into analysing big data can actually add value to their operational workflows and decision-making process.

Think of problems as opportunities

The opportunities for using big data in business decision-making arise due to different circumstances and would generally concern business problems.

The following video discusses how data can be used in problem-solving. When watching this video segment, pay close attention to the basic problem types typically found in businesses that analysts may have to deal with.

Case study activity 3

Scenario continued…

XYZ Manufacturing is facing several challenges in its manufacturing operations, including:
- Quality control issues: The company faces quality control issues in its manufacturing process, resulting in increased production costs and product defects.
- Supply chain management: The company is finding it difficult to manage its global supply chain, leading to delays in delivery and increased inventory costs.
- Predictive maintenance: The company is struggling with maintenance costs due to unexpected equipment failures and downtime.

Task: Identify opportunities to use big data for each of the challenges in XYZ Manufacturing.

Follow this process.

• First, try to pinpoint the problems that need to be analysed using big data.
• Then, determine the problem type that needs to be solved.
• Finally, consider the opportunities to use big data to address these challenges.

Expand the answer to see some of the ways big data can be used to address these problems.

How to identify opportunities?

To use big data for operational decision-making, analysts first need to identify opportunities to do so. Therefore, analysts may need to:

• access available data summaries and sources – to identify problem areas of the business that may need further analysis
• participate in departmental meetings with key stakeholders (e.g. CEO, CFO, supervisors, department managers and other operational staff ) – to gain key information on existing issues in data, operational workflows and systems
• get information on existing reports – to identify any gaps where other types of data need to be captured as a requirement for operational decision-making
• use other methods – such as participating in forums (e.g. lunch and learn sessions) and intranet forums where issues may be posted.

Case study activity 4

XYZ Manufacturing has provided you with the following data summary of product defect reports and associated downtime from their existing reports. Investigate the data summary provided to you below and identify opportunities for using big data in XYZ Manufacturing.

Question 1

After investigating the data summary from XYZ Manufacturing, which two (2) sub-categories will you choose to focus the analysis on?

Question 2

What are the opportunities for analysing big data related to the chosen product sub-categories? 

Question 3

Using the ‘Data strategy’ skills considering people, processes and tools, how can the problem be broken down further to identify opportunities for analysis?

Previously we learnt that business problems are opportunities for using big data for operational decision-making. However, as business problems can come in all shapes, sizes, and levels of complexity, it is vital to define the boundaries of the analysis at the start of the project. To do this, we follow a process commonly referred to as ‘scoping’.

Scoping is done to determine the size, scale, boundaries and limitations of business requirements. This can be accomplished by doing the following:

• Frame the problem - This involves identifying a specific objective or goal and defining the problem associated with the operational decision-making requirements.
• Frame the report - This involves identifying how analysis results should be presented and the nature and specifications of the reporting requirements.

Developing a strategy to determine all the operational decision-making and reporting requirements is an important step in any data analysis project and may involve tasks such as:

• identifying operational questions that must be answered
• determining areas of possible operational improvement
• selecting operational issues that can be resolved based on collected data
• determining allowable resources available to perform operational decision-making analysis.

Frame the problem

Framing the problem is critical to the success of the project. This step helps to identify the scope of the operational decision-making requirements and define the project's purpose. Analysts are required to carry out the following tasks when framing the problem. ²⁶

• Recognise what specific problems they need to solve in the analysis.
• .Identify the main objectives of the project
  • Identify what needs to be achieved in business terms.
  • Identify what needs to be done to meet the needs.
• Specify the problem – This would require the analysts to write the problem statement and key project requirements in an appropriate organisational document and share them with key stakeholders.
• Additionally, analysts should consider the project's objectives and success criteria.
  • What is the team attempting to achieve by doing the analysis?
  • What will be considered “good enough” as an outcome of the analysis?

Analysts must clearly document the project's scope so that it can be referred to at different stages of the analysis. This will ensure that all analysis tasks are performed within the scope. It is important to note that the entire analysis is based on the problem statement and project requirements documented at this stage. Therefore analysts need to document and record industry-specific information clearly and share this information with the project team and key stakeholders.

Frame the report

Framing the reporting requirements is critical to ensure results from the analysis for operational decision-making are usable, meaningful and fit for purpose. The purpose of a report is to present relevant business information in an organised and structured format that is easily understandable by its intended audience.

Nature of the report

As a result of big data analysis, reports are typically generated through interactive reports and dashboards using business intelligence tools/platforms. There are a variety of report types that are typically used by businesses, and their selection depends on various reasons. Read the article ‘A Guide to the top 14 types of reports with examples’ by datapine.com to learn more. ²⁷

For the purpose of this module, we will be more focused on those report types that will allow businesses to make operational decisions.

• Analytical reports – This report type contains useful information to facilitate the decision-making process. It provides a mix of qualitative and quantitative insights based on statistics and historical data.²⁸
• Operational reports – These report types are used to track, measure and improve processes, workflows, and performance in ongoing operational areas. ²⁹ These reports help to answer critical business operational questions on the spot.
• What-if scenario analysis reports – These reports are used to evaluate how a combination of factors can impact future events/outcomes. Businesses can use these reports to predict future outcomes based on historical data patterns and explore different scenarios that can affect these outcomes. ³⁰

Gathering reporting requirements

Analysts are required to carry out the following tasks when gathering reporting requirements.

• Recognise what specific report type they need to create for the analysis.
• Identify the main objectives of the report.
  • Identify what needs to be included in business terms – key metrics, specific business information.
  • Identify what needs to be done to meet the reporting needs.
  • Identify the timeliness of the reports and the data that the report is based on.
• Clearly define the report– this would require the analysts to write down the objective or goal of the report in an appropriate organisational document and share it with key stakeholders.
• Additionally, analysts should consider whether there are:
  • organisational guidelines that should be followed – specific brand and style guidelines to be used
  • recommended tools to generate the reports
  • specific formats and preferred data representation types to be included in the report.

Analysts must clearly document the report's nature and scope so that it can be referred to at different stages of the analysis to ensure all reports are generated within scope.

Asking effective questions using SMART goals

We previously learnt about SMART goals in Topic 1. Now, we will explore how these are used for determining the scope of operational decision-making and reporting requirements by using questioning techniques such as:

• leading questions
• closed-ended questions.

Follow the SMART methodology

The following is a sample list of questions to help you gather all the information related to operational decision-making and reporting requirements in line with the business goal/objective.

TIP: Requirements will answer all the important questions. Therefore, consider the what, when, who and how when formulating questions.

Expand to see details of the following.

Case study activity 5

Task 1

Read the requirements outlined in the scenario carefully to understand the business problem, opportunity or the purpose of the analysis. Then, write a clear and concise statement that summarises the goal of the analysis.

Task 2

Considering the S.M.A.R.T. goals, write five (5) questions to obtain operational decision-making requirements from stakeholders.

Task 3

Considering the S.M.A.R.T. goals, write five (5) questions to obtain reporting requirements from stakeholders.

Task 4

Use XYZ Manufacturing’s Business Requirements Gathering form_template_v1.docx to record the information from the previous tasks (1, 2 and 3):

• the goal of the analysis (from Task 1)
• the questions for gathering operational decision-making requirements ( from Task 2)
• the questions for gathering reporting requirements (from Task 3) 

Confirming business requirements involve verifying their accuracy and completeness in line with the business objective of the project. All the requirements must be collected and evaluated to ensure they meet the stated guidelines to achieve the desired outcomes.

Why do we need to confirm requirements?

The requirements gathered in the previous steps have the potential to be incorrect or incomplete. This can be due to various factors. For example, there may be:

• misinterpretations of the business requirements
• changes in the business requirements
• new additions to the previously stated requirements
• new systems or tools used for the analysis
• changes in the datasets received
• new datasets to be used for the analysis that were previously not available.

Therefore, both operational decision-making and reporting requirements need to be confirmed to ensure their interpretation is accurate and complete before moving forward with the analysis tasks.

How to confirm requirements?

Once the business requirements have been gathered, this information needs to be confirmed by discussion and consultation with the appropriate personnel (Stakeholders) associated with the analysis project, such as:

• Project supervisor
• Subject matter experts involved in the project
• Relevant department managers
• Other stakeholders, if involved in the project.

Confirmation needs to be formally requested and evidence of this confirmation should be kept as supporting evidence as a valuable reference throughout the analysis project. Some examples of how formal confirmation can be obtained are as follows.

• Face-to-face discussions and meetings – Meeting minutes can be recorded and kept as supporting evidence of the confirmation and feedback received from the stakeholders.
• Email requests and responses – Email responses from stakeholders can be kept as formal records and supporting evidence of confirming parameters for the analysis.

Regardless of the communication method used, it is important to:

• use effective and clear language to communicate your ideas
• ask the right questions (e.g. open questions)
• to inquire about advice
• request for confirmation of the established parameters
• provide evidence of the established parameters– this can be in the form of:
  • word documents
  • Excel spreadsheets with numerical information and visualisations.

For example, let us investigate the standard protocols that should be followed when consulting your supervisor via email.

Email Etiquette

When writing an email, ensure that you:

• address the email to the correct person(s) email address
• use the standard email template as recommended by your organisation
• include the following main elements within the structure of the email:
  • subject-line
  • openers (greeting)
  • body
  • closings (sign-off)
• include all necessary information regarding the data anomalies
• check for any errors in grammar, spelling and punctuation

Refer to the How to Write a Proper Email: Make the Right Impression | Grammarly to gain more insights and tips on using proper email etiquette. The following video further discusses the recommended protocols that you need to consider when writing a formal email.

Case study activity 6

Your role: You are working as a Business Operations Analyst at XYZ Manufacturing.

Your task: Draft an email to your supervisor ‘Peter Brown’, requesting confirmation of the business requirements for operational decision-making and reporting you’ve determined for the project. You must use XYZ Manufacturing’s standard email template to draft your email.

XYZ Manufacturing_Email template_v1.docx

Note: Assume you are including an attachment of the document you created to record the details of key requirements with this email. Ensure that you mention information regarding this attachment in the body of the email for the email recipient's attention.

Previously, you learnt that there are organisational guidelines and specific procedures that were followed when obtaining and confirming operational decision-making and reporting requirements from stakeholders.

Some of these procedures involve:

• using organisational templates or forms to document requirements and specifications
• following the organisation’s communication protocols when consulting with stakeholders.

Another procedure that analysts will often have to follow is when requesting access to specific data sources and summaries.

Legislative requirements

Issues such as the physical location of where the data is stored, the security of access to the data, the lawful use of the data and the type of personal information need careful consideration. Strict legislation needs to be adhered to throughout data collection and analysis.

Data access policy principles

In Topic 2, you were introduced to various data protection and privacy legislation and regulations that organisations need to comply with. Personal information may need to be removed from datasets before running analytics and careful filtering of data from systems may be required. Therefore, organisations have data access policies in place to ensure that data is shared only with authorised personnel for pre-determined purposes. Also, it is important to note that not all data within an organisation is accessible to all employees.

For example, refer to the ‘Data Access Policy Principles’ from the Australian Government’s Department of Social Services official website.

Data access procedure

Generally, the steps to request data access are as follows.

Step 1 – Identify the specific data sources and summaries required for the analysis.

• Data sources – this may be specified in terms of table names, field/column names
• Data summaries - this may be specified in terms of the dashboard or report names.

Step 2 – Document the required data source details and summaries required using a documentation method that is recommended by the organisation. For example, an organisation may require a data access form template to be filled in with the required details. Some data may have legislative requirements concerning their access and use. In such situations, this information must also be recorded in the formal documentation for data access.

Step 3 – Collaborate with the relevant department or teams within the organisation to request data access. This can be done by:

• emailing the relevant department/team with an attached copy of the completed data access form
• recording details in an online ticketing system and submitting the request to the relevant department/team.

Case study activity 7

Recall the XYZ Manufacturing data analysis project scenario where the objective is to find the products that generate the lowest profit. The management also wanted to decide whether to stop producing some of the low-profit products and whether to focus on producing more profitable products.

Within this context, assume that you need to analyse all manufacturing costs and transactions of products within the past six months. Refer to the XYZ Manufacturing_Data flow diagram_v1.pdf to identify the data you need for the analysis.

You were also informed that there is a Power BI report/dashboard called ‘XYZ Manufacturing Financials’ that may have relevant data summaries required for the analysis. However, you currently do not have access to view this report/dashboard.

Refer to the following sample data access policy of XYZ Manufacturing.

Task 1: Within this scenario context, list all the data sources you would require for the analysis and all the data summaries.

Task 2: Draft an email to the IT department requesting access to the required data.

Topic summary

Congratulations on completing your learning for this topic Identify business requirements relating to big data.

In this topic, you have learnt the following:

• Skills to learn the domain knowledge of business processes
• How to identify opportunities to use big data
• How to scope operational decision-making and reporting requirements
• How to confirm operational decision-making and reporting requirements
• How procedures are followed to request for data access.

Assessments

Now that you have completed the basic knowledge and skills in this topic, you are ready to complete the following assessment event.

• Assessment 3 (Case Study)

What’s next?

Next, we will learn how to interpret big data sources and summaries.