• To provide an overview of the class agenda and the expected learning objectives

Coach welcome apprentices to lesson and run through the session outline and learning objectives. Coach can run an ice breaker from here .

• Understand the data lifecycle and describe what happens at each stage

The data life cycle describes what happens to a piece of data from when it is created to when it is deleted and everything in between. Apprentices need to know the name of each stage (technically usage is not part of the BCS definition of the cycle, but we have included it as we think it is relevant) and understand what activities happen at each stage. Use this as an opportunity to understand the group's understanding of data and their expectations of how it should be used. At each stage discuss likely concepts they will need to understand- for example, during creation, how is the data created and what is its purpose? How is it stored? Is it being stored and processed lawfully? At what point does the data become out of date or obsolete? What are the data laws that govern its use? There is a short activity for apprentices to think about the data they use regularly so they can start to think about their work in data terms.

• Understand the Data Analytics Lifecycle and describe what happens at each stage

Following on from the data lifecycle we also want apprentices to think about the data analytics lifecycle. It is important apprentices know about both and are able to distinguish between them. The data analytics lifecycle may be called different things by different providers, but for us we follow the plan, data prep, analyse, model, refine and communicate cycle. You should run through each stage and discuss possible activities that might occur at each. The activity should help apprentices think about this. Encourage apprentices to think about their own projects and see how they can apply these stage to it. Most of this module is about helping apprentices think about how to plan out their projects. Most of the cycle will be covered in the two bootcamps.

• Identify who the key decision makers and contributors are in your project

The rest of the module will focus on the plan stage of the project and the first part of this is identifying stakeholders. In this section you want to guide apprentices to think about those who have influence on their projects and therefore how closely they need to manage them. For example, line managers should be regularly informed whereas the sales staff may need to be updated at the end of the project. You will show apprentices the different types of stakeholder which will help them consider who theirs are so they can start to plan how to manage them.

• Understand how to manage stakeholders in your project

Now stakeholders have been identified it is time to consider how they are to be managed. The key focus of this section is to help apprentices understand how they can elicit the right information from their stakeholders. If you know what a stakeholder wants then you can keep them at arms length by ensuring your work is in line with their expectations. A helpful tool for apprentices is the types of questions they ask which you will help them consider. There is an exercise which will allow apprentices to practice planning questions to help understand stakeholder expectations.

• Understand the information required to build a project brief

This is a shorter section in terms of your input as you give the floor to apprentices to discuss their experiences around communicating with stakeholders. What success have they seen? Where have things gone wrong? Try and summarise their thoughts and add some anecdotes from your own experience.

• Justify the use of Big Data in analysis by considering the benefits and drawbacks

A crucial part of planning a project is designing a project brief that captures all the required information in one document that all stakeholders can access and agree to. You will guide and discuss with apprentices the what, when, who and why of a project so they understand what information they need to convey. This includes deadlines, problem statements, stakeholders and deliverables. There is an exercise for apprentices to review three examples of a brief to discuss what is good and bad about them.

• Understand the difference between verification and validation

Two concepts which arise often in data analytics are validation and verification and apprentices need to understand the differences between them. Validation occurs throughout a project to ensure that phases completed meet an external requirement (client expectations, data in a consistent format with its source, regulatory compliance like GDPR has been met). Verification happens at the end of a phase to ensure that success criteria have been met, for example checking a dashboard captures the correct information as set out in your project brief. This concept will be addressed again in the ETL section as validation occurs at the end of the extract phase to ensure data is in the right format while verification happens at the end where the loaded target is checked against the project brief criteria.

• Understand how to set a hypothesis

The final part of this session is to help apprentices think about whether their project will involve some sort of statistical analysis. We will cover the actual statisticals in later sessions, but apprentices should know that any hypothesis should be stated in a project brief. Explore the difference between a null and alternate hypothesis and ask apprentices if they can come up with their own examples.

• To recap the day

Go through the learning objectives again and show apprentices the assignments and check for their understanding. You may want to create a kahoot quiz, but if you do please make sure you have submitted a create resource request first. Remind apprentices to complete session attendance log and update their OTJT.

• To provide an overview of the class agenda and the expected learning objectives

Coach welcome apprentices to lesson and run through the session outline and learning objectives. Coach can run an ice breaker from here .

• Understand the different types of data you may use in a project

In this session the them of planning a project will continue through apprentices considering what the data may look like in their projects. Note, we are talking high level (quantitative vs qualitative) not the specific data types that programming languages use (string, number, float, etc). Please avoid talking about programming data types as you will likely confuse the apprentices. The aim of this section is for apprentices to plan out what tools, visualisations and models they may need to build based off the type of data they will receive. Understanding whether their data is quantitative or qualitative will allow them to anticipate issues and predict the best course of action they will need to follow. This section can lead to interesting discussions around specific data (is time discrete or continuous?)

• Understand where your data has come from

In a project brief, apprentices need to state where their data has come from as this will allow them to show considerations such as legal compliance and permissions. Go through each type of source and discuss what sort of data this might be and how they might want to use it. In all likilihood the data apprentices will use in their roles will be propietary and they need to demonstrate they have taken the necessary steps to ensure it is protected. Use this to discuss what steps they can take to protect their data and find out what types of data they regularly use. This is followed by a discussion on the DPA and GDPR. DPA is obsolete but they need to know it (for some reason?) in the KM2 exam. This will be removed in the 2.0 content. Focus more on GDPR and stress that if apprentices are using any PII they must show their compliance. Ask apprentices if they have much experience with GDPR and draw on any anecdotes they give.

• Explain the difference between structured and unstructred data

As well as considering the source and types of data they will be using, apprentices should also think about its structure. People tend to think of data as row and columns, and while much of the data apprentices will be using will be in this format, it is not all the data that exists in the world (or even their role). Apprentices will make use of unstructured data all the time (emails, videos, phone calls, etc) and this section can open their eyes to the possibility of applying data analytics technique to improve their role (how can they join information from emails/reports to make decisions more quickly and effectively?). A common cause of confusion is Excel spreadsheets. WHile the data within may be stored in a structured format, the sheet itself is unstructured as it does not conform to strict rules and itself is not easily readable.

• Understand the different file extensions that may be used in your role

Most of the data apprentices will receive will be digital, but what are the file types? Put apprentices into breakout rooms and have them look at the different file types. They should discuss the properties of the file type and consider when they would be of use. Note, most of the examples are actually text files but have had to be put in that way so apprentices can see the raw source code. Files like CSV and RTF are difficult for us to read, but computers are able to process them in a way which makes them human readable. To demonstrate this, you can download the CSV and RTF files which the computer should open as Excel and Word files respectively. Apprentices may be aware of other file types so discuss with them what they use. If they mention PDF, tell them to run as it is a difficult format for computers to read data from.

• Understand the ETL process

A concept that may appear in their exam is ETL, which is why we introduce it here. It is also possible apprentices may build their own warehouses or pipelines and will need to follow this process. This section will help apprentices appreciate that when combining large amount of data from across an organisation, then ETL is the way to go. Go through each stage and discuss likely actions that will happen in each. Help apprentices see the benefit and consider whether this is a project they could put in their portfolio.

• Recap the day

Go through the learning objectives and assignments and clarify anything apprentices may still not understand. Go to Kahoot! and run the module 1 Kahoot quiz (apprentices can download the app on their phone, or just use their browser). Make sure apprentices update tehir OTJ and complete the SAL.