You’ll explore stakeholder presentations and strategies for sharing dashboards with clients. Then, you’ll focus on preparing for the BI interview process by refining your portfolio, updating your resume, practicing interview techniques that demonstrate your skills to recruiters and hiring managers, and more.
Learning Objectives
- Communicate with stakeholders about data insights to drive business decisions and goals.
- Practice putting dashboard insights into a presentation for stakeholders to give regular updates or answer specific questions and make forecasts.
- Prepare a resume to demonstrate relevant business intelligence experience and skills
- Distill insights from monitored data.
- Communicating the purpose and consequences of data insights.
- Utilize clear and effective presentation skills.
- Prepare a portfolio to demonstrate business intelligence skills.
- Practice interview techniques for a business intelligence role.
Communicate insights to stakeholders
Video: Welcome to module 4
In the upcoming lessons, you’ll delve into the critical non-technical aspects of being a successful business intelligence (BI) professional. While technical skills are vital, effective communication and presentation abilities are equally essential. As a BI professional, you must not only identify and manipulate data but also convey your insights in a way that resonates with stakeholders. This involves crafting visualizations and dashboards that align with business objectives. Moreover, your proficiency in communication is not just a workplace asset; it plays a pivotal role in career advancement, whether during job interviews, promotion discussions, or seeking educational opportunities. The upcoming lessons will specifically focus on stakeholder presentations, sharing dashboards with clients, navigating the BI hiring process, refining your portfolio, updating your resume for the BI field, and mastering interview techniques. These skills, combined with your technical expertise, will propel your BI career to new heights. Get ready for an exciting professional journey!
As you’re discovering,
working as a business intelligence professional
involves many technical skills. These include
things like knowing how to identify the right data, metrics, and KPIs for
a particular project, applying data modeling and pipelines to organize
and move data, transforming data
into a usable form, using that data to solve
problems and answer questions, and making visualizations
and dashboards that drive business
processes and goals. But BI also requires excellent communication
and presentation skills. After all, if you want your hard work to
really make an impact, it’s important to know how to effectively share
it with others. Successful BI professionals
can clearly demonstrate how the tools they create enable their clients to meet
business objectives. Plus, this is also important for your
career advancement! Having strong communication
and presentation skills can help you excel whether you’re interviewing for a job, discussing a promotion, or asking a supervisor about a new training or
educational opportunity. During the next few lessons, we’re going to concentrate on
these key workplace skills. They are an essential
complement to all the technical
knowledge that you’ve gained so far in this program. First, you’ll explore stakeholder presentations and sharing dashboards with clients. Then, you’ll shift your focus to the BI hiring process and strategies for refining
your portfolio. In addition, you’ll have the opportunity to
update your resume for the BI field so it clearly communicates all of
your new experiences. And finally, you’ll review interview techniques
that will help you demonstrate your skills to recruiters and hiring managers. Each of these lessons
will prepare you to take your BI career
to the next level. So, let’s get moving on your
exciting professional journey.
Video: Present your insights
- BI projects are not always linear, and presentations are a key part of communicating with stakeholders about project updates.
- BI presentations can be given in a variety of formats, including email threads, phone calls, and meetings.
- It is important to tailor the presentation to the audience, using clear, concise, and accessible language.
- The first presentation to stakeholders will likely be when sharing low-fidelity mockups.
- Later, the functional dashboard will be shared with users, and it is important to explain how to use it.
- Dashboards are constantly evolving tools, so it is important to keep presenting updates on recent changes or new opportunities.
Here are some additional key points from the text:
- It is important to empathize with the audience and understand their point of view.
- Technical jargon should be avoided, and explanations should be as simple as possible.
- Stakeholders’ concerns should be addressed, and feedback should be incorporated into the project.
- The presentation should be engaging and informative.
In this course, you’ve
learned that the steps of a BI project
aren’t always linear. Time passes, problems change, questions are refined — there’s constant evolution.
And presenting and communicating about
project updates is a key part of this process. If you earned your Google
Data Analytics certificate, you spent a lot of
time learning about presentation and
communication skills. In that context, you worked on data storytelling, creating
compelling slideshows, public speaking
strategies, responding to feedback and questions
from clients, and more. In the world of BI, the concept of presenting is
a bit different. So, let’s begin by clarifying what’s meant by
“presentation” in BI. People often think
a presentation has to happen in a
conference room. But many BI presentations
are simply email threads. With this in mind, going forward, think of a BI presentation as anytime you communicate with stakeholders about their
needs or project status. Note that this doesn’t include
answering questions or giving clarification about
minor project details. Presentations are
a bit more formal — even if they’re in
the form of an email. Whether your stakeholders
will receive your project updates
in their inboxes, on a phone call, at a meeting, or a
mixture of these is something you should
confirm early, when verifying project
scope and deadlines. And no matter which
format you’re using, always follow presentation and communication best practices. This includes engaging
your audience by taking the time to understand
their point of view. Think about their stake in the
project and what they hope to gain from the data
insights that you deliver. Next, be sure to prioritize the most
relevant information. This means starting with
high-level updates first, whether that’s something
about your current progress, a recent change, or your
plans for next steps. Use clear, concise, and
accessible language. An effective BI
professional recognizes that some people will have
used a dashboard before, but that’s not often the case. Even though BI is
a technical realm, it’s wise to avoid using
too much technical jargon. Explain your work as
simply as possible — this is another example of the importance of empathizing
with your audience. I find that it’s important
to tailor the words and level of detail for each
particular audience. For example, I know executives with technical
backgrounds who are going to want me to get deep into the details, while others
just want the bottom-line. Lastly, if a stakeholder shared a concern with you in
the previous meeting, it’s important that
your next presentation describes how you addressed that issue. And be
sure to confirm that they’re satisfied with
your plan going forward. The first time you present
to your stakeholders will likely be when sharing
your low-fidelity mockups. As you’ve learned,
these sketches give everyone a clear idea of your design intentions and they’re essential to getting
necessary feedback. Typically, you’ll have an
initial call or email when you ask if the idea you’re presenting meet
stakeholder goals. And because the mockup stages early
on in the design process, you can take in people’s
ideas and suggestions. Then, if necessary, easily move in a new
direction before you invest hours in
bringing your mockup to life on an actual dashboard. Later, you’ll share your functional dashboard
with your users. First and foremost, this involves explaining
how to use it. Even the clearest and
most intuitive dashboards deserve explanation. Here, you might provide a live demonstration
or you could create a slide deck about
how to interpret the visuals and
change the settings. Lastly, you are now aware that the majority of dashboards are
constantly evolving tools, so they don’t necessarily
have a “final state.” Just keep presenting updates on recent changes or
new opportunities that have been identified. Then, you’ll be able to
successfully collaborate with stakeholders and
keep your dashboards as fresh and helpful
as possible.
Reading: Business intelligence presentation examples
Reading
In this part of the certificate program, you started thinking about how to present your insights to stakeholders. Slide decks are a common tool that you can use to present to your stakeholders and even showcase and explain your dashboards. This reading will provide you with some tips and tricks for designing slide presentations. For more resources, you can also check out the Google Data Analytics Certificate content about developing presentations and slideshows.
Tips for building a presentation
Use the following tips and sample layout to build your own presentation.
Tip 1: Always remember audience and purpose
To develop an effective presentation that communicates your point, it’s important to keep your audience in mind. Ask yourself these two questions to help you define the overall flow and build out your presentation:
Who is my audience?
- If your intended audience is primarily high-level executives, your presentation should be kept at a high level. Executives tend to focus on main takeaways that encourage improving, correcting, or inventing things. Keep your presentation brief and spend most of your time on results and recommendations, or provide a walkthrough of how they can best use the tools you’ve created. It can be useful to create an executive summary slide that synthesizes the whole presentation in one slide.
- If your intended audience is comprised of stakeholders and managers, they might have more time to learn about new processes, how you developed the right tools, and ask more technical questions. Be prepared to provide more details with this audience!
- If your intended audience is comprised of analysts and individual contributors, you will have the most freedom—and perhaps the most time—to go in to more detail about the data, processes, and results.
- Support all members of your audience by making your content accessible for audience members with diverse abilities, experiences, and backgrounds.
What is the purpose of my presentation?
- If the goal of your presentation is to request or recommend something at the end, like a sales pitch, you can have each slide work toward the recommendations at the end.
- If the goal of your presentation is to focus on the results of your analysis, each slide can help mark the path to the results. Be sure to include plenty of views of the data analysis steps to demonstrate the path you took with the data.
- If the goal of your presentation is to provide a report on the data analysis, your slides should clearly summarize your data and key findings. In this case, it is alright to simply offer the data on its own.
- If the goal of your presentation is to showcase how to use new business intelligence tools, your slides should clearly showcase what your audience needs to understand to start using the tool themselves.
Tip 2: Prepare talking points and limit text on slides
As you create each slide in your presentation, prepare talking points (also called speaker notes) on what you will say.
Don’t forget that you will be talking at the same time that your audience is reading your slides. If your slides start becoming more like documents, you should rethink what you will say so that you can remove some text from the slides. Make it easy for your audience to skim read the slides while still paying attention to what you are saying. In general, follow the five-second rule. Your audience should not be spending more than five seconds reading any block of text on a slide.
Knowing exactly what you will say throughout your presentation creates a natural flow to your story, and helps avoid awkward pauses between topics. Slides that summarize data can also be repetitive; if you prepare a variety of interesting talking points about the data, you can keep your audience alert and paying attention.
Tip 3: End with your recommendations
Ending your presentation with recommendations and key takeaways brings the presentation to a natural close, reminds your audience of the key points, and allows them to leave with a strong impression of your recommendations. Use one slide for your recommendations at the end, and make them clear and concise. And, if you are recommending that something be done, provide next steps and describe what you would consider a successful outcome.
Tip 4: Allow enough time for the presentation and questions
Assume that everyone in your audience is busy. Keep your presentation on topic and as short as possible by:
- Being aware of your timing. This applies to the total number of slides and the time you spend on each slide. A good starting point is to spend 1-2 minutes on summary slides and 3-5 minutes on slides that generate discussion.
- Presenting your data efficiently. Make sure that every slide tells a unique and important part of your data story. If a slide isn’t that unique, you might think about combining the information on that slide with another slide.
- Saving enough time for questions at the end or allowing enough time to answer questions throughout your presentation.
Putting it all together: Your slide deck layout
This section will cover how to put everything together in a sample slide deck layout. This is just one way you can format your slide presentations–you may find that other layouts work better for you and your presentation style. That’s great! But this is a clear and concise starting point you can use to develop clear and effective slide decks.
First slide: Agenda
Provide a high-level bulleted list of the topics you will cover and the amount of time you will spend on each. Every company’s practices are different, but in general, most presentations run from 30 minutes to an hour at most. Here is an example of a 30-minute agenda:
- Introductions (4 minutes)
- Project overview and goals (5 minutes)
- Data and analysis (10 minutes)
- Recommendations (3 minutes)
- Actionable steps (3 minutes)
- Questions (5 minutes)
Second slide: Purpose
Not everyone in your audience is familiar with your project or knows why it is important. They didn’t spend the last couple of weeks thinking through the BI processes and tools for your project like you did. This slide summarizes the purpose of the project for your audience and why it is important to the business.
Here is an example of a purpose statement:
Service center consolidation is an important cost savings initiative. The aim of this project is to monitor the impact of service center consolidation on customer response times for continued improvement.
Third slide: Data/analysis
When discussing the data, the BI processes and tools, and how your audience can use them, be sure to include the following:
- Slides typically have a logical order (beginning, middle, and end) to fully build the story.
- Each slide should logically introduce the slide that follows it. Visual cues from the slides or verbal cues from your talking points should let the audience know when you will go on to the next slide.
- Remember not to use too much text on the slides. When in doubt, refer back to the second tip on preparing talking points and limiting the text on slides.
- The high-level information that people read from the slides shouldn’t be the same as the information you provide in your talking points. There should be a nice balance between the two to tell a good story. You don’t want to simply read or say the words on the slides.
For extra visuals on the slides, use animations. For example, you can:
- Fade in one bullet point at a time as you discuss each on a slide.
- Only display the visual that is relevant to what you are talking about (fade out non-relevant visuals).
- Use arrows or callouts to point to a specific area of a visual that you are using.
Fourth slide: Recommendations
If you have been telling your story well in the previous slides, the recommendations will be obvious to your audience. This is when you might get a lot of questions about how your data supports your recommendations. Be ready to communicate how your data backs up your conclusion or recommendations in different ways. Having multiple words to state the same thing also helps if someone is having difficulty with one particular explanation.
Fifth slide: Call to action
Sometimes the call to action can be combined with the recommendations slide. If there are multiple actions or activities recommended, a separate slide is best.
Recall our example of a purpose statement: Service center consolidation is an important cost savings initiative. The aim of this project is to monitor the impact of service center consolidation on customer response times for continued improvement.
Suppose the monitoring reports showed that service center consolidation negatively impacted customer response times. A call to action might be to examine if processes need to change to bring customer response times back to what they were before the consolidation.
Wrapping it up: Getting feedback
After you present to your audience, think about how you told your data story and how you can get feedback for improvement. Consider asking your manager or a colleague for candid thoughts about your storytelling and presentation overall. Feedback is great to help you improve. Just like most of the work you’ll do as a BI professional, presentations are an iterative process!
Reading: Case study: Ipsos – Informing stakeholders with compelling data visualizations
Practice Quiz: Activity: Design a slide deck for a business intelligence presentation
Reading: Activity Exemplar: Design a slide deck for a business intelligence presentation
Reading
Completed Exemplar
To review the exemplar for this course item, click the following link and select Use Template.
Link to exemplar: Minnesota traffic volume slide presentation
Assessment of Exemplar
Compare the exemplar to your completed activity. Review your work using each of the criteria in the exemplar. What did you do well? Where can you improve? Use your answers to these questions to guide you as you continue to progress through the course.
Note: The exemplar represents one possible way to complete the activity. Yours will likely differ in certain ways. What’s important is that your slide deck describes your BI project briefly and effectively.
This exemplar presentation is a brief slide deck that presents the Minnesota Interstate Traffic Dataset that you used in a previous activity. Your slide deck might appear very different from the exemplar if you used a different dataset or project. If so, ensure that your presentation still includes the following four categories of slides.
Introduction slide
Your first slide should include the following components:
- A title
- A visual element
- Optional: a subtitle
- Optional: Your name or company
In this exemplar, Slide 1 has the title “Minnesota Interstate Traffic Volume,” the subtitle “An in-depth analysis of traffic patterns on our interstate highways,” the Minnesota Department of Transportation logo, and a graphic of a car. It includes a simple color palette but few other details that distract from the introductory slide.
Business problem
In this exemplar, Slide 2 includes a very brief description of the business problem. The slide includes a picture of the Minnesota interstate with high traffic congestion. Some projects you work on might require more slides devoted to describing the business problem, but this simple slide is enough of a summary in this case.
Methods
Slide 3 of the exemplar describes the three primary charts used to visualize the data: Monthly Volumes, Weather, and Holiday Travel. It also includes a short description for each chart that suggests reasoning for separating the data into its own chart.
Insights
Slides 4–6 summarize the most important insights from the dashboard. Each slide features a chart that was introduced in Slide 3. These slides include images of each of the charts.
Slide 4 explains that August generally has the highest traffic volume, and February has the lowest. It points out an unusual dip in traffic in April 2018 and that aside from this dip the traffic trends are consistent from year to year.
Slide 5 focuses on weather and its effects on traffic. It also introduces a question: : What can the Minnesota Department of Transportation do to alleviate traffic issues on rainy days?
Slide 6 explains the holiday traffic trends. It supposes that the high traffic in August might be partially due to the state fair that takes place during that month. It also suggests that the holidays in January contribute to most of the traffic volume during that month.
Slide 7 examines when hourly traffic patterns emerge and if holidays impact them. It also explains that while to- and from-work commuter traffic has higher volume, there is not a significant difference during a holiday.
Slide 8 is the final slide and includes a quick signoff to conclude the slide deck presentation. This slide also helps the presenter transition into asking the audience if they have any questions.
Key takeaways
BI presentations can take many forms. A slide deck is a convenient and simple medium for sharing your insights with your stakeholders. You can customize a slide deck an infinite number of ways, while still communicating the most important information. The presentation you made in this activity will help you prepare for many slide decks you’ll make in your role as a BI professional.
Career focus: Projects and portfolios
Video: The business intelligence professional hiring process
Anita, a Senior Business Intelligence Analyst at Google, discusses the BI profession and how to navigate your job search.
- BI is everywhere and there’s a BI job for you, regardless of your industry preference.
- Entry-level BI professionals are typically called “Business Intelligence Analysts” or “Junior/Assistant Business Intelligence Analysts.”
- Research job opportunities to find which additional skills you should develop.
- You can find listings on job searching sites like LinkedIn, Indeed, or Glassdoor.
- Prepare for your interview by researching the company and rehearsing.
- Follow up with the interviewer after your final interview.
- Apply to more jobs and work on refining your BI skills while waiting for a response.
Hi! It’s great to be back with you to continue learning
about the BI profession. So far in this section, you’ve learned how to share
your work and insights with your stakeholders during a project. Now, you’ll apply those
same presentation skills to your career advancement. If you haven’t met me yet, I’m Anita, a Senior Business Intelligence
Analyst at Google. The job search can sometimes feel difficult and time-consuming. I encourage all of my
candidates to stay positive if they don’t get the first
role they interview for. It’s not uncommon for a person to interview for many different roles before they finally find the right match. Understanding how the BI industry works will help you navigate your job search. The first thing to know
is that BI is everywhere. In every industry, companies
need business intelligence to make informed decisions. Whether you have a passion
for healthcare, finance, human resources, retail, education, construction, or anything
else… there’s a BI job for you. You can begin searching for a BI job by narrowing your criteria
to a specific industry. Your query could be “business
intelligence healthcare” or “business intelligence finance.” If you don’t have a preference, you can search more generally by trying “entry-level business intelligence.” The second thing to know is that there are a few specific titles that a BI professional can have. Typically, an entry-level or
early-career BI professional will be called a “Business
Intelligence Analyst.” You may also encounter “Junior” or “Assistant Business
Intelligence Analyst.” Job offers with this title may expect anywhere from zero to
three years of experience. However, if a BI job asks for more years of experience than you have, you should apply anyway. As long as your skillset
matches the job description, it’s worth applying. With a strong portfolio and resume, you may be a great candidate even if you don’t have
a lot of experience. If you’re looking for a
job in a specific industry, the job listing may ask for skills or knowledge related to that field. You can research job opportunities in your industry of interest to find which additional
skills you should develop. Where exactly should you apply to BI jobs? You can find listings on
any job searching site, such as LinkedIn, Indeed, or Glassdoor. And a quick Google
search can help you find some more recent job opportunities. Through these sites or the
companys’ specific forms, you’ll be able to fill
out job applications and share your resume and portfolio. Otherwise, you can email the position’s hiring manager to apply. If you do get a response
to your application, you’ll likely interact with a
recruiter or hiring manager. They may reach out to you
with an email or a phone call to schedule an interview. If so, congratulations! You can prepare by researching the company, if you haven’t already, and
rehearsing for your interview. Some organizations may contact you for multiple rounds of interviews, especially if they’ve received
a lot of applications. You may be asked to describe
the projects in your portfolio or complete a short BI-related exercise, kind of like the activities you’ve been doing in this program. Once you complete your final
interview, the waiting begins. Arguably, this is the hardest part, but you can make the most of this time. First, you should follow up
by thanking the interviewer. You can also apply to more jobs and work on refining your BI skills. Hopefully, you’ll soon have
an exciting, new opportunity. Now that you know what to expect
from the BI hiring process, it’s time to prepare your
application materials. This includes your BI projects, portfolio, and an updated resume. Then, you’ll learn more
about interview techniques to help you get hired for
your first BI position.
Reading: Use prediction for better collaboration
Reading
In this program, you have been learning all about the role business intelligence professionals fill in an organization, how they build systems to store and move data where it needs to go, and how they create visualization and dashboard tools to share insights. You’ve also been learning about how monitoring can be used to provide stakeholders with updated information to inform decisions. Monitoring can also be used for predictive analytics. Normally this is not part of a BI professional’s role, but the tools they create can be used by data scientists to make predictions. In this reading, you’ll be introduced to predictive analytics and how BI professionals are sometimes involved.
Predictive analytics
Predictive analytics is a branch of data analytics that uses historical data to identify patterns to forecast future outcomes that can guide decision-making. The goal of predictive analytics is to anticipate upcoming events and preemptively make decisions according to those predictions. The predictions can focus on any point in the future—from weekly measurements to revenue predictions for the next year.
By feeding historical data into a predictive model, stakeholders can make decisions that aren’t just based on what has already happened in the past—they can make decisions that take into account likely future events, too!
One example would be a hotel using predictive analytics to determine staffing needs for major holidays. In the hospitality industry, there are many variables that might affect staffing decisions:
- the number of guests
- what services they’re using the most
- how much it costs to pay employees to be there
Being able to predict needs and schedule employees appropriately is key. So, a hotel might use a predictive model to consider all of these factors to inform staffing decisions.
Another example could be a marketing team using predictive analysis to time their advertising campaigns. Based on the successes of previous years, the marketing team can assess what trends are likely to follow in the coming year and plan accordingly.
Presenting dashboards
As a BI professional, you might not be performing predictive analytics as part of your role. However, the tools you build to monitor or update data might be helpful for data scientists on your team who will perform this kind of analysis. By presenting dashboards effectively, you can properly communicate to stakeholders or data scientists what the next step will be in the data pipeline, and set them up to take the tools you create to the next level.
Key takeaways
BI professionals collaborate with a variety of different teams and experts to support the business needs of their organization. Predictive analytics likely will not be a task you perform on the job, but you may work with teams who do. Understanding the basics will help you consider their needs as you design tools to support all of the teams who rely on your work!
Video: Heather: Personal career journey into BI
Heather is a data and analytics sales specialist who did not have a bachelor’s degree but was able to work her way up in the business world. She started by taking internships for free and then waitressing at night. She also used LinkedIn to connect with people in the technology industry and introduce herself. It took her about three years to land her first job in tech.
Heather believes that the skills she learned working in the restaurant industry, such as being able to multitask, remember orders, and be kind to customers, are transferable to the business intelligence field. She also enjoys being able to solve problems for her customers and help them grow their businesses.
Heather’s advice for others is to not be hard on yourself and to not be afraid to ask people questions. She also recommends connecting with people on LinkedIn and introducing yourself.
Hi, my name is Heather and I am a data and analytics
sales specialist. I was a waitress in New
York City for many years. I do not have a
bachelor’s degree and my grandfather was able to work his way up in business, and as a child, he told
me I could do the same, so I did that. I always thought that finding my voice in
an organization, starting small and
working my way up, that industry for me
just happened to be the technology
industry where I fell. I took internships for free and then I’d waitress at night. I would search on LinkedIn, I would friend
people on LinkedIn, and ask them to have a
conversation with me, and introduce myself
to them and say, “Hi, I’m Heather. These are
the things I’m good at, I’m good with people, I’m good with numbers, I know how to use
computer systems, I can be an asset on your team.” I probably did that
over and over again for about three years until I
landed my first job in tech. I think being a server or being a waitress or a bar attender
and anybody in any kind of restaurant industry has really wonderful
transferable skills to land a job in
business intelligence. I have a lot of clients. I work with a lot of partners, and I also work with a
lot of team members. The skills that I learned working in
the service industry, especially in New York City, is being able to multitask, have a lot of tables at once, being able to
remember your orders, being really kind
to your regulars. My customers, I view
them as my regulars just as I did when I bar
tended ten years ago, making sure that they’re happy. How many times do you go to a restaurant and
something isn’t right and if the server gives
you a tough experience, well, you’re going
to remember that. Now working in
business intelligence, I have a solutions
architect that I work with, I have a customer
engineer I work with, and other partners to help
me rally around a customer. When I solve a problem for
a customer and they’re efficiently utilizing our
data and analytics platforms, it brings me a lot of
joy because I know that I’m helping them
grow their business. I had maybe six or seven
hours worth of video calls and I was really on a roll with each one and I was
understanding their problems, I was able to talk about our
products in a technical, effective way, and it
made me feel so happy when I was able to communicate that way with my customers, with my extended team. Just don’t be hard
on yourself and don’t be scared to
ask people questions. Don’t be scared to
connect with people on LinkedIn and ask
for a conversation to introduce yourself. People don’t do that anymore, so set yourself apart and
put yourself out there.
Video: Incorporate business intelligence work in your portfolio
If you have completed any data projects, you should create a portfolio to showcase your work to potential employers. Your portfolio can include project planning documents, dashboards, presentations, and other relevant assets. You can host your portfolio on your own website or use an existing data sharing platform. When adding projects to your portfolio, you can include data, screenshots of dashboards, embedded dashboards, or links to access dashboards on Tableau. You should also explain your thought process, what work you did, and what you might do differently in the future. Finally, you should include a short biography describing your professional goals and interests. Be sure to follow your employer’s rules and regulations for data sharing when adding projects to your portfolio.
If you’ve earned your Google Data Analytics Certificate or completed any non-BI data projects, you may already have a portfolio. As a reminder, a portfolio is a collection of materials that can be shared with
potential employers. It’s the part of your job application with evidence of your accomplishments. If you don’t have a portfolio yet, it’s time to make one. This is a shareable, accessible way to showcase your work, which can give you an advantage over other candidates. Also, a well-rounded
portfolio demonstrates your background in non-data industries, and the transferable skills you’ve gained. Portfolios enable you to share project planning documents, dashboards, presentations, and any other assets that will help demonstrate your skills. You can host your portfolio on your own custom website or use an existing data sharing platform. Sites such as GitHub or Kaggle that you may have used for sharing data can be used to link out to dashboards. Tableau also has a social platform and sharing capabilities. Once you pick a platform, or multiple platforms, to host your portfolio, you can add your projects. Choose whether to represent your projects by including your data, screenshots of your dashboard, the embedded dashboard itself, or all of the above. Or you can include a link to access your dashboard on Tableau. When you’ve included
all the relevant parts from your project in your portfolio, explain your process. Describe your thought process, what work you did, and what you might do
differently in the future. It also helps to include
a short biography. By describing your professional
goals and interests, you can personalize your portfolio and make it stand out. Now, there’s one very important
thing to keep in mind: Some projects you work on
may deal with private data, so it’s critical to make sure that you follow your employers’ rules and regulations for data sharing. In cases where you cannot share any data or visuals from your project, you can include a summary of what you did in your portfolio. Which details you can share may be up to your employer, but it’s still important to document the roles you had on each
project you were part of. Now, it’s time to create
or update your portfolio. This will be a process you go through periodically
throughout your career.
Career focus: Join the field of business intelligence
Video: Refine your resume
Recruiters go through a lot of applications during the hiring process, so it’s important to have a compelling resume to stand out. This is especially true if you’re applying for a BI job. Here are some tips for updating your resume for a BI position:
- Include any degrees, certificates, or vocational training you’ve earned.
- List the BI skills you’ve learned, using specific language instead of general terms.
- Include the BI software you’re familiar with, such as BigQuery and Tableau.
- Create multiple versions of your resume, tailoring each one to the specific job you’re applying for.
- List your most recent and relevant experience at the top of your resume.
A strong resume is essential for catching the attention of recruiters and hiring managers. Once you’ve updated your resume, you’ll be ready to move on to the final component of the application process: interviews.
Recruiters go through
tons of applications during the hiring process. So having a compelling
resume is super important to becoming a candidate of choice. If you earned your Google
Data Analytics Certificate, you learned a lot about
creating an effective resume. Now we’re going to refine
your original resume to be appropriate for the BI world. Feel free to take a minute
to review those lessons now so you’re ready to proceed. Updating your resume will enable you to emphasize your BI skills. This is a good practice whenever you apply for new types of jobs. The first thing to do is
update the education section. Include any degrees and
certificates you’ve earned, as well as vocational training. Right now, you’re almost
done with this program. When you earn your certificate, you’ll be able to include
it in your resume too. For now, you can indicate
that you’re currently working toward your Google Business
Intelligence Certificate. Then, update the skills section with any new data know-how you’ve gained. This can include everything you’ve learned during this course and anything else that’s relevant to the workplace. Make sure to use specific
language to describe your skills. For example, “data
management” is not specific because there are many
ways to manage data. Instead, you could include “data cleaning” and “data merging” as
types of data management. The same applies for BI-specific skills. Rather than using “business intelligence,” you can list “data modeling”
and “dashboard building.” In your skills section or
a separate tool section, include the software
you’re most familiar with. Because you used BigQuery
and Tableau in this program, you can put them on your resume. If you learn other kinds of BI software after completing this program, make sure to include them as well. Now it’s time for some general resume tips that apply to any industry. If you’ve created resumes before, you may already know and
do some of these things. Still, hopefully the
following tips can serve as a helpful reminder. It’s always good practice
to create multiple versions of your resume. Each time you apply to a job,
you can tweak the language to best match the job description. For instance, if you’re applying to a BI job in the retail sector you can emphasize any past
retail experience you might have. Then, if you apply to a
job in a different field, you can remove those details to make room for other accomplishments. These tweaks can help
highlight specific skills that set you apart from other candidates. Another tip is to list the most recent and relevant information at the top of the education, skills,
and job experience sections. Recruiters and hiring
managers are very busy and may spend only a short
amount of time on each resume. It always helps to be brief
and direct to highlight the most important content
as quickly as possible. Now that you know some BI resume tips, it’s time to make these updates a reality. A strong resume is essential to catching the attention of
recruiters and hiring managers. With your completed portfolio and resume, you’ll be ready to move
on to the final component of the application process: interviews.
Reading: Resume-writing workshop
Reading
A key tool for your job search as a business intelligence professional is your resume. At this point, you may already have a resume that you have been using. Or, if you completed the Google Data Analytics Certificate lesson about resume-building, you have a foundation for creating your BI-specific resume. In this reading, you will learn more about refining your resume for BI roles. This will help you as you continue revising your resume for your future job searches!
Highlight your best qualities
When creating or revising your resume, you will need to consider what you want to highlight about yourself to potential employers.
For instance, if you have relevant work experience, then you will want to pick a format that highlights that.
If you are transitioning from a different career and don’t yet have relevant work experience, then you may want to pick a format that highlights your technical skills and portfolio projects. Some resume formats include a “Summary” or “Goals” section at the top to help candidates add context to their application, while other resume formats avoid these sections completely and uses that space for sections such as “Skills” and “Experience”.
Whatever format you pick, your resume should ideally be one page. If the one-page rule seems limiting, think about the purpose resumes serve in the hiring process overall. Resumes are short documents designed to communicate the most important information about yourself to recruiters and hiring managers at a glance. This is also why it’s important to consider what you want to highlight most—this is one of the first impressions you make on potential employers!
Writing about your experience
As you think about how to represent your work experience on your resume effectively, it might be helpful to refer to these best practices:
Focus on your accomplishments first, and explain them using the formula Accomplished X, as measured by Y, by doing Z.
- These statements help you communicate the most important things a recruiter or hiring manager is searching for—the impact of your work.
- Whenever possible, use numbers to explain your accomplishments. For example, “Increased manufacturing productivity by 15% by improving shop floor employee engagement,” is better than “Increased manufacturing productivity.”
Phrase your work experience and duties using Problem-Action-Result (PAR) statements.
- For example, instead of saying “was responsible for two blogs a month,” phrase it as “earned little-known website over 2,000 new clicks through strategic blogging.”
Describe jobs that highlight transferable skills (those skills that can transfer from one job or industry to another).
- This is especially important if you are transitioning from another industry into business intelligence.
- For example, communication is a skill often used in job descriptions for business intelligence professionals, so highlight examples from your work experience that demonstrate your ability to communicate effectively.
Describe jobs that highlight your soft skills.
- These are non-technical traits and behaviors that relate to how you work.
- Are you detail-oriented? Do you have grit and perseverance? Are you a strong critical thinker? Do you have leadership skills?
- For instance, you could give an example of when you demonstrated leadership on the job.
- Showing is always more effective than telling.
This is almost always the hardest part of crafting a resume, especially if you are transitioning from a different career field. However, if you take a moment to think deeply about your previous work experience, you’ll likely discover that you can find ways to represent your work experiences in a way that highlights your ability to do things important to business intelligence roles, such as thinking critically or making data-driven decisions.
Putting your skills to the test
Many companies use algorithms to screen and filter resumes for keywords. If your resume does not contain the keywords they are searching for, a human may never even read your resume. Reserving at least one bullet point to list specific programs you are familiar with or skills you have is a great way to make sure your resume makes it past automated keyword screenings and onto the desk of a recruiter or hiring manager. The following are some best practices for adding skills to your resume effectively.
Get help from the real world
Reviewing real-world resumes is always a great idea. It can help you get a feel for how others in the industry are representing their experience and skills. You can find resumes on job sites, LinkedIn, or even just by searching for “business intelligence resume.” There are many ways to represent your technical skills, and taking a moment to understand how other professionals do this may give you some great ideas.
What skills to add
The skills section on your resume likely only has room for 2-4 bullet points, so be sure to use this space effectively. You might want to avoid listing soft skills or non-technical skills here. Instead, this is a great chance for you to highlight some of the skills you’ve picked up in these courses, such as:
- Strong analytical skills
- Pattern recognition
- Relational databases and SQL
- Strong data visualization skills
- Proficiency with spreadsheets, SQL, DataFlow, and Tableau
Notice how the skills listed above communicate a well-rounded skill set without using more words than necessary. The skills section summarizes what you’re capable of doing while listing the technology and tools you are proficient in.
Fine-tuning your resume
One of the most important ways you can adapt your existing resume is by making it specifically tailored to BI roles. Below are links to two resume examples. The first example is a rough draft an entry-level BI professional created early on in her resume writing process. The second resume is her final draft. This version is more specific about the roles she is interested in and how her previous experience can be applied to BI roles. Refer to both versions below:
Resume drafts
To access the resume drafts, click the following links and select Use Template.
Video: Kelly: Tips for resume preparation
Kelly shares her experience as a sustainability financial analyst at Google and how she created a TikTok channel to help others find mentors and resources for breaking into the business intelligence field. She emphasizes the importance of tailoring your resume to each specific job posting, using the STAR method to highlight relevant skills and experiences. She also advises job seekers to be succinct and precise in their resume bullet points, only listing relevant experiences, and not to be afraid to take that first step and apply for jobs.
I’m Kelly. I’m a sustainability financial
analyst here at Google, and basically, what that means, is that I work with
the global sustainability team here. And I partner with them for
any of their external commitments, and any of the work that they do. So when I first started figuring out
what I wanted to do and when I first started trying to get internships and get
my foot in door at these big companies, it was really hard for
me to understand what I needed to do, how to find mentors, what resources were
available to even get my foot in the door. And so, I found an opportunity and
I wanted to create that opportunity for others, and
that’s why I created my TikTok channel. I wanted to make sure that all of
those things that I really struggled with to find,
other people could find them more easily, and also just show people that,
if I could do it, they could do it too. So, how I actually tailor my resume to
different experiences and make sure that my relevant experience is shown for
specific roles that I’m applying to, is creating a document listing out all
of the experiences that you’ve had, using the star method. So for each role, list out the situation,
the task, the action, and the results, and have that readily available for all
the jobs or experiences that you’ve had. And then you can actually take the job
posting, whichever one that you’re seeing, whichever job you would like to apply to, and take the relevant
experience that you have, and map it directly to the job posting. So,
for example, if the job requires data and analytics, or the job requires
working with stakeholders, and you have that in
your relevant experience, make sure to put that at
the top of your resume. Whatever job posting you’re looking at,
if they have keywords for skills required, make sure that you have those words
listed on your resume as well. You might have really great
analytical experience, But if you’re leaving out those keywords
that recruiters are looking for, you might get missed. Second of all, when actually looking at
your resume, make sure to be succinct, and precise with the bullet points that you’re
listing, as well as the experience. A lot of the times people will want to
write out paragraphs on their experiences, and what they did. But the more clear and precise that you
can make it, the easier it’s going to be for a recruiter to actually
read through your resume. And lastly, make sure that your
listing only relevant experiences, if there are things that
you’ve had on your resume for couple of years that might not be
very relevant to the job posting. Make sure to take those out so that the things that are relevant
can shine on your resume as well. If I could give one piece of
advice to someone who wants to get into business intelligence,
it’s just apply. Don’t be afraid to take that first step,
and get your foot in the door, because, the rest will follow. And, some of my favorite advice that
I’ve ever gotten was, it’s going to be better than you even imagined, so
just let yourself get to that place. [SOUND]
Practice Quiz: Activity: Stand out with a compelling, focused resume
Reading: Activity Exemplar: Stand out with a compelling, focused resume
Reading
Completed Exemplar
To review the exemplar for this course item, click the following link and select Use Template.
Link to exemplar: Business intelligence analyst resume
Assessment of Exemplar
Compare the exemplar to your completed activity. Review your work using each of the criteria in the exemplar. What did you do well? Where can you improve? Use your answers to these questions to guide you as you continue to progress through the course.
Note: The exemplar represents one possible way to complete the activity. Your resume will likely differ in certain ways. What’s important is that your resume clearly communicates a snapshot of your skills and experience and what value you would bring to the role.
Your resume should include the following components:
- Personal information: Your name, location, phone number, email address, and links to your LinkedIn® profile (if you have one) and portfolio
- Education: A list of any school you attended after high school in reverse chronological order. Each listing should include the school’s location; the degree, diploma, or certificate you earned; and the dates that you attended. It should also include internships, apprenticeships, and any professional certifications or credentials you hold, including the Google Business Intelligence Certificate and the Google Data Analytics Certificate (if applicable).
- Experience: A list of at least three of your past positions in reverse chronological order. Each listing should include the company name, the location, your job title, the dates you worked there, and a description of your responsibilities. Your descriptions should be tailored to the job description of the position you are seeking, emphasizing BI-related and transferable skills. Your experience section should also use Problem-Action-Result (PAR) statements to describe your relevant accomplishments and measurable impact in your previous roles.
- Skills: A list of the skills you have that are most relevant to the position, including skills you’ve learned in this program, skills you’ve gained in previous education or positions, and your strengths and competencies
Your resume should also be:
- Free of spelling, grammatical, and punctuation errors
- As concise as possible
- No more than 1–2 pages in length
Video: Interview preparation strategies
When preparing for a BI job interview, it is important to highlight your data experience, demonstrate your BI knowledge, and list your skills. You should also be prepared to answer questions about your coding languages and tools. Finally, express your enthusiasm for the role and ask follow-up questions.
If you’ve experienced
a job interview before, you probably know what to expect. You might feel some nerves
as you prepare for it, excitement as you discuss your
passions and accomplishments, and anticipation as you
wait for a job offer. But what should you know
about BI job interviews? What might give you an advantage in a competitive job market? The most important topic to
discuss is your data experience. This includes your non-BI data background, and, of course, your hard
work during this course. Projects that you complete in a learning environment
are extremely valuable, even if you don’t have
an official role yet. After all, BI professionals
learn on the job every day. It’s half the fun. Then, you want to demonstrate
your BI knowledge. You can do this by explaining
your step-by-step process, like you did while creating
your portfolio write-ups. Here, you can get into specifics. Explain your project planning process, your approach to data modeling, and your dashboard design strategies. Discuss any obstacles you encountered and how you overcame them. Did you ask for help, try a new approach, or research solutions? Explaining how you dealt with a problem in your project will
highlight your resilience, positive attitude, and creativity. You also want to list your skills. It might be tempting to talk
mostly about your people skills or how you’re a very hard worker. While this is true, interviews also wanna know
about technical skills. Describe the coding languages and tools you’re familiar with. Make sure to discuss the
technical skills you developed in this course, such
as Python and Tableau. For instance, on our Finance
and Data Analytics team, we sometimes search for a candidate who knows a particular coding language. Other times, it’s important
for us to hire someone who can pick up multiple
new languages quickly. Some hiring managers may even ask you to complete a coding exercise to demonstrate your skill level. If so, make sure you understand which skills they will assess so you can prepare accordingly. I always tell candidates, “Don’t be afraid to ask follow-up questions if you don’t have all
the information you need.” No recruiter expects
you to know everything. And, finally, talk about
how excited you are to start in a BI role. Interviewers want to hire someone who is both competent and enthusiastic. The hiring manager may guide
most of your interview. They may steer the conversations
with their questions, but you should make sure to
discuss each of these topics before your interview is over. In general, it also helps to remember some universal
interview best practices. Answer the interviewer’s
questions descriptively and prioritize the most
relevant information. Speak with a friendly
but professional tone. Whether you’re in an
in-person or virtual setting, dress appropriately, make eye contact, and keep your body language
as relaxed and natural as you can. That last one might be
tough if you’re nervous, but that’s okay. Interviewers understand that you are eager to make a good impression. It will also help to think
of questions you may want to ask the interviewer. You’ll want to know what kinds
of data you will work on, how many people are on
the company’s BI team, and what you would be
expected to do in the role. You can also ask about the
organization’s commitment to inclusivity or their
philosophy on work-life balance. By asking your own questions,
you demonstrate your interest and that you’re a proactive learner. After all, asking the right questions is a BI professional’s first job. Each interview is a new opportunity to show off how hard you’ve worked and get one step closer
to an amazing new job.
Reading: Proactive approaches to the interview process
Reading
Throughout your career as a business intelligence professional, you will interview with potential employers during the application process. Interviewing is a key skill for your job search. In this reading, you’ll consider how to identify BI-specific roles during your job search as well as general tips for interviewing.
Identify BI roles
Part of your job search will include identifying roles that are specific to the BI field. As you learned in previous lessons, there are many types of data-related jobs, but there are key elements you can search for in job descriptions to determine if a job is actually a BI role.
- Search for keywords: An easy way to identify BI-specific roles is to search for job listings that refer to business intelligence directly. Often, BI-related roles will be listed as “business intelligence analyst” or “business intelligence engineer.” Previously, you learned about the differences between BI analysts and engineers, but these terms are often used interchangeably; be sure to read the job description and requirements carefully to decide if you’re a good fit for the role.
- Consider skills and responsibilities: You can also determine whether or not a role is BI-specific by what skills and responsibilities are listed in the job description. Often, data analyst roles are focused on analyzing historical data provided by existing systems. BI roles are usually more focused on developing database systems and delivery processes to provide intelligent access to stakeholders.
- Research: A large part of your job search is going to be research. When trying to determine whether or not a role is actually BI-related, researching the business that posted the job listing can reveal the kinds of roles that exist within their organization and how they approach data roles in general.
General tips for job interviews
- Find connections between the job listing and your resume: First, re-read your resume and the job description to help you draw lines between the two. Where do they connect? Then, as you interview, include specific keywords or phrases from the job description that match skills you possess or achievements you have accomplished previously in your career.
- Focus on data: As you start to think about things you want to highlight in your interview, don’t forget to include data. This helps your interviewer understand not just your overall achievements, but how big of an impact you made. What data can you provide that tells the story of your experience in terms of the needs of this position? The “equation” we suggest includes something like this: I accomplished X as measured by Y doing Z. Here’s an example: “I increased customer satisfaction by 22% in three months by designing a new digital onboarding process.” If you don’t have access to this kind of data from a previous position, you can still indicate the scope you were accountable for and strengthen the language you use when describing your responsibilities by including action words like provided, created, developed, supported, implemented, and generated. For example: “I implemented a new meeting-scheduling system that saved employees time and improved morale.”
- Look back at past work experiences: Review your work history. That may not sound like something you need to prepare for, but most of us have done more than we think and it’s easy to forget some of our own wins (and lessons learned from mistakes). Think of examples of times you achieved something so you are prepared to answer questions like “Tell me about a time when…” or “How would you approach this situation…?” People often diminish or ignore their past job experiences if they don’t immediately apply to the position they’re applying for. However, you bring a lot of transferable skills from past jobs that might be useful—you just have to frame them the right way. For example, you might have gained communication skills from a previous position that can help you connect with stakeholders in a BI role.
- Come ready with questions: Next, come to the interview with your own questions, such as “What are some upcoming projects I’d be working on? What current goals is the company focused on? Can you tell me about the team I’ll be working with?” This shows you care about understanding the company and the position you’re applying for. Besides, this is your opportunity to interview them as well.
This type of preparation will help you feel confident and prepared to talk about yourself and the position. It will enable you to fully explore your experience, the position, and your career aspirations and really connect with the employer.
Key takeaways
Job interviews are a necessary part of your job search. As you continue working towards your career as a BI professional, thinking about how you approach the interview process early can ensure that you are prepared for them when the time comes. And being prepared means you can impress potential employers and move forward on your career journey!
Reading: Prepare for interviews with Interview Warmup
Reading
Now that you have developed new skills and knowledge in business intelligence, it’s time to start preparing for interviews. Interview Warmup is a tool that helps you practice answering questions to become more confident and comfortable throughout the interview process.
Get started
Follow these steps to start a five-question practice interview related to BI and data analytics:
- Go to grow.google/interview-warmup.
- Click Start practicing.
- Select Data Analytics to open an additional menu.
- Select Business Intelligence as the field you wish to practice.
- Click Start.
The interview will last about 10 minutes, and the questions will vary with each attempt. During each interview session, you will be asked two background questions, one behavioral question, and two technical questions. You are encouraged to try as many practice interviews as you want.
You can also review complete lists of business intelligence interview questions or general interview questions if you’d like to focus on a particular topic.
How it works
Interview Warmup asks you interview questions to practice delivering your responses verbally. Your answers will be transcribed in real time, allowing you to review how you responded. In addition, Interview Warmup’s machine learning algorithm can detect insights that can help you learn more about your answers and improve the way you communicate.
Here are a few examples of questions the tool might ask:
- How does a career in business intelligence line up with your longer term career goals over the next few years?
- How might your role as a business intelligence analyst impact an organization? What are some of the challenges of using business intelligence?
- How would you test integrity of data across various sources?
- What are some examples of data visualization deliverables? How would you use one of these deliverables?
- Tell me about some of the potential challenges of working with stakeholders. What would you do on a project to prevent or overcome these challenges?
Here are some of the insights that Interview Warmup provides:
- Talking points: The tool lets you know which topics you covered in your answer, such as your experience, skills, and goals. You’ll also be able to view other topics that you might want to consider covering.
- Most-used words: The tool highlights the words you used most often and suggests synonyms to broaden your word choices.
- Job-related terms: The tool highlights the words you used that are related to the role or industry in which you are preparing to work. You’ll also be able to view an entire list of job-related terms that you might want to consider including in your answer.
Interview Warmup gives you the space to practice and prepare for interviews on your own. Your responses will be viewable only by you, and they won’t be graded or judged.
Key takeaways
Practicing for interviews is an important skill for your career in business intelligence. Using Interview Warmup can help you practice interview questions and receive feedback in real time. As you practice, you will gain confidence and be able to prepare more polished responses for common interview questions.
Review: Present business intelligence insights
Video: Wrap-up
In this concluding message, Terrence emphasizes the importance of effective communication and presentation skills in a Business Intelligence (BI) role. He highlights the significance of articulating project insights and accomplishments to various stakeholders, including recruiters, hiring managers, co-workers, and employers. The summary encapsulates the journey through the BI program, covering the value of communication skills, preparation for the BI career, updating the portfolio, enhancing the resume, and gaining interview tips. Terrence encourages the learner, acknowledging their significant progress in the course and expressing congratulations on reaching this point.
Hi there, it’s Terrence again. Now it’s time to wrap up this section and move on
to your graded assessment. In your future BI role, communicating your insights and accomplishments will
be an essential skill. It’s important to explain to
recruiters, hiring managers, co-workers, and employers how you worked on your projects. For example, you
learned the value of communication and
presentation skills when sharing your dashboards
with stakeholders, then you focused on preparing
for your career in BI. You learned about
the hiring process and how to look for a job, then worked on your portfolio. The skills you learned while creating presentations
can help you update your portfolio with
your latest BI achievements. After that, you
updated your resume to reflect the skills you
developed during this program, and finally, you learned some interview tips to prepare
you for your job search. By now, you’re well on your way to start
applying for jobs. You’ve made significant
progress in this course, congratulations.
Reading: Glossary terms from module 4
Reading
Business intelligence presentation: A communication with stakeholders about their needs or project status
Quiz: Module 4 challenge
Which of the following pieces of information are typically included in a business intelligence presentation to stakeholders? Select all that apply.
Updates on project status
Information about stakeholder needs
Describing how you addressed a concern previously raised by stakeholders is one of four presentation and communication best practices. What are the other three? Select all that apply.
- Engage your audience by taking the time to understand their point of view.
- Speak in clear, concise, and accessible language.
- Prioritize the most relevant information.
Fill in the blank: When sharing your_____, the sketches are intended to give stakeholders a clear idea of your design intentions.
low-fidelity mockups
Fill in the blank: If you are interested in business intelligence jobs in any industry, keep your criteria _____ during your job search by searching for “entry-level business intelligence” positions.
What are the benefits of having a portfolio to share during an interview? Select all that apply.
- Demonstrate your transferable skills.
- Demonstrate your data-industry skills.
- Showcase your work.
Fill in the blank: When answering interview questions, it is beneficial to prioritize the _____ details about your professional background.
relevant
At what point in the process should a business intelligence professional confirm the format in which business intelligence presentations will be conducted?
Early, when verifying project scope and deadlines
What is shared with stakeholders in order to provide them with a clear idea of your dashboard design intentions?
Low-fidelity mockups
What job titles are most common in entry-level business intelligence jobs? Select all that apply.
- Assistant business intelligence analyst
- Business intelligence analyst
- Junior business intelligence analyst
Which of the following pieces of information should you include when sharing your portfolio? Select all that apply.
- What you might do differently in the future
- Your thought process
- The work you performed