Shadowing Practice: think like a business analyst in tech (3 core skills + solving case study) - Learn English Speaking with Video

After graduating college in 2019, I started my first job as a business analyst. (my 1st day at Spotify, 2019) I was excited but I was also really scared because I studied music business at NYU and I didn't have any direct business analytics background, so there were a lot of things I had to learn from scratch.

And with two and a half years of learning from my mentors, colleagues, and through my fair share of trial and errors, these are the three most important skills to have as a business analyst in tech. (1: technical skills, 2: problem solving skills, 3: strategic thinking & business sense) I'll talk about what they actually are with real case examples and how you can learn them whether you're a student or in your full time job.

If you're interviewing, these are also the key skills that companies are evaluating you on for a BA interview.

Before we get started, Thank you GlassesUSA.com for sponsoring today's video.

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And I'll leave the links of the glasses I'm wearing in the description box.

So, let's get it started!

Skill no. 1, your technical skills.

Especially if you want to work in tech with an analyst title, SQL is the most important than Excel Google Sheets.

SQL is a language that enables you to pull millions and billions of user information stored in databases to answer business questions.

Let's say you work at Netflix, and some of the questions that you would be asked would be things like how many monthly active users do we have per region per day?

Or specifically, how many monthly active users do we have per region that have finished watching Squid Game?

If you know SQL, you can easily pull these numbers and answer questions fast instead of having to wait for data scientists to employ for you or rely solely on dashboards.

How can you learn SQL?

So I'm going to talk about if you don't have any experience with SQL and if you have some experience.

If you have your experience with SQL, I would recommend starting with datacamp's class on intro to SQL.

This is free and you get to learn the basic SQL logics and command lines@.

I also love how it's super interactive so everything feels very real when you're coding on it.

If you have some experience with SQL or if you're preparing for a SQL text@ screen, I highly highly recommend going to leetcode or Interview Query.

On these websites, you will see all the SQL teg questions from companies like Facebook, Google that were actually asked during the interviews.

And even if you're not interviewing, I find this extremely useful just to see how SQL is used to solve real business problems at specific companies.

I would definitely be sure to ace the easy question and get comfortable with medium questions.

So aside from SQL, data wrangling skills in Excel and Google Sheets is another essential.

Once you pull thousands of rows of raw data at your SQL, the next step is to load the data into Excel or Google Sheets to then organize your raw data and visualize graphs there.

In the typical BA interview for tech companies, there's usually a take home case study where you're given a set of raw data in Excel and you have to analyze the data and extract insights.

And no, you don't have to know all these formulas out there!

In my day to day, I mainly use pivot tables, sumifs, vlookups, index/match.

and if anything it would just be more (sumifs vlookup pivot table index/match) advanced variations of them.

I think what's more important here is knowing how to solve the problem.

As an example, I didn't know sumif existed. (sumif??) All I knew was I wanted to sum all the rows based on a criteria.

I Googled exactly that and I realized sumif can help me do that.

So Google is going to be your best friend when it comes to data wrangling.

How do you learn data wrangling skills?

My biggest tip to learn it is to play around with the data yourself and practice.

If you're in an internship and even if it's not related to data, let your manager know that you like to gain data skills and would love to see if you can work on related projects or even if there's anyone you can speak to.

When I was doing my digital marketing internship at Roc Nation, my internship had almost nothing to do with data analysis.

But because I asked, I was able to get time with analysts and see how they do their analysis in Excel and how they wrangle their data and visualize things.

If you're working full time, the next time you get any data point, ask to see what the raw data looks like in Excel or Google sheet form.

And try to see how people wrangle and structure their data.

What I used to do was making a copy of the sheet and try to do it myself.

And last tip is practice.

The more you do it, the more you will see the pattern building your own systemic way of visualizing things.

Skill no. 2, problem solving skills.

This is about how you can break down ambiguous questions into smaller pieces in a structured way.

So as a business analyst, you often be asked very ambiguous questions in your job or even in your interview during the case study round.

A classic question is a root cause analysis which I get asked all the time at work too.

So get ready for this question.

Imagine you work at Netflix We're seeing monthly active users declining on the Netflix app.

Can you root cause the issue?

What recommendations do you have?

To approach any ambiguous problem, there's a general structure to problem solving that I learned from my mentors.

Break down the problem into smaller questions or pieces, then use data to answer your questions.

After that, you can consolidate your learnings into insights, and based on your insights you provide your business recommendations.

So the first question I'll think about is impact size.

How long have we been seeing this MAU decline, and what is the size of this user decline?

Also look at geography.

Are we seeing this on a global level or in a specific market?

And seasonality too.

Did we see MAU decline last year around the same time too or did it only happen this year?

Maybe it's a recurring pattern and related to seasonality?

And these are some other questions I would look into I then dive into the data to find insights for each of these questions.

The biggest mistake and that's what I used to do when I started was to dive straight into the data and I would drown myself in there for hours and not have a narrative and answer.

Let's say after you analyze data, and you may be analyzing 10 to 15 metric.

But when you communicate the insights in your email to your manager, or in your executive summary in your presentation, communicate them in a top-down way.

So I will say it like this.

Top-down communication is when you start with your key message and then go into your supporting details.

There's also a video about top-down communication like this one, and I highly recommend you to check it out.

How do you learn problem solving skills?

First tip is to watch mock case interviews.

I'll link some good ones down in the description box.

I also love seeing product managers do their mock interviews.

Especially these two on the Exponent channel since it's more tech driven.

In terms of what jobs or internship experiences that are more relevant, consulting is a big one.

And the secret is that's where most tech companies recruit their BA's from.

Internship wise, I highly recommend insights internship, analytics, or market research internships.

Basically internships that have something along the lines of using data to drive actionable insights.

Can be quantitative data or qualitative data doesn't matter.

What you're trying to learn here is to turn data into insights and tell a story.

And regardless of whether you're in school or in a full time job, the next time when someone presents, pay attention to the structure of their presentation.

See how they go from point A to point B to point C.

Think about what they did well and what you would improve on if you were the one presenting.

Skill no. 3, strategic thinking and business sense.

What sets great analysts apart from average analysts?

Is their ability to turn data into actionable insights to guide the business recommendation.

Basically, how would this specific piece of data be actionable for the business?

It's not about how many coding languages you know, it's about what the business could do based on the data you provide that matters most.

So, using our example again on...

We're seeing monthly active users declining on the Netflix app.

Can you recall the issue?

What recommendations do you have?

100

Previously, we align on a few questions I will answer with data.

101

But before we go analyze the data, I learned that a way to sharpen my strategic thinking is to pause and think first about the So What?

102

of getting each data points or insights are actionable.

103

Role playing helps, so imagine let's say we are the CEO of the company, how can this data help us make a decision?

104

For impacts sizing the So What? is that if it's alarge amount of users declining then we should be alarmed and come up with large scale counter-actions.

105

Also, looking at the MAU trend, if it's a spiked drop, it likely will be a one time event, perhaps a bug; if it's a gradual trend, perhaps we aren't finding values using our services; if it's a step change, perhaps we made some changes on our product and it's hurting our growth.

106

So seasonality, So What?

107

if it's a recurring trend that happens every year, there's not much we can do but will closely monitor.

108

Geography, So What?

109

if we see it on a global level, then it may be a bug in our data that's driving down the numbers everywhere.

110

And you'll be surprised that these things actually happen.

111

If it's a specific market, then perhaps our competitor launched a new feature that's taking away our users or there's a macro level trend happened in the market that we should be aware of.

112

External factors such as competition.

113

The So What? here is we should understand what it is and if it would make sense for us to build something similar or have some counter-actions.

114

Demographic, specifically aged group.

115

The So What? here is if it's happening a specific aged group, perhaps we are underserving this cohort of users and we can think of strategies to make our product and experiences more appealing to this aged group.

116

Breaking down the MAU metric, So What?

117

If it's less new users coming in, we need to think about our acquisition strategy; if it's more users turning out, we need to think about engagement strategy to retain users.

118

What's really good about doing the So What? exercise is it forces you to think strategically before you even pull the number.

119

So our insights on Netflix MAU decline was around competition and higher churn rates among 25 to 34 y/o in the US.

120

Based on the insights, what are some business recommendations you can provide?

121

Looking back at our So Whats?, you can then build upon them.

122

First, I will think about understanding the competition.

123

We can conduct user research to understand the new feature that the competitor has launched and how we can come up with appropriate counter-actions.

124

Second, double down on engagement strategies to reduce the churn among 25 to 34 y/o in the US 1. we can understand the types of content or feature that this cohort tend to consume the most and increase awareness of them.

125

For instance, we can service as a specific content on homepage, talk about the feature via email communications or do a PR announcement of a specific show.

126

Second, we can perform a cohort analysis to identify the key behaviors that make a user highly engaged.

127

For instance, is it about using a specific feature or the number of content watch or the diversity of genre they see that make them a highly engaged users?

128

Based on such, we can then take steps to encourage unengaged users to follow the behavior of engaged users to prevent churn.

129

How do you learn strategic thinking and business sense?

130

First, before you analyze any data point, pause for a second and think about the So What? of knowing the data point.

131

Why does the CEO need to know this data and what can the CEO do about it?

132

So your insights are strategic versus just plain numbers.

133

For a business sense, this is probably the harder one for me to learn, but a good tip is to have regular conversations with people outside your team, to learn how things work at your company.

134

For instance, ask the user research team, if you want to start a user research, what do you need and what is intell?

135

Ask the marketing team what tactics have been done for the engagement strategy and what worked well?

136

Talk to the product team and see how they evaluate the strength of a new feature?

137

As you become more senior in your role, you will then be the one implementing these recommendations end to end with cross functional stakeholders.

138

So it's better to know how things work from their end.

139

Hopefully this was helpful in shedding some light on the course skills of a business analysit's in tech.

140

And again, thank you glassesusa.com for sponsoring today's video.

141

You can shop my glasses in the link in the description box.

142

Thank you all for watching and I'll see you in my next video.

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Vocabulary and speaking notes for this lesson

This B2 speaking lesson is built on the video “think like a business analyst in tech”. The speaker keeps coming back to these words: user, Sql, skill, insights, learn. This video has 142 sentences and 2611 words to shadow. The speech runs for 12:12. The speaker talks fast, about 214 words per minute, so expect linked and reduced sounds. 83% of the words are among the 3,000 most common in English; the rest is worth studying before you start. 32 of its 142 sentences are questions, so it is good practice for question intonation and short answers.

Key vocabulary in this video

The 15 most advanced words in the video, with pronunciation and meaning:

Word	Pronunciation	Meaning
insight noun	/ˈɪnsaɪ̯t/	A sight or view of the interior of anything; a deep inspection or view; introspection; frequently used with into.
internship noun	/ˈɪntɜːnʃɪp/	A job taken by a student in order to learn a profession or trade.
analyst noun	/ˈænəlɪst/	Someone who analyzes.
recommendation noun	/ˌɹɛkəmɛnˈdeɪʃən/	An act of recommending.
wrangle verb	/ˈɹæŋɡəl/	To convince or influence (someone) by arguing or contending.
analyze verb	/ˈæn.əˌlaɪz/	To subject to analysis.
actionable adjective	/ˈæk.ʃə.nə.bəl/	Able to be acted on; able to be used as the basis for taking action.
churn verb	/t͡ʃɝn/	To agitate rapidly and repetitively, or to stir with a rowing or rocking motion; generally applies to liquids, notably cream.
cohort noun	/ˈkoʊ̯ˌhɔɹt/	A group of people supporting the same thing or person.
seasonality noun		Variation with the seasons
visualize verb	/ˈvɪʒuəˌlaɪz/	To perceive (something) visually; to see.
ambiguous adjective	/æmˈbɪɡ.ju.əs/	Open to multiple interpretations.
lens noun	/lɛnz/	An object, usually made of glass, that focuses or defocuses the light that passes through it.
pivot noun	/ˈpɪv.ɪt/	A thing on which something turns; specifically a metal pointed pin or short shaft in machinery, such as the end of an axle or spindle.
recur verb	/ɹɪˈkɜː/	Of an event, situation, etc.: to appear or happen again, especially repeatedly.

Phrasal verbs you will hear

Word	Pronunciation	Meaning
break down verb		To stop functioning.
come up with verb		To manage to produce, deliver, or present (something) by inventing, creating, thinking of, or obtaining it.
check out verb		To record the departure or withdrawal of someone or something (such as guests, employees, books, etc.).
cut out verb		To refrain from (doing something, using something etc.), to stop or cease (doing something).
drive down verb		To cause or force a price, quantity, rate, etc. to decrease.
take away verb	/ˌteɪk əˈweɪ/	To remove something and put it in a different place.
turn out verb		To end up; to result.
wake up verb	/ˌweɪk ˈʌp/	To stop sleeping; to awake.

Sentences worth repeating

Short, complete lines from the video that you can reuse in everyday conversation:

How do you learn data wrangling skills?
Can you root cause the issue?
What recommendations do you have?
How do you learn problem solving skills?
Can you recall the issue?

Grammar in this video

The structures the speaker uses most, with the exact words from the video:

Structure	In the video
Conditional sentences if + clause, will/would + verb — a condition and its result	if anything it would just
“Used to” used to + verb — a past habit or state that is no longer true	used to do
Passive voice be + past participle — the focus is on what happens, not who does it	would be asked · were actually asked · be asked
Present perfect have/has + past participle — a past action that still matters now	I've worn · have finished · has launched

Pronunciation to watch

The speaker uses 30 contractions and reduced forms, such as you're, I'll, I'm. Say them the short way, as you hear them.

The “sh” and “zh” sounds: internship /ˈɪntɜːnʃɪp/, recommendation /ˌɹɛkəmɛnˈdeɪʃən/, actionable /ˈæk.ʃə.nə.bəl/, visualize /ˈvɪʒuəˌlaɪz/, prescription /pɹəˈskɹɪp.ʃən/
Long words — get the stress right: recommendation /ˌɹɛkəmɛnˈdeɪʃən/, actionable /ˈæk.ʃə.nə.bəl/, ambiguous /æmˈbɪɡ.ju.əs/, analytics /ˌæn.əˈlɪt.ɪks/, competitor /kəmˈpɛt.ɪ.tɚ/

How to practise with this video

Listen to the whole video once without speaking and note the words you do not know.
Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
Record yourself and compare with the original, paying attention to words like insight, internship, analyst.

What is the Shadowing Technique?

Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.

Shadowing technique: read the full step-by-step guide →

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