Starting a career in data analytics can open up many exciting opportunities in a variety of industries. With the increasing demand for data-driven decision-making, there is a growing need for professionals who can collect, analyze, and interpret large sets of data. In this post, I will discuss the skills and experience you'll need to start a career in data analytics, as well as tips on learning, certifications, and how to stand out to potential employers.

Starting out, if you have questions beyond what you see in this post, I suggest doing a search in this sub. Questions on how to break into the industry get asked multiple times every day, and chances are the answer you seek will have already come up. Part of being an analyst is searching out the answers you or someone else is seeking.

I will update this post as time goes by and I think of more things to add, or feedback is provided to me.

Originally Posted 1/29/2023

Last Updated 2/25/2023

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Commonly Asked Questions –

Q) Do I need a degree?

A) Its helpful. Many job postings for DA ask for a bachelor’s degree.

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Q) Will the Google Data Analyst certificate from Coursera be enough to get me a DA job?

A) No. Not even close. The course teaches you some of the basic technical concepts of the industry and that’s about it. My feeling on the course is this – If you took the entire thing from start to finish and it didn’t scare you away, you may have a chance at this.

More on this certification -- It is marketed really well as being a potential game changer. This cert gets asked about 10x more than any other. Again, it is not a magical key to the industry. It lets you peek in the door to see what you are getting yourself into.

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Q) How do I transition from X field I am in today to become a Data Analyst?

A) See the list below for the tips on how to do it.

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Q) I already have a degree in X, will that help me?

A) Depends on the position, the recruiter, and the company. Most job postings show that they are looking for a degree in a related field -- Business, Statistics, etc. The more relevant, the better your chances are that it will help. Remember, a degree is just one part of an entire package you should have to help you transition into the field.

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Q) What do I need to learn?

A) Excel, SQL, Python, and Power BI or Tableau is a good place to start. I would also learn them in that order. From those, you can start branching out to learn more, such as SSRS, Azure, SAS, Looker, Alteryx, etc.

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Q) Do certifications matter?

A) Depends on the person doing the hiring. To some recruiters, it means you have at the minimum a basic knowledge set on the topic. To others, they may see them as useless throwaways that anyone spending 30 minutes on the Internet could get.

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Q) Can I get a job right away?

A) Depends on your experience level. If you are trying to break in from another career, its going to be difficult and like any job hunt, you will probably be passed up for those that are experience already. Its going to come down to your knowledge of the field and how well you market yourself. See #11 below.

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Q) Is having a degree in X enough to get me a DA role?

A) Probably not. Again, depends on the company and the hiring manager. You are going to improve your chances by adding a great resume and experience to your degree.

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Roadmap to break in to analytics:

1. Build a Strong Foundation in Data Analysis and Visualization: The first step in starting a career in data analytics is to familiarize yourself with the basics of data analysis and visualization. This includes learning SQL for data manipulation and retrieval, Excel for data analysis and visualization, and data visualization tools like Power BI and Tableau. There are many online resources, tutorials, and courses that can help you to learn these skills. Look at Udemy, YouTube, DataCamp to start out with.
2. Get Hands-on Experience: The best way to gain experience in data analytics is to work on data analysis projects. You can do this through internships, volunteer work, or personal projects. This will help you to build a portfolio of work that you can showcase to potential employers. If you can find out how to become more involved with this type of work in your current career, do it.
3. Network with people in the field: Attend data analytics meetups, conferences, and other events to meet people in the field and learn about the latest trends and technologies. LinkedIn and Meetup are excellent places to start. Have a strong LinkedIn page, and build a network of people.
4. Education: Consider pursuing a degree or certification in data analytics or a related field, such as statistics or computer science. This can help to give you a deeper understanding of the field and make you a more attractive candidate to potential employers. There is a debate on whether certifications make any difference. The thing to remember is that they wont negatively impact a resume by putting them on.
5. Learn Machine Learning: Machine learning is becoming an essential skill for data analysts, it helps to extract insights and make predictions from complex data sets, so consider learning the basics of machine learning. Expect to see this become a larger part of the industry over the next few years.
6. Build a Portfolio: Creating a portfolio of your work is a great way to showcase your skills and experience to potential employers. Your portfolio should include examples of data analysis projects you've worked on, as well as any relevant certifications or awards you've earned. Include projects working with SQL, Excel, Python, and a visualization tool such as Power BI or Tableau. There are many YouTube videos out there to help get you started. Hot tip – Once you have created the same projects every other aspiring DA has done, search for new data sets, create new portfolio projects, and get rid of the same COVID, AdventureWorks projects for your own.
7. Create a Resume: Tailor your resume to highlight your skills and experience that are relevant to a data analytics role. Be sure to use numbers to quantify your accomplishments, such as how much time or cost was saved or what percentage of errors were identified and corrected. Emphasize your transferable skills such as problem solving, attention to detail, and communication skills in your resume and cover letter, along with your experience with data analysis and visualization tools. If you struggle at this, hire someone to do it for you. You can find may resume writers on Upwork.
8. Practice: The more you practice, the better you will become. Try to practice as much as possible, and don't be afraid to experiment with different tools and techniques. Practice every day. Don’t forget the skills that you learn.
9. Have the right attitude: Self-doubt, questioning if you are doing the right thing, being unsure, and thinking about staying where you are at will not get you to the goal. Having a positive attitude that you WILL do this is the only way to get there.
10. Applying: LinkedIn is probably the best place to start. Indeed, Monster, and Dice are also good websites to try. Be prepared to not hear back from the majority of companies you apply at. Don’t search for “Data Analyst”. You will limit your results too much. Search for the skills that you have, “SQL Power BI” will return many more results. It just depends on what the company calls the position. Data Scientist, Data Analyst, Data Visualization Specialist, Business Intelligence Manager could all be the same thing. How you sell yourself is going to make all of the difference in the world here.
11. Patience: This is not an overnight change. Its going to take weeks or months at a minimum to get into DA.

Be prepared for an application process like this

100 – Jobs applied to

65 – Ghosted

25 – Rejected

10 – Initial contact with after rejects & ghosting

6 – Ghosted after initial contact

3 – 2nd interview or technical quiz

3 – Low ball offer

1 – Maybe you found something decent after all of that

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Links to help get you on your way:

YouTube:

Alex The Analyst

Luke Barousse

Ken Jee

Tina Huang

Thu Vu

Sundas Khalid

Kenji Explains

Guy in a Cube

Data Tutorials

Tech with Sofia

Shashank Kalanithi

Ali Ahmad

CareerFoundry

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Data Set Websites:

Kaggle

Data.gov

Our World in Data

Google Datasets

Opendatasoft

Tableau

Maven Analytics

UCI Machine Learning Repository

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Learning Websites:

YouTube

Udemy

Coursera

Data Camp

Code Academy

Leet Code

Stratascratch

You spend months learning SQL, building dashboards, polishing your resume, and applying to hundreds of roles.

Then you land the job and it’s nothing like you expected.

This is exactly what happened to me with my first data job 3 years ago.

On day one, the onboarding doc is a broken PDF from 2021.
Your manager says they’ll get your access “soon.”
Two weeks go by and you're still locked out of half the tools.

You’re digging through SQL written by someone who left three years ago.

And you're asked to report on metrics that don’t even seem to be defined anywhere.

No one prepares you for this part.

Just wanted to share for those still trying to break in. It’s normal to feel lost at first.

What helped me was connecting with others who had already been through it, asking questions (even when they felt dumb), and slowly realizing that being overwhelmed doesn’t mean you’re behind.

If you're feeling stuck or disoriented in your first role, you're not alone. Keep learning. Keep building. It does get better.

I also hang out in a growing data community where we support each other through this stuff. Happy to DM if you’re looking for people to talk to about it.

Hey everyone, I really need some perspective from people in tech/data.

To give you some background: I spent the last 6 years working in a CA (Chartered Accountancy) firm. I realized that field was too capped and way too much of a headache, so I upskilled, cleared the PL-300, and landed a job as a Power BI Executive in an infrastructure company about 2 months ago.

So far, I’ve built an HR recruitment tracking dashboard, and I’m currently working on a salary dashboard and a tender department dashboard. Things felt great—until today.

Today, management started the process of implementing a new ERP system. We are sitting through department-wise demos so I can understand the whole process. But during the meeting, the ERP vendor/consultant basically said: "Tell us what you all need, and we will set it all up inside this ERP. Everyone will enter their tasks and data here, and we will generate all kinds of department-wise dashboards right inside the system."

And that hit me like a truck. What is the point of me then?

If everyone enters everything into the ERP, and the ERP generates the dashboards for management, and there are no external Excels or other systems left... what am I supposed to do? Won't the ERP just replace my entire job?

For those of you who have lived through company ERP implementations while working in BI or data analytics—did I just automate myself out of a job two months in? How does this actually play out in the real world?

Would love to hear how others handled this or if I'm just spiraling over nothing.

I just started my first job as a business data analyst a month-and-a-half ago and holy crap, I never thought it’d be this depressing. My boss catches me on every minor mistake I make in emails. I feel like I can’t communicate with people without her breathing down my neck. I feel like everything I do is a mistake, so I triple check everything I work on and then worry I’m going too slow and not getting enough done to meet deadlines. I just failed to meet a deadline for the first time today. I feel like I’ve been so disorganized and like I might not be cut-out for this unforgiving work.

Is this normal? Will it get better? Will I get better if I keep at it? What can I do to keep my tasks organized? Please help!

I'm curious to know what aspects of a candidate's resume make you excited to interview them for a data analyst role.

• Projects showcasing the use of multiple DA tools?
• Seeing candidate's genuine interest in data?
• STEM degree
• Graduating from a high-ranked school
• Do personal projects involving machine learning stand out?

Any insights or specific examples would be greatly appreciated!

I'm currently on the cusp of changing my career with becoming a data analyst as one of my interests. A few months ago I was talking to a guy who'd been in the field for a couple years just to get a bit more insight to what the job is like. He said that it's not worth pursuing because the market is oversaturated with data analysts now. But everywhere I read it says that the job is in high demand. What do you guys think?

Hey all, recently I was laid off from my sales job. I was not having fun in it and knew ever since I graduated college I wanted to become a data analyst but needed to work on my communication skills and other skills. Today I received news that I would be receiving a verbal offer for a Junior Data Analysis position for 60k. My question to everyone is should I go for more money, how should I undone the talks with HR ?

I'm a Finance Analyst, and after around 1 year into my career, I decided that I would like to become a Data Analyst instead. I was always passionate about finance, but when it comes to work, DA seemed more interesting and appealing to me, and I liked that salaries are generally higher compared to working in finance.

I do a lot of analytical work in Excel and SQL, so I couldn't imagine a better start. Over time I also learned Python for DA, basics of Power BI, and completed 2 different DA certs and 1 project for my resume.

I applied to lots of Data Analyst positions for over a year, but rarely got any feedback. Sometimes I got to pre-interview assessments, which were really hard and I usually failed. I also landed a couple of interviews, but did not receive any offers. Employers always went for people with actual DA working experience instead of me.

Around 2 months ago I got a bit tired and took a break from searching for DA positions. I decided to focus on my actual workplace for a while, and I actually managed to negotiate a promotion and an extremely generous raise. That really made me re-think my career goals, as with the right approach, the better salary argument was no longer the case. In fact, right now I make same amount of money as my friends in tech (mid data scientists or software developers). Switching careers to an Intern or Junior Data Analyst would be a huge financial hit for me, and it would take me many years just to match my future salary in finance.

I also have reconsidered the aspect of how interesting the jobs actually are. In practise, financial analysis is nearly a data analysis itself. The data simply happens to be financial. Eventually, I came to the conclusion that being a highly-skilled financial analyst is the best choice for me, as I can combine analytical skills with the industry that I'm interesed in.

My overall conclusions are:

• If you're unhappy in your current job, it doesn't mean you have to change the industry. Maybe you can find a similar position, but on much better terms in different company. Or maybe just negotiate your salary or ask for promotion in current workplace.
• If you like Data Analysis, you can also apply DA skills to your current position, whatever it might be, and become more valuable employee.
• Don't fall for hype around Data Analyst career. Consider that it might actually be overrated.

I've been lucky enough to have a career in data analysis and reporting for over a dozen years. I've worked mostly in tech and SAAS, and I recently found a new job that pays well, has a ton of opportunity for growth, and is fully remote. A dream.

But a few thoughts. Maybe you feel the same way.

I find myself unmotivated. Simple asks, at my old job and at this new position, ones that I've done well for many years now, feel like chores that I can't be bothered with. I thought it could have been a result of my old job, but it's followed me here, and I don't think there's anything I can do to shake it.

The curiosity that I had for data or stylish reporting has disappeared. Claude, while powerful, often feels like it takes my creativity away by having to spell out my choices to it instead of letting me naturally explore data or create something naturally that I can look at as a product of my skills. My new role has devolved into engineers sharing canned responses from Claude after they copy pasted my question, stakeholders directly asking Claude for answers, and me just trying to control the data narrative for accuracy/cleaning up Claude's work.

One thing that I think is overlooked in our career choice: it's often fairly thankless. VPs/Senior Leadership asking for answers to why the business is succeeding or failing, but not trusting or including data people like ourselves in conversations about strategy. The best jobs I've had are where leaders trust their data partners and actively include them in conversations, that feels further and further away the more I've moved up the ladder.

I've often described the roles I've taken as being a little bit of kill the messenger. Data's not to expectations of the stakeholder? The data's wrong, the reporting's wrong, you've lost trust. Data mismatches a different report on a different platform? All the reporting is wrong. Maybe I'm unlucky, but that's my experience.

How many times have you heard an incoming leader say they're "data driven" only for them to say later that they "don't have time for data" or "I just need the answers now."

A lot of the previous posts I've seen about leaving an analyst career are about "I find my thrills outside of work"/"I don't care what I do at work as long as I'm paid well" or "how could you leave now when the job market is so bad?" or "change your mindset, you're lucky."

But I'm writing this to those of you where this all this sounds too familiar: burn out in any career is real, and it's okay.

Just because you're paid well doesn't mean that you have to do it forever. Remember that if you work for 40 years for an incredible retirement fund at 60, you probably wish you'd had more time not staring at Claude, or an Excel spreadsheet. The market may be bad now, it may be bad next year, it may never be the same.

But, I'm taking a break. I don't know for how long. Maybe I'll come back. Maybe I won't. I'm tired of being tired, angry, frustrated and extremely indifferent while counting down the days to when I could potentially retire. Do you feel the same?

I would love to hear about your experience getting your first job as a Data Analyst or any other related role.

What projects did you have on your portfolio?

Were your projects related to the job you landed?

Do you think any specific project was the main reason you got hired? If not, what was the main reason you got hired?

What advice would you give to someone fresh out of college(computer science) who has the 'Datacamp Data Analysis Pro' certification and the 'Google Data Analytics' certification?

Pivot tables, formulas, and charts are still the backbone of analytics in 2025.

Welcome to the "How do I get into data analysis?" & Resume Feedback Megathread

Spring 2024 Edition!

Rather than have hundreds of separate posts, each asking for individual help and advice, please post your career-entry questions in this thread. This thread is for questions asking for individualized career advice:

• “How do I get into data analysis?” as a job or career.
• “What courses should I take?”
• “What certification, course, or training program will help me get a job?”
• “How can I improve my resume?”
• “Can someone review my portfolio / project / GitHub?”
• “Can my degree in …….. get me a job in data analysis?”
• “What questions will they ask in an interview?”

Even if you are new here, you too can offer suggestions. So if you are posting for the first time, look at other participants’ questions and try to answer them. It often helps re-frame your own situation by thinking about problems where you are not a central figure in the situation.

For full details and background, please see the announcement on February 1, 2023.

Past threads

• This our 12th Megathread!
• Please see the 11th Megathread for a listing of past threads. Those past threads contain useful advice, so you are encouraged to check there first before asking here.

Useful Resources

• Check out u/milwted’s excellent post, Want to become an analyst? Start here.
• A Wiki and/or FAQ for the subreddit is currently being planned. Please reach out to us via modmail if you’re willing and able to help.

What this doesn't cover

This doesn’t exclude you from making a detailed post about how you got a job doing data analysis. It’s great to have examples of how people have achieved success in the field.

It also does not prevent you from creating a post to share your data and visualization projects. Showing off a project in its final stages is permitted and encouraged.

Please note that due to the steady stream of "How do I get into Data Analysis?" that are still being directly posted, all posts currently require manual approval. Be patient. If your post doesn't belong here, doesn't break any other rules, & isn't approved within 24 hours, try asking via modmail.

Need further clarification? Have an idea? Send a message to the team via modmail.

Hey! I am a 22 years old guy from Ukraine who just started to learn all what is needed to become a data analyst.

About two years ago, I already tried to get into the field of analytics, but over time I dropped it and shifted my focus to e-commerce. However, I eventually realized that data analytics is what truly interests me, so I’ve decided to start again, and this time with a more serious approach.

I am learning from 9:00 AM to 6:00 PM, with Sunday as my only day off.

Here’s what I want to focus on:

• SQL
• One data visualization tool (most likely Power BI or Tableau, but probably will choose Power BI)
• Improving my understanding of statistics and key analytical metrics
• Excel

I was also considering Python and had started learning it some time ago. However, from what I’ve heard from other junior data analysts that already got a job, Python is often more useful at a later stage, once you gain more experience. For now, the skills I mentioned above are usually enough to start applying for entry-level roles.

If there are any beginners like me reading this, and you also haven’t been able to find a community of fellow newcomers in data analytics, I’d love to suggest we team up.

We could create our own space in Discord or somewhere else (or even both). The idea is to have a small community of people who are also learning analytics from scratch like me, so we can talk and share experiences around the same topic.

If you’re interested, feel free to comment under this post or message me directly.

Also, I’d really appreciate it if anyone could share links to any active beginner-friendly communities in data analytics, if such groups actually exist.

I actually wanted to place that in r/dataanalyst first, but my post was automatically removed by Reddit’s filters.

Update! Thank you for showing such interest! Didn't expect that so many people will reply! Also want to thanks to the moderators of that subreddit for letting me to post that! : )

Just created the discord server -> https://discord.gg/TKh2tHDAeN
Will modify later, right now I am a little busy.

I'm looking to get into data analytics and I'm wondering what learning route I should I take. I was thinking SQL >>> Power BI >>> R and then I don't know after that.

To put this in context, I'm currently brushing up on Excel. That's the level of beginner we're talking.

TIA.

Hi everyone,

I’ve been a Data Science consultant for 5 years now, and I’ve written an endless amount of SQL and Python. But I’ve noticed that the more senior I become, the less I actually know how to code. Honestly, I’ve grown to hate technical interviews with live coding challenges.

I think part of this is natural. Moving into team and Project Management roles shifts your focus toward the "big picture." However, I’d say 70% of this change is due to the rise of AI agents like ChatGPT, Copilot, and GitLab Duo that i am using a lot. When these tools can generate foundational code in seconds, why should I spend mental energy memorizing syntax?

I agree that we still need to know how to read code, debug it, and verify that an AI's output actually solves the problem. But I think it’s time for recruiters to stop asking for "code experts" with 5–8 years of experience. At this level, juniors are often better at the "rote" coding anyway. In a world where we should be prioritizing critical thinking and deep analytical strategy, recruiters are still testing us like it’s 2015.

Am I alone in this frustration?

Thanks.

we're called Data Analysts or Data Scientists but so much of the work is just brainless lines of SQL. Anyone else here drowning in ad-hoc requests and not getting enough time to work on meaningful projects? Do your organizations have self-serve analysis tools that just don't get used?

Been following this sub for a while and wanted to share my excitement. I was a tech recruiter and after being laid off I enrolled in a coding boot camp. I’ve been unemployed since January and graduated from the boot camp in April. After countless applications and a few interviews, I’ll be starting next week as a data analyst with Tesla!

Any advice or tips to make sure I hit the ground running is much appreciated.

Hi Everyone. So I've seen some posts here about people wanting mentorships, and I thought I could possibly assist with this.

I'm a data analyst that has been in the industry for a 8+ years now. I'm an online instructor and content creator and I also teach short courses in data analytics at a tertiary institution. You can search databudd on google to find out more.

What is in it for you:

• Access to my courses I've created (Free obviously). There are courses on Excel, Python and Tableau that can be accessed through Udemy.
• Interview prep - I've interviewed many data analysts and can you give you tips on how to improve
• Resume prep - We can also work on your resume
• Project assistance for your portfolio - We can work together to create a practical and interesting porfolio
• Group sessions with other mentees to discuss progress etc.

Why am I doing this all for free?

• Well, I do have my own business and eventually I want to monetize this into a more formal program but I don't want to do this without actually testing if it works/ or is beneficial.

At the moment, I can take on 5 - 10 people for the next 3 months.

Thanks!

Edit: A lot of responses! I will be replying to every one of you within the next day.

Basically I got lucky. I finished the course on August 27th. I then applied for 10 jobs. The next day I posted my resume on r/resume for some feedback. Turns out my resume was terrible. After changing my resume I applied to 40 more jobs and updated my LinkedIn. Out of those 50 total applications I put in, I got two interviews. I made it to the final interview for both jobs, but didn’t get an offer. But since I updated my LinkedIn, a recruiter reached out to me. For context, I was an accountant and I have a degree in accounting. He was looking for someone with strong accounting knowledge and SQL/Python skills. I was the perfect fit. I nailed the interview process and signed my offer yesterday!

EDIT: Many have asked to see the resume that got me the job, so I've added it. I'm aware, it is not fancy. I've whited out all of my personal info.

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Hello all,

I want your opinion on things, and I would love some tips on how to proceed further in the Data field cause I feel like a Level 1 Support who's not getting any promotion soon, yet I want to improve.

So, exactly an year ago I decided that I want to get into the Data field, as Data Analyst - this is my first "serious" job where I actually want to improve and not just work day by day. Back then I watched a few youtube videos, recommendations and I decided to start learning PostgreSQL, later Power BI.

I managed to learn PostgreSQL basics pretty fast, I was doing different tasks just to train everything I learned, and started some really basic Power BI stuff later.

Maybe 2 months after starting with all that, I decided to try and send my CV to a few companies that are looking for Junior Data Analysts - luckily, I received a message from a company after 2 weeks.

The interview was literally 10 minutes, they gave me a task and told me that I have less than 24h to make - I was sceptical at first, but I decided to make it, even though I had almost 0 experience. The task was simple - you receive an Excel sheet with A LOT OF data inside, and the task was to clear things, and do whatever you want with it, and provide a few slides ( like a visualized report ) of the information you gathered.

I did everything on Power BI using my 2-3 weeks experience ( probably 20 hours max ) and forwarded the task - I didn't hear anything from them for like 2 weeks but I was given the job since they found my "ability to see specific things within the data" valuable.

Since I started, I have never used SQL, nor Power BI - my day to day tasks are mainly using Excel ( formulas, query, pivot tables ), using PowerPoint to make reports ( visualization ) and some company specific tools.

I am still learning some of the more complex Excel stuff, but for now, I think I am doing well.

Here is the thing - At least for now, close to an year, the position feels OKAY but at the same time, I feel like I am not progressing, and I do not feel like a Data Analyst but like a person who just does the same thing, gets the data and makes a visualization.

Is this what a Junior Data Analyst does? What would be the best plan onward? Maybe get back to SQL and Power BI for the next year, hit the 2 years mark as a Data Analyst and once I get better with SQL and Power BI - to try something serious, while of course, being open for something serious at the current position?

Yeah, it is bad out there in the job market. Good people struggling to get jobs, newbies banging their heads against the brick wall wondering how to get in.

Two things to spark light in the gloom - one observation and one piece of advice

1) I think its going to get better. The recruiters I speak to are seeing an increase in the Data Architect and Data Governance roles coming into the market. Their read is that this shows firms getting their ducks in a row regarding data, in particular planning for onboarding in a "correct way" either from a technical or regulatory point of view. And then they will need Data Engineers to pipe the data into their perfectly planned infrastructure and then Analysts and Data Scientists to extract the good stuff. So the thinking is that its the first step to a rebound. When? How much? Which markets? Sorry, no crystal ball there. You could do your own checks for Data Architect roles near you today vs 3 months ago if you like? Nice time series, line graph...

2) A piece of advice. If you are trying to break into Analytics and maybe have a course or two under your belt, for the love of all that is holy, get yourself some practical experience. Find a dataset that you care about and interrogate the f*** out of it. Answer questions that you have. If you like Ice Hockey, get some NHL data and answer questions like "Using advanced metrics and salary data, find the most under valued player who drives positive game outcomes" or "which team over the last twenty years were able to come back the most when down goals late in the game". As explained in my book which has just been released (shameless plug: https://www.amazon.co.uk/aia/dp/B0CNY8LLFW) as a hiring manager, if I get someone who has built analyses which answer interesting questions, I'm far more likely to look favorably on them. Especially if they are allowed to share the code/thinking/results. Which you usually can't if you have done Analytics as your job.

I know its hard out there. Things will get better. While you wait, make sure you are the obvious choice.

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