I got first interview for business analytics 2-3 years experience position after long time and the first interview was just phone call with recruiter basic questions. And now she said they will take technical/ functional + sql zoom interview with hiring manager which is 30mins+ sql 15 mins. I never had technical interview before and would really need some guidance on what kind of questions I should be ready to answer. As per I know technical / functional part might be talking about current role, situation abased and project related questions. And behavioral ? But SQL not sure, if 2 years of experience means advanced or intermediate level. Should I look into leetcode type questions? In the job description they really required 2 years of sql, excel, tableau. Any help would be appreciated. Since I got first technical interview after months of application, I really want to cover all the bases.

hi everyone so I'm currently studying Business Economics. I’m really interested in becoming a business analyst, and if possible, I’d be so grateful to hear perspective on the roadmap for this career form you guys. Any advice, tips, or resources would really mean a lot to me, especially since I’m struggling to find genuine people to connect with in this field.

Thank you so much for your time!

I've seen a job listed with this title recently. Whats to be expected of a job like this? Did they purposely list it as.. “Non-It Project Analyst” so potential candidates can't look it up on salary.com?

For some reason I get the feeling its supposed to be called “operations analyst.”

Is this a good entry level job?

Embarking on a journey to master data analytics has been both challenging and rewarding. I’ve been diving deep into tools like Excel, SQL, and Power BI, primarily using resources from Maven Analytics. While these non-official sources have been incredibly helpful, I’ve also been mindful of the ethical considerations around using pirated content.

To ensure I retain and apply what I’ve learned, I’ve been working on various projects. Here are a few steps I’ve taken to keep my skills sharp:

1. Creating Real-World Projects: I’ve been applying my skills to real-world scenarios, such as analyzing sales data, creating interactive dashboards, and performing complex SQL queries. This hands-on approach has been crucial in reinforcing my learning.
2. Building a Portfolio: Documenting my projects and showcasing them in a portfolio has helped me track my progress and demonstrate my capabilities to potential employers.
3. Practicing Regularly: Consistency is key. I set aside time each week to practice and explore new datasets, ensuring that my skills remain up-to-date.
4. Engaging with the Community: Joining online forums and participating in data challenges has provided me with valuable feedback and new perspectives.

When it comes to sharing my accomplishments on LinkedIn, I focus on the skills and knowledge I’ve gained rather than the source of the materials. Here’s how I do it:

1. Adding Courses to LinkedIn: After completing a course, I add it to my LinkedIn profile under the “Licenses & Certifications” section. This helps showcase my continuous learning journey.
2. Sharing Projects: I regularly post updates about my projects, including screenshots and brief descriptions of the insights I’ve uncovered. This not only highlights my skills but also engages my network.
3. Writing Articles: Occasionally, I write articles about my learning experiences and the projects I’ve worked on. This helps me articulate my knowledge and share it with a broader audience.

While using pirated sources is not ideal, my focus remains on ethical learning and continuous improvement. I aim to transition to official resources as soon as possible to support the creators who make these valuable tools available.

Please suggest any data sets and sources to practice the skills I get and how to post what I learned on LinkedIn.

Hi all! I’m exploring a career in AI/ML that emphasizes practicality and real-world applications over theoretical research. Here’s a bit about me:

•	Background: I hold a bachelor’s degree in biology and currently work as a Systems Configuration Analyst at a medical insurance company. I also have a solid foundation in SQL and am learning Python, with plans to explore Scikit-learn, PyTorch, and TensorFlow.
•	Interests: My goal is to work with and utilize machine learning models, rather than building them from scratch. I’m interested in roles that leverage these skills to make a positive social impact, particularly in fields like healthcare, environmental conservation, or tech for social good.

I’d appreciate any insights on the following questions:

1.	Which roles would best align with my focus on using machine learning models rather than building them? So far, I’m considering Applied Data Scientist and AI Solutions Engineer.
2.	What’s the difference between MLOps and Data Scientist roles? I’m curious about which role would fit someone who wants to use models rather than engineer them from scratch.
3.	How does an MLOps Specialist differ from a Machine Learning Engineer? I’ve read that ML Engineers often build models while MLOps focuses on deployment, so I’d love more context on which would be more practical.
4.	Should I pursue a master’s degree for these types of roles? I’d like to advance in these fields, but I’d rather avoid further schooling unless absolutely necessary. Is it feasible to move into Applied Data Science or AI Solutions Engineering without a master’s?

Any advice would be helpful! Thanks in advance.

Hello, everyone. I'm a beginner in Data Analytics looking for advices.

I'm a bachelor in a Business-related field (28 yo). In the first phase of my career I have been working on quality management, administration, human resourcers, trying to find what I like. 2 years ago I was hired by a small company and started as a "generalist". Slowly but surely I started to improve things with Excel & Power BI and now I'm in charge of the data analysis of the company (but still an assistant 🥲). Luckily I found that I like Data Analytics.

So after searching for info, I have some questions:

1. It seems that the best option for a Masters is Georgia Tech. How difficult is it? I plan to enroll in the Online MSc in Analytics for 2026 (focus all my 2025 in preparing and studying). As a citizen of a third world country, a master is kind of relevant and of course I will try to gain more work experience.

2. In case Georgia Tech doesn't work out, what other options do I have? I read about the online Data Analytics masters at WGU (western governors University) but it wasn't well-known? My budget is around 20k USD.

3. Right now I'm improving my Excel, DAX and Power BI with Maven Analytics. After that I plan to study SQL and then Python. What other things should I study? Whenever I can I practice at work using the SQL bolt page to get the basics of SQL.

4. Is it a good thing to have a GitHub repository? Tbh I don't understand how github works, but I think it's used to upload and show your projects? I mean, the code of your SQL, Python or other languages.

5. Certifications: Experience is always better, but, if the market asks for certs, what would be the best ones to have?

Any additional info you may have, feel free to share. Thanks a lot!

Hey everyone! I'm in a bit of a dilemma and would love to get some advice from you all. I've done 5 internships, all focused on analytics, and I’ve been grinding SQL and pretty much all the analytics interview questions (Leetcode Hard). However, I haven't put much time into Data Structures and Algorithms (DSA) on Leetcode.

Right now, I’m not specifically targeting any one role in data (whether it's Data Science, Data Analytics, or Data Engineering) but want to keep my options open in the analytics field in general. I see a lot of posts about how DSA is a must for tech jobs, but I’m not sure if it applies as much in analytics or if it’s a wise investment given my experience so far.

For those who've been in the analytics industry or gone through the process, what’s your take on the importance of DSA for analytics roles? Should I dedicate some time to it, or would I be better off focusing on honing new skills (Hadoop/Spark/Hive,..)? Any advice is appreciated! Thanks!

“Build out final one-slider view that showcases in a certain level of detail what the MVP dashboard layer could look like.”

Edit: I did ask for clarification from my manager. Inquiring here because I was so confused at the language of the ask and am wondering if I just don’t actually speak analytics.

i've been seeing a lot of posting for "Sales Data Analyst"

Yeah obviously you're analyzing company's sales but is that really it ? i wonder if someone can clarify what's the actually daily routine or challenges
also what's the career progress specifically through that role

Hello everyone and thank you for your time !

I am 27 years old, a political science student and a working professional as well in customer service sector.

I'm interested in data analytics as a way to gain some technical skills fast and also learn something useful that will help me grow both professionaly and academicaly.

I recently started a certificate in Data analytics which is more related to business intelligence field with a final capstone and covers excel,R,Power BI,SQL,KNIME.. The duration is 6 months but the issue is that i'm afraid i will burn out with all the things i do at the same time (also learning a new language).

The thing is, that my university offers some classes with SPSS for social science research. I personally consider take these classes but im not sure if it is worth to resign from the Data analytics certificate for that or learning both.

The other option is to start a new certificate based only on R (Data Science and Big Data with the R Language and RStudio) which will be shorter and also i will invest in this language in the long term.

What you really recommend?

Hi all! I graduated 2 months ago from grad school with a degree in BioInformatics. I have been trying to find a job in analytics but no luck so far but have interviewed in 2-3 places over the last 2 months.

Today I got an offer from a hospital that doesn’t pay well and the job is data entry. That’s obviously not what I wanna do but should I just take it to start my career? I am afraid I won’t have space and time to interview elsewhere as I will have to go 5 days a week in office, 8-5PM.

Any thoughts on this?

Our urge to predict the future is deeply psychological. Forecasts act as a crutch, easing our anxiety about the unknown.

Biases like overconfidence give us faith in our predictions, even when past patterns offer little insight into what’s ahead. Meanwhile, confirmation bias keeps us clinging to forecasts, interpreting data in ways that reinforce the story we want to believe. And because forecasting is so embedded in decision-making, leaders are often expected to present firm numbers.

Saying “We don’t really know what will happen” risks backlash or a loss of trust. This illusion of certainty may be comforting, but it comes at a cost.

EDIT:
Great points, here's a summary of responses:

• Forecasts, flawed as they may be, are essential
• They’re an organization’s best guess about how their world works...a way to test their understanding and map out what’s ahead
• Even imperfect forecasts provide a foundation for discussion, giving leaders something they can analyze, question, and refine over time
• They provide a coherent framework that businesses can adjust as new information and clarity emerges
• By putting predictions on paper, organizations gain structure and a common knowledge base to guide decisions about staffing, budgeting, and resources; without forecasts, planning would feel like guesswork
• There’s also a psychological bias at play: those who make predictions are often seen as more confident and knowledgeable, even when wrong, which reinforces a trust in the act of forecasting itself

Hi there!

I want to better understand how a user navigates through our website currently, effectively knowing where point A starts, what point B is, and what events are firing at each step.

I thought a sankey diagram would be a good solution to this, but I can’t figure out a way to also show what events are firing and what at what point during the user session.

I do have a visual mock up that probably better explains what I am after if anyone wants to see it, this subreddit won’t let me post here.

Any help is greatly appreciated :)

hi! please be nice as im looking for some support and answers 🥹 i have a brief background in data engineering. i did it for a year as a junior data engineer but it didnt last and i was given other work which didnt align with my main skills (which were built from data engineering).

i have a background in computer science and i really love working with data. ive read a few posts here about peoples experience in doing data analytics and their transitioning stories so im seeking advice on how to move forward.

i dont wanna let go of my technical background just yet and at least be solid at it. i think data engineering doesnt seem to care so much about what the data means (at least based on my experience in doing it) and focuses more on getting the data through to the other side and making it clean. like i said, it was just for a year but i wish i was given more exposure to it for me to understand better.

my current plan is to learn how to do dashboards in power bi and get certified in it just for the sake of learning. i know its saturated but theres no harm in getting the certificate and my current company sponsors it so i might as well just do it. i wanna do data science as well but i have 0 experience in AI so i think taking up some brief courses in data science might help and wont exactly make me forget my coding skills but what is best exactly?

i really wanna be able to give meaning to data and i like cracking my head at understanding why the data is this way; how do i make it better and easier to understand; and what is it telling me and i wanna be able to uncover insights with the data ive cleansed and made reports out of and then make decisions with it. sorry for sounding naive but i am new and im willing to learn.

im not a pro at excel yet but i think there are a lot of tutorials out there to help me be good at the data side of it excel.

i wanna be able to derive decisions out of my data. im planning to get in the business side of it in the long run so im thinking of pursuing masters in business analytics but like i said i’m not sure where to begin.

whats within my control at the moment and what im planning to do is:

• get certified in power bi
• be good at sql (i like sql)
• be good at excel
• pursue masters in business analytics?
• take some datasets online from kaggle and make simple dashboards in power bi
• do some learning in data science
• learn python and do some simple data science projects with it

im aware its a mess but if anyone could give me some solid advice, itd be really helpful.

thank you

I’m a DA trying to break into DS. Have about 3 yoe in analytics altogether. Learning ML and NLP Where can I start with for doing DS related projects? How do I make my resume stronger apart from my day to day? Any suggestions are appreciated.

What is the worst part about doing data analysis?

I've worked a bit on building dashboards and creating ad hoc analysis for decision takers. For me, getting my hands and consolidating data has been the hardest part. Analysis on analysis with varied usage and often it ends up in the analysis graveyard faster than it took to create it.

Let’s just say I have CSM, PL-300 and ECBA. Would I be competitive in this job market? And how oversaturated is business analyst work?

We are currently in the process of transitioning from ThoughtSpot to Tableau, and I have around 1000 answers in ThoughtSpot that need to be converted into Tableau’s TWB format.

Has anyone gone through a similar transition? Are there any tools, scripts, or best practices to automate this process? Manually recreating all of these reports in Tableau would be a huge task, so any advice on making this smoother would be highly appreciated.

Thanks in advance!

I am halfway through my bachelor's and I have been seriously questioning my choice of getting this degree. I originally got it to break into tech, to get the remote position possibilities, and to hopefully get the higher pay that IT people are able to get. The job itself sounds pretty good for me when i hear people that have actually managed to get one. But reading about the current tech job market, im questioning whether to drop out or not, specifically to change majors when i figure out what that would be. i originally wanted to do something creative or psychology or marketing. im not passionate about tech itself, but the benefits and opportunities that can be found drew me to it. i just dont know if those benefits will be obtainable.

is the degree worth it? what would you do if you were me?

Hi 👋 I'm currently researching if there's interest in a tool where you can query your database using natural language.

The flow would be

• Pick your database connection
• Write something like "How many users bought X yesterday"
• You would get the number of users

You can also get reports in form of graphs and plots.

I view the target demographic as users with little knowledge of the schema and SQL I.e. the well known ad hoc analysis. But I might be wrong.

Any feedback would be highly appreciated 🙏

I've been given the opportunity to define a new title for myself as I transition from another department in my company. The two titles that have been presented to me are Data Scientist and Senior Data Manager. Currently my role involves a lot of data automation utilizing an in house developed system, communicating between departments to ensure process alignment, mapping out where data should be populated from in the documents.

Which job title matches my current role and which has better future job prospects and salary growth?

Hello all!

I need the help of the masses on this one. I am charged with conducting a questionnaire, a long, multiple choice one, for large numbers of subjects.

Now, in addition to the data we get from the answers, I'd want to know how they answered. Hold long it took per question, how many times and in which questions they switched answers, how many times they went back to previous questions, heatmaps and click tracking for the queation pages, etc.

Anyone knows which tools I could use for this purpose? Is therr any prebuilt tool like Qualtrics that could do the trick?

Part of the reason I like coding bootcamps is that they offer career services like resume make over and mentors, but I don’t want to pay the price of bootcamp, I just want the career services, any one know where I can get it from? I currently have two bachelors degree and a data science portfolio along with many professional certificates, I think what I need now is data science career services. Let me know what you think and where I can pay for some career services.

I also completed coursera certification, and im about to graduate with my bachelors. My wife is due with our second baby in February and we are stressed for me to find a job by then. Is this feasible? We also are willing to relocate anywhere as we are sure the remote jobs are too competitive at this time. Anyways, im just looking for some input. Also, when should I start applying?

I was looking at 100 days though there seems to be some barriers of outdated information. But if it's still good I am open to doing it and researching additional solutions. I have experience with c# only and game development engine specific languages. I'm looking into switching to analytics as a field. I'm not looking for only a certificate, but more for knowledge where I can build interesting projects myself to showcase. A certificate does help but I know it isn't taken as seriously. I prefer free or cheap (under $500). Currently I have experience in salesforce and if a future role uses it that's okay (as some do in analytics) but I don't like the admin role. I prefer to work with spreadsheets, formulas and code when necessary. I don't want to go the salesforce developer route because I am disliking the declarative code route and developers still often get saddled with alot of admin tasks. I posted this in another sub but I realized there maybe some analytics geared courses out there?

This doesn't really have any value, I just need a rant.

People love spreadsheets and seem to, for whatever reason, switch using quite a large range of date formats, which makes my job unbelievable difficult.

And I hate it. With a passion.

Edit: I actually love the job, just dicking around with human error is my main gripe.

Hi everyone, I have been working for a Finance org for 1+ years in the US now. But I feel the kind of role I am in is not helping me build a Data oriented career. Hence looking for a mentor who I can discuss career goals with. Reach out if you’re interested, we can get in touch!

I am a business student applying for business analyst positions. I only have one academic project on my resume:

Mining association rules from music dataset -Analyzed user music preferences using association rule mining in R from a binary dataset. -Utilized the apriori algorithm with custom thresholds using Rstudio to discover relationships between artists, providing insights for a hypothetical music streaming platform. -visualized too rules based on support, confidence, and lift, and generated artist recommendations based on frequent listening patterns

What I have listed for my technical skills are: Excel, Rstudio, Data visualization, Association rules, and cluster analysis.

Is this a decent project to have on my resume? Should I do a better job explaining it or talk about it in more depth such as normalizing the data, formatting the data, ect?

I am a Sales Operations Manager at a Fortune 500 company - in my 10 years of work experience (Fortune 100, FAANG, Fortune 500) I progressed from sales (4 years) to sales management (3 years) and eventually pivoted to Sales Operations (3 years). For the past 3 years I have been in different Sales Operations roles with escalating responsibilities (analyst -> manager -> Sr. Manager. I went from zero technical skills (I barely could use excel) to intermediate SQL and data visualization skills (Tableau mainly). I am self taught so I am sure I have lots of bad habits. I would like to further pivot to more analytics focused work as my time spent writing SQL and building Tableau dashboards is my favorite part of my job currently.

I am pretty strong socially and a good interviewer. I am wondering if I should go back to school to get my MSBA or if I should try to get some certifications and pivot into a more analytics focused career without furthering my education. I don't think my company will assist with tuition but my boss would absolutely approve and tuition up to ~50k would not be a problem. It is extremely important to me to keep building my skill set - I hated being in Sales and felt stuck for years because I didn't have any applicable skills. I have spent the past 4 years building a skill set and want to continue to level up.

Also wondering if I would be a fish out of water in any MSBA program as I am in my mid 30s. Any advice / feedback would be greatly appreciated.

I was sitting in a conference call where the billionaire ceo laid off most of their developer team and doesn’t know the difference between excel and python.

Maybe I am a bit naive, but I was hoping that our teams data driven insights would help lead to meaningful change. I have thought about going back to academia and teaching.

Any advice would be greatly welcomed!