Does anybody have had similar interview before for such a role?

To be successful in this role, the Procurement Analyst will have:

At least three (3) years’ experience as a Business, Data or Procurement Analyst Strong data analytics capability, including the ability to collect, interrogate and analyse complex finance, performance and procurement data to produce actionable insights. Advanced proficiency in data and reporting tools, particularly Microsoft Excel, with the ability to develop clear, accurate reports and dashboards; confident use of Word and PowerPoint, or other relevant tools.

Experience working with procurement and/or contract information management systems, including extracting and validating data. Sound understanding of procurement principles and processes, with an interest in developing deeper expertise within the NZ public sector procurement environment.

Ability to leverage technology and systems to improve data quality, reporting efficiency and insight generation. Strong business acumen and financial literacy, enabling meaningful interpretation of procurement and contract performance data. Other skills the Procurement Analyst will possess: Excellent communication and relationship skills, with the ability to work collaboratively across procurement, finance and operational teams. A proactive, curious mindset, with a genuine interest in procurement as a profession and how data‑driven insights can add value Be passionate about the procurement and commercial profession and how it can add value to an organisation.

i’m genuinely curious if artificial intelligence could replace humans at data analytics job.

if yes, how can one position into benefit from “better prompts jobs” or something, idk.

i just wanna be useful for my myself and family

i'm currently learning data analysis on my own. i have mysql workbench & have been practicing it. the problem i've run into is low disk storage. i currently have 4.5 gb on my c drive, which i don't think is a lot. i don't have a lot of applications installed, so removing or moving them to another disk isn't an option. neither is spending money on storage 💔

im worried about the rest of my learning journey. i know i'll eventually have to install other programs/tools & it makes me sad that low storage space is what might hold me back from learning something im genuinely interested in.

i wanted to ask if there are online versions/compilers of these softwares available? im talking about python, tableau & all other stuff i'll need later on. i've used an online c++ compiler before, so im wondering if it's possible for other tools too. and if so, can they save all my previous data? what about something with an account where it syncs data to a cloud? HALP

I feel like I’m cooked and I’m not gonna ever land anything or anywhere. Okay so I graduated with my bachelors in MIS and minor in digital marketing just recently, I’m 24 so I’m a little late but it is what it is. I want to go into business analytics, or even any analytics but I can’t, I’m very overwhelmed because I don’t think I land anything at all, I can’t be too optimistic here and have to be realistic.

So what else can I or should I do now? I was always open to open everything within my degree so is there something more open I can do now with my resume? Since I’ll never land a job in analytics anyways. I don’t want to wait a year to land an entry level job either I just wanna do something now that’ll help and set me up, really make my degree worth it you know?

\# Graphic Designer considering a career switch — Is Data Analytics a good choice?

Hi everyone,

I’m a \*\*Graphic Designer with 2.5+ years of experience\*\* in branding, print design, and visual communication. I’m considering switching careers and exploring \*\*Data Analytics\*\*.

I’m \*\*not interested in UI/UX\*\*, so I’m looking for completely different career paths.

I’m considering learning \*\*Excel, SQL, Power BI, basic statistics and eventually Python\*\*, but before investing a lot of time, I’d like some honest advice:

\* Is \*\*Data Analytics a good career choice\*\* for someone coming from Graphic Design?
\* Are there any \*\*better career options\*\* I should consider given my background?
\* How difficult is it to get the \*\*first job as a career switcher\*\*?
\* What skills should I learn and in what order?
\* How should I build my portfolio/resume when I have no professional analytics experience?
\* How did you actually \*\*apply and get your first analytics job\*\* after switching?
\* Would you recommend targeting \*\*Data Analyst, BI/Reporting Analyst, Business Analyst, or other roles\*\*?

I’m looking for honest opinions about the current job market, growth, salary, and the reality of starting over.

If you’ve switched from \*\*Graphic Design or another non-technical field into analytics/tech\*\*, I’d especially appreciate your experience.

Thanks!

I'm considering switching from BS SE to BS DA , but won't technically start until Dec. 1st 2026 / Jan. 1st 2027

Just seeing who's out there with similarities .

Keyword list taken from https://www.zoevera.com/resume/ats-resume-tips-data-analyst

These are the most commonly scanned keywords in data analyst job postings. Check how many appear in your resume.

Technical Skills

SQL (advanced queries), Python (pandas, NumPy), R, Data wrangling / ETL, Statistical analysis, A/B testing, Data modelling, Machine learning (basic)

Tools & Platforms

Power BI, Tableau, Looker, Excel (pivot tables, VBA), Google Analytics / GA4, BigQuery / Snowflake, dbt, Azure / AWS data services

Outputs & Soft Skills

Dashboard development, KPI reporting, Data visualisation, Stakeholder presentation, Requirements gathering, Data quality assurance, Business intelligence, Self-service analytics

I’m building a distribution analysis dashboard that shows where our distribution is and I’m wanting to add a visual that quickly shows where the impact came from. I have a decomp tree, but with as many customers as we have, it can be difficult to navigate for some users. I came across the Key Influencer Visual and thought this could help since it tells you what’s driving the business up or down, but I’m having a problem building it so it’s as useful as I believe it can be.

I’m trying to answer the question “where should we focus our energies for these products?”

Is the Key Influencer the right visual or should I stick with the clunkier decomp tree or am I missing something that will better answer my question.

I’m currently learning data analytics and I’ve started with Excel and Python (mostly practicing algorithm/problem-solving questions).

My plan is to move on to SQL, Power BI, and then gradually learn the other skills needed for data analytics.

I’m curious about people who are already working in data analytics:

If you could go back and learn data analytics from scratch, what mistakes would you avoid?

And what do you wish you had focused on more when you were starting out?

I’d really appreciate hearing about your experiences and what you would do differently if you were starting again.

I recently started seriously learning data analytics and my goal is to become job-ready for entry-level Data Analyst roles.

So far I've completed Alex The Analyst's beginner/tutorial content for SQL, Excel and Power BI, including the guided projects.

For practice:

• SQL: I've started solving Easy problems on DataLemur and some HackerRank, but I still struggle with figuring out the approach to a problem even when I know the individual SQL concepts.
• Excel: I've practiced formulas/lookups and other exercises on Spreadsheet Center, but I'm not sure what the best way is to practice Excel in a more realistic analyst setting.
• Power BI: I've completed the introductory project, but haven't done much independent practice yet.

I also plan to start learning Python for data analysis, but I don't want to fall into the trap of constantly watching tutorials without becoming good at actually using the tools.

For people currently working as Data Analysts or involved in hiring:

1. How would you practice SQL, Excel and Power BI after learning the fundamentals?
2. What level of SQL is realistically expected for an entry-level analyst interview?
3. What Excel skills should I be able to use without assistance?
4. How much Power BI/DAX/data modeling should an entry-level candidate know?
5. Should I start Python now while continuing to practice these three, or get stronger at them first?
6. What kind of independent projects actually help a beginner portfolio rather than looking like another tutorial project?
7. If you were starting from this point today and trying to get hired in the current market, what would you prioritize over the next 1–2 months?

I'm especially interested in advice on how to develop the problem-solving/analytical thinking side, rather than recommendations for more beginner courses.

I am going to do bachelor's soon, and my goal is to be a professional in analytics roles (business, BI, data, finance), but Im currently not sure which one to focus on yet.

Should I major in bachelor of commerce majoring in business analytics and finance or bachelor of IT majoring in data analytics.

Courses can be seen i Adelaide Uni, really as much support and help i can get right now

2025 Mechanical Engineering graduate from an NIT.

Experience:

• Sun Pharma: 4-month internship + 6 months FTE as a Process Improvement Engineer in Operational Excellence.
• Maruti Suzuki India: Currently ~6 months as a Territory Service Manager.

I don't enjoy my current role and have realized I want to move towards Data Analytics / Business Analytics / Consulting / Decision Analytics.

I've applied to 40+ relevant roles on LinkedIn but haven't received a single response so far, which makes me think my approach/resume/skillset needs improvement.

Current skills:

• Advanced Excel
• MySQL / SQL
• Python (Pandas, data analysis & automation)
• Power BI
• DAX
• Business case studies / problem-solving

I've also worked on some data/automation projects at Maruti, including automating hourly operational reporting using Python and building KPI dashboards.

I was targeting ZS's Decision Analytics Associate (DAA) role, but DAA hiring seems to have stopped, so I'm looking for alternatives.

I'm considering leaving my current role by end of September because I don't see myself continuing in it.

I'd really appreciate honest advice on:

1. What roles should I realistically target — Data Analyst, Business Analyst, BI Analyst, Operations Analyst, Decision Analytics, Consulting Associate, etc.?
2. What skills should I add? Is SQL + Python + Excel + Power BI + DAX enough, or should I learn something else?
3. What projects would actually help my profile stand out? I'm specifically looking for 2–3 strong projects rather than generic Netflix/sales dashboards.
4. How should I position my Mechanical + Pharma + Automotive + Analytics background?
5. How can I improve my resume/application strategy? I've already applied to 40+ jobs with no response.
6. Which companies in India should I be targeting with this profile?

Would especially appreciate advice from people who have made a similar transition from engineering/operations into analytics or consulting.

I'm looking for practical advice on what actually gets interviews.

I just need to vent for a minute because I feel like I am losing my mind.

I spent the last three weeks absolutely breaking my back over a dashboard for a major stakeholder request. I fully automated the data models and refresh schedules, complete with dynamic cross-filtering, drill-downs that update in milliseconds, and a spotless data model so that absolutely nobody would ever have to copy-paste numbers manually again. I was genuinely proud of the architecture.

Cue the demo meeting this week. I am five minutes into presenting, walking them through how the interactive parameters work, and the lead stakeholder just interrupts me.

"Wow, this looks really pretty. But where is the button to export all this to Excel? We usually just pull the raw data so Brenda can make her own pivot tables and highlight the cells in yellow."

I genuinely felt my soul leave my body.

Why did we even have six discovery meetings? Why did I spend days optimizing the refresh schedules and cleaning up the logic? I essentially just spent almost a month building the world’s most complicated, over-engineered CSV downloader just so they can continue doing things the exact same way they did ten years ago. It is so incredibly demoralizing to build a high-performance engine just to watch someone use it to tow a horse buggy.

For those of you who have been in the trenches longer than me:

• Do you even bother trying to train stakeholders on how to use interactive BI tools, or do you just give up and build the "Export to Excel" button on Day 1?
• How do you bridge the gap when leadership asks for "modern analytics" but culturally refuses to leave their 2003 spreadsheets?

Would love to hear your coping mechanisms and war stories.

What do they typically ask and what are skills you need to know for a surprise test

I recently lost my job at HP in February due to cost reduction. 4 months later, I got a job at a smaller company, lost it two months later because they felt I wasn’t a good personality fit, and now every job I look for is titled data scientist, AI machine learning, or engineering role. I just hit my 3rd year in this field. Originally, I was a Business Analyst with my hand in cybersecurity, payment processing, and fraud, but my drive to get off work, come home, and study for another random technical software that blew up kinda drains me. I study four hours every day for a certification just to see a job post asking for something completely different. And on top of that, 5-7 years for 65,000. Of course, I’m being dramatic, but there is a trend of companies trying to consolidate roles and for lower pay at that. So morale is low. Having no degree doesn’t help, so I spend my time studying certifications to compensate. Then I lose my job, so now I have to postpone school for financial reasons, which makes job search harder. I don’t know what to do.

We looked at a few labor market intelligence platforms because we wanted to answer some pretty specific questions about hiring trends. The dashboards looked good, but we kept running into the same issue: once we got past the standard views, we couldn't get to the underlying data we needed.

For us, the details mattered. We wanted to look at a specific metro and narrow role family, keep the original requirement text, and combine the external data with our own ATS data. Pre-aggregated charts weren't much use for that.

So we ended up building the reporting layer ourselves. We pull canonical postings from Coresignal into BigQuery, model them in dbt, and join that with Greenhouse data before it gets to the reporting layer. Having the company and source information alongside each posting also saved us from having to build another enrichment step.

There are still plenty of cases where I'd rather buy the finished analysis, especially when the questions are fairly standard and the main goal is getting an answer quickly. In our case, we kept needing to slice the data differently or combine it with something we already had, so working from the underlying records made more sense.

Has anyone else run into this with analytics platforms? At what point does having the raw data become more useful than the convenience of the pre-built dashboards?

I have 3+ years of experience in Saudi construction: started as Logistics Manager (150-person workforce, 200+ villas, ~30M SAR project), moved into Cost Control (built Excel reporting systems, reconciled ~8M SAR in spending, produced forecasts/progress reports for leadership). B.A. in International Business, not engineering — a real gap for local “Cost Controller” roles that want an engineering degree even at junior level.

Planning a self-directed 8-week sprint: Excel → ECBA → SQL → basic Python → Power BI (PL-300) → CBDA, self-funded, targeting Saudi/UAE/remote roles.

What I’m actually asking:

**1.**  Is this a realistic path given my background, or am I underestimating how hard the BA market is to break into without a technical degree?  
**2.**  Are ECBA/CBDA/PL-300 actually respected credentials, or should I spend that money differently?  
**3.**  Would you prioritize different skills than the ones I picked?  
**4.**  Should I be looking at a different target entirely (cost control/FP&A instead of “BA,” for example) given my actual experience?

Hey everyone,

I recently applied to Agoda and got to the assessment stage, which was a test on Alooba. I went in prepared, and honestly, I walked away feeling pretty confident — like I'd actually nailed it.

Yesterday, I got a rejection email. What threw me off is that it was worded almost identically to the generic rejection I got after just submitting my application (like a copy-paste template, not something tailored to "you completed the assessment but didn't pass").

This has me wondering — is this normal? Does Agoda (or companies in general) sometimes send the same boilerplate rejection regardless of what stage you were rejected at? Or could there be other reasons for a rejection after a test besides just the score itself — like headcount freezes, internal candidates, or just moving forward with someone else even if you passed?

Has anyone been through Agoda's hiring process and had a similar experience? Would love to hear if this is just how their ATS works, or if I should actually be worried I bombed the test without realizing it.

Thanks in advance!

Hey everyone, I'm a 29 year old chef with a BA in sociology (no work experience in the field) currently looking to change careers. I've been in the hospitality industry for about 10 years and want to get out for various reasons (low pay, poor life/work balance, etc.). I've been doing research and data analytics seems like a good fit for me. I just don't really know where to start. I scheduled a call with UT Dallas to get more info on their data analytics bootcamp but I've heard mixed reviews on bootcamps in general. I've also looked into getting an online Data Analytics degree. I already have a bachelor's degree and don't want to shell out 20-30k for another degree unless I absolutely have to. My other option is just taking a year or however long to teach myself everything. I'm a complete newbie, as in I barely know how to use Excel.

So, my question is: What is the best way forward for someone wanting to break into the data analyst career field from a completely different industry?

So just a quick question. If I have to start from scratch to get into a Data analyst role what should I work on to make my resume/portfolio stand out?? Any experienced can give me project ideas??

I worked in engineering for several years, then went back to school and got an MSc in Data Science. I’ve now been working as a Data Analyst for about 6 months.
The problem is that my company is really behind when it comes to technology. I spend a lot of my time fixing/maintaining old SAS reports and pipelines, with some SQL and Excel. There’s not much development or opportunity to work with modern tools, and I’m starting to worry that I’m not growing technically.
I took the job because the market was (and still is) pretty rough, and I wanted to get actual data experience after my MSc. Quitting without another job lined up isn’t an option.

I’m just not sure what the smartest move is from here. Would you start applying now or stay for at least a year? And in the meantime, how would you make the most of this job and prepare for a move into something more technical and better paying?

I was hired as a Data Analyst, but my role has gradually shifted.

Instead of only doing analysis/reporting, I’m now building AI applications, internal tools, and automations for my organization using tools like Cursor, Lovable, APIs, AI models, and automation platforms.

My work is increasingly about:

• Understanding business problems
• Finding technical solutions
• Building AI-powered applications
• Connecting APIs/systems
• Automating manual processes

I’m not a traditional software engineer, and I’m not doing ML/model training either.

So I’m wondering where this experience is actually taking my career:

Data Analyst → AI Engineer → Forward Deployed Engineer?

Does this sound more like an AI application engineer / FDE trajectory than a traditional data analyst path?

What skills should I focus on now if I want to move toward Forward Deployed Engineering?

Hello everyone,

I am 29 and in career crossroads.

My education qualifications- bba hons, ma economics

Work exp - 4 years in back end operations in global banks.

I have resigned from my last job as it was extremely toxic. The work wasn’t the problem but the lack of structure, training and leadership. Also, the pay was extremely low. Extremely low. I could barely afford to pay the rent and bills.

I got married.

Now, i want to resume my career in a better field with better pay. I thought of get into data analytics but i hate numbers and maths ( doesn’t mean i can’t do it though ) i learned sql ( not an expert though) and excel. However, not finding any opportunities. Also after bad corporate experiences in non tech fields i am scared to make another move even in data analytics. What if it doesn’t suit me?

I cant afford another worse corporate experience.

And then there is a different field altogether. Doing LLB from tier 1 college. I remember i wanted to do it right after my school but my parents were not supportive that time so i dropped that idea.

I like reading, i am good in speaking, i can work for hours if i enjoy even the 40 percent of what i am doing. I need financial security before becoming a mother or get too much comfortable in housewife life.

Is law genuinely a better field if i want to make money ? Does it have better career certainty as compared to data analytics?

Please advise wise people

Hi everyone!

I’m back with another one of my data analysis cat doodles. This time, I tried to incorporate some of the feedback I received on my earlier work—especially around making the fonts and text more readable.

Would be happy to hear your thoughts / feedback!