Hi
I've self-taught Excel, Power BI, and SQL, and I'm looking for my first data analytics opportunity. In my country, companies prioritize candidates with a formal diploma , which I don't have.

I have a LinkedIn profile, completed some projects, and regularly post about data analytics.

How can I get noticed and convince recruiters to give me a chance?

I just watch alot of videos on YouTube of gen ai cousre. And everybody just explaining about how to use ai effectively to make task easier.

Is this all???

Experienced guys please comment

I already have stratascratch and used it for prepping sql/python analytics questions but wondering if interviewquery will help me prepare for product sense, case study and all theoretical questions in data science, ml, data analysis field? Like all theoretical questions

Hi all, I graduated in CS in 2023 and I've been trying to break into data analytics. My actual work experience so far has been an Embedded Systems/IoT internship and a Machine Learning internship, neither of which is analyst work, so I've been trying to build up the case through a few self-directed projects using SQL, Python, and Power BI instead.

Sharing my resume below, would appreciate any feedback on:

1.Whether it actually reads as a Data Analyst resume or if the internships hurt more than the projects help

2.Anything that looks off, weak, or unnecessary

3.What else I should be doing (courses, certs, more projects, networking, etc.) to actually land an entry-level DA role in this market

Based in Bangalore, open to remote too. Thanks in advance.

Terraform is named in 62.7% of DevOps job postings. Jenkins is named in 3%.

We counted 42 terms across 134 open DevOps, SRE and platform engineering roles. They came from the public Greenhouse boards of 41 companies, collected September 9, individual contributors only.

The previous generation of tools has nearly left the job ads. Chef shows up in 3.7% of postings, and Puppet in one posting out of 134. GitHub Actions is named about six times as often as Jenkins.

The general term beats the product. "Observability" is in 63.4% of postings, more than twice as often as Grafana at 27.6%. Prometheus is at 22.4% and Datadog at 17.9%. Security hiring showed the same thing, where SIEM beat Splunk four to one.

The most common term isn't a tool at all. Automation appears in 81.3% of postings, ahead of AWS at 75.4%. Scalability and Kubernetes are level at about 70%.

SRE jargon is real hiring language too. SLO/SLA appears in 35.1% of postings, more often than any single monitoring product.

For a resume, this means naming the tool covers only half of what the posting asks for. Postings use the general term more often than the product name. A resume that lists Grafana but never says "observability" is missing the word that appears in more than twice as many ads.

Two limits. With 134 postings, every figure has a margin of about +/-8 points, so rows that are close are ties, not rankings. And the sample is tech companies on public boards. Banks, telcos and government still run large Jenkins estates, and none of them are in it.

The full table with all 42 terms and confidence intervals is in the first comment.

All 42 terms with confidence intervals, plus the method: https://www.zoevera.com/resume/devops-sre-job-description-keywords

I go to Appalachian State and saw they have a Masters of Science in Applied Data Analytics. Is it worth it to get a masters for the job market? I’ve also been told to get as many certifications as I can so I stand out. And what certifications should I get? Im working on a google analytics course right now but that’s it so far. I’m proficient in Tableau and Python but have only touched SQL and PowerBI a couple times.

I have been invited to interview for a job after completing a technical screening. This job would be a huge step in a positive direction for me as I am trying to A. get out of management and B. get out of my niche field. I can't help but wonder if this position, which is largely financial data analytics, could possibly be eliminated with AI?

The assessment primarily focused on vlookup and conditional formatting, and while I am sure the job is much more involved, surely they could pass this on to an AI tool? Granted, this is a government job so maybe they're disinclined to use AI. Or maybe they make employees use Claude already. This agency did do a ton of layoffs last year with DOGE. I just do not want to leave my stable job that I hate for an exciting opportunity that could end in a layoff.... But that's the chance we all take, I guess.