William Fetzner

This month I’ve been seeing a lot more Data Analyst positions opening up. How long will this last? No one knows. But, this is a sign that even in a volatile Job market opportunities can spring up when least expected. This is why it’s best to stay prepared. Keep your skills sharp, keep your resume updated and remain consistent in your job search. Play around with the terminology. Don’t just search Data Analyst, but also try to search by the skills you acquired. For example type in “Power Bi” in the job boards and see what all roles pop up. You might be surprised what roles come up that don’t necessarily have the title “Data Analyst” Eventually one of these open roles will be sending you an offer letter. This is the time to stay prepared or get prepared. The market will bounce back before you know it.

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Tackling a Challenging SQL Baseball Interview Question! ⚾ https://lnkd.in/eZvRNvuU Check out my latest video where I dive deep into a complex SQL problem centered around baseball statistics. Maybe you're prepping for an interview, love SQL, or are just a baseball stats nerd. Hopefully going to start making more Sports+Data content soon! #SQL #DataAnalysis #Baseball #InterviewPrep #ProblemSolving #DataScience #TechSkills #SportsAnalytics

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And this is why I love Udemy, DataCamp, Mimo, Coursera, and W3Schools.com among many others.. Learning on the go and in snippets just large enough to keep your focus, but short enough to squeeze in lessons during a busy schedule! All I use for work are Excel and SQL with some Crystal Reports sprinkled in, but that doesn’t mean that’s all I know how to do!! #dataanalyst #r #python #excel #tableau #powerbi #sql #java #machinelearning #statisticalanalysis #datascientistintraining #exceedyourlimits

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"The difficulty of finding a job is wildly overreported, there are still people out there getting good jobs and I love helping them" - Albert Bellamy This is not one you want to miss! Albert joins me as a guest on The Data Nerd Podcast as we discuss building a resume for the job you want. It was a reality check for me as he talked through fixing my own resume, and best practices anyone can apply to get the job they want. We discuss everything from do's and don'ts, how to ensure your resume is making it through the ATS (applicant tracking system), and how to ensure you're telling the story that needs to be heard on your resume. Known as "the Marine who smiles at spreadsheets" and renowned for fixing broken resumes, Albert brings over two decades of diverse experience to his role as an Alteryx instructor. You can catch the podcast on YouTube or any podcast platform. YouTube: https://lnkd.in/e2v-frpG Spotify: https://lnkd.in/eZJ_mA_J Apple: https://lnkd.in/evD3qk7T Amazon: https://lnkd.in/eqd3_WHz #data #analytics #resume #datacareers #jobs

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I realized something pretty fundamental about SQL that I don't think I've personally ever heard stated explicitly. When you select a column without grouping/aggregation, it's as if you are completely separating this column from the rest of the table and returning it. This may seem obvious. But think about the implications when attempting to select a grouped by column with a non-grouped column SQL will try to return all the data from the non-grouped column and combine it with the grouped data, which will contain less rows. At least in MySQL this does not produce an error, but it will result in incorrect data. To solve select only what you are aggregating and grouping. Then do a self join on the fields that you are aggregating and grouping.

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*** If are looking to hire an analytics professional, please send me a message. I am looking for new opportunities and available to start ASAP. ***    One of my pet peeves when I perform code reviews is seeing multiple chunks of SQL code strewn throughout a R or Python script. Instead of unnecessary lines thrown into a script, I always push for two specific actions. A. Throw the data you need into a database table and select from there. B. Throw all the queries you need into various SQL files and use those in your R or Python scipt to pull the appropriate data. I actually prefer solution B in most cases. One just needs a few functions to grab the SQL file, convert it into a string, and pull data from the database. In the following example, you have a simple query. Throw that into a .sql file and then we use a user defined function I created (GetSqlData) to get the query and extract the data. #recruiter  #analytics  #datascience  #rstats  #sql

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Chris French has developed a dashboard that shows data analytics jobs posted by individuals on LinkedIn, not in the jobs sections. With so many places to look, Chris has developed a curation process that not only shows a job posting, but humanizes that job search with a name and face for who posted the job. the little things that will make a big difference! #dataanalytics #datahumanizing #jobsearch #opentowork

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Many people think being a data engineer means you'll get to build sweet pipelines and code in Python or SQL all day. What they don't tell you is the inordinate amount of time you'll be dealing with networking, authentication, and credential-based issues you need to solve on a daily or weekly basis before you can do the 'fun' stuff! However, I do feel fortunate to be at an organization that gives me the autonomy and responsibility to learn this side of engineering because I've always favored learning how the whole system works and not being too narrowly focused.

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You're hired as a Data Scientist to solve specific business problems. So think about what types of problems you want to solve, and then build projects related to those problems (aka Tailored Projects). Otherwise you'll end up applying for any Data related role just so you can 'get something' and before you know it, you've applied for hundreds of jobs with no response. Tailor your projects to the jobs you actually want. To help you do this, I'm sharing my ultimate guide to Tailored Projects on Wednesday the 10th July, 09:30 am What would you like to see in the guide?

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Here is my submission to Maven Analytics commuter challenge! In this challenge, I was tasked with analyzing the MTA's post-covid ridership trends. If you are interested in the insights I gathered, view the project below! #mavencommuterchallenge https://lnkd.in/dAuujjTd

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Just applied for a job at Tiger Analytics and got this auto-reply: "Thank you for your applying for {{Job_name}}." Looks like I might have invented a new job title! 😂 😂 Despite the typo, I'm super excited about the opportunity. Fingers crossed they figure out which position it is! #tiger_analytics #CareerJourney #DataScience #TechJobs #JobHunt #NewOpportunities #CareerGoals #JobSeeking #HumorInTech

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In order to break into the analytics engineering position or to be very good at it, you have to have a very solid understanding of these two core topics: 1. Table Grain/Granularity 2. Different Types of SQL Joins and Unions I often refer to excelling in this position as being a "table surgeon".

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Do you sometime feel you are a Data Janitor instead of a Data Analyst/Engineer? Me too. Between missing info, bizarre inconsistencies, and outright errors, our job is one big data cleanup party. The real skill isn’t just in the tech—it’s in surviving the chaos with your sanity intact. Here’s to chasing perfect data and finding humor in the madness! 🚀 #DataQuality #DataAnalytics #DataEngineering #TechChallenges #DataDrama

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Tired of Feeling Like a Data Analyst Rookie? Level up your skills beyond the bootcamp curriculum! This blog unpacks the soft skills needed to thrive as a senior analyst. (Think communication, collaboration, and more!) Get insider tips on: -         Reproducible Analysis (no more hunting for old code!) -         P-Values Explained (made simple!) -         Tracking Your Analyst Achievements Ready to make an impact? Head over to Muvaamia for more! https://www.muvaamia.com/ #DataAnalysis #SoftSkills #CareerGrowth

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"I've sent out hundreds of applications for data analyst roles, but so far, crickets." This is the reality for many recent grads, or anyone looking to pivot into a career in data analytics. So, how do you cut through the noise and make your mark in this seemingly oversaturated field?" Get a referral. AI makes it so easy for job seekers to blast out hundreds of job applications each week, which means the competition is great but the quality is bland. Hiring managers are swamped and don't have time to sift through every resume they receive. Genuine referrals are more valuable than ever. Instead of spending time sending out generic applications, spend time building sincere relationships with people you find interesting. Join online groups, attend free conferences, ask coworkers questions. Turn your previous experience into an asset. Do you have experience in Finance? Customer service? Retail? Education? Every industry uses data and has a need for a data analyst. My degree in Civil Engineering played a major part in landing my first data analyst job at a transport service company. Hiring managers are looking for someone who can speak the language of the data and analyse it in the context of the business. Bonus points if you have any industry-specific skills or certifications. So much could be said. Current data analyts, what advice do you have for aspiring data analysts? ⬇️ #datanalyst #dataanalysis #dataanalytics

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Making good headway on my SQL 101 course. This is going to be different than a lot of courses out there. I am still a few weeks out from recording and releasing it. But I would love you hear from you. What questions do you have about SQL that you just cant seem to find the answer from any other beginner course?? ----- I want to help you understand the things I never did after doing countless courses. How do you connect to an online database? What exactly do you do with the data after you query it? How can you use SQL in conjunction with other data tools like Excel/Python? What does an actual day in the life Analyst do and how could SQL help you accomplish that?? How do you use more advanced concepts like stored procedures to make you job easier?

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💡 How do I use visualization to solve my own problem at work. I was asked why a data point seems high comparing to couple months ago. Here is how I did it: 1) Used Tableau to draft a graph to see the trend of this data point over the past 2 years 2) Notice a trend of some month having higher number than the rest 3) Explain to the person about the data trend over time Have you ever created visualization to solve a problem?

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I dedicate my free time to learning more about Tableau. Alongside my graduate courses, I make use of time blocks to further my understanding of Tableau's features. #Tableau #Analytics #Data

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