I'm a data analyst and IT specialist at a third-party logistics (3PL) company. I build the reporting a warehouse runs on: Python pipelines that turn raw warehouse-system exports into KPI reports, FIFO checks and Power BI dashboards, so no one has to put them together by hand.
Outside work, I pick questions I'm curious about and answer them with data. Is AI a bubble? How unusual is Luka DonΔiΔ's hot start? Can a dashboard build itself?
- π¦ At work: warehouse KPIs, operator performance, inventory and capacity planning
- π Strongest in: SQL and Excel, plus Python, Power BI and Power Automate
- π At university: information security, cryptography and C programming
- π« Reach me: LinkedIn or viktorsbergs@gmail.com
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Tracks all 10 players straight from a TV broadcast, maps them onto a top-down court in feet and measures offensive spacing frame by frame, with a broadcast-style overlay video and CSVs for SQL and Power BI.
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Tools I built and run in a real 3PL warehouse: over a dozen pipelines that turn system exports into daily and monthly KPI reports, operator scoring, FIFO compliance checks and Power BI datasets.
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An early-warning system that re-scrapes market data every week, rebuilds a SQL feature warehouse and runs seven models to estimate the odds and timing of an AI-stock crash.
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β°οΈ Hillside AIA web app that turns a spreadsheet into an interactive dashboard: it profiles the data, talks through what matters, and builds charts you can filter and edit.
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π NBA AnalysisData stories published as LinkedIn carousels, each rebuildable from public data: Luka's record-setting start and what going 2-for-1 at the end of a quarter is worth.
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IBM Data Science capstone: API and web-scraped data, SQL, interactive maps, a Dash app, and four tuned classifiers that predict whether a Falcon 9 booster lands.
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Every day
Also used in my projects
