Umami is a modern, privacy-focused analytics platform. An open-source alternative to Google Analytics, Mixpanel and Amplitude.
🏃 An R package for advanced sports performance analysis and training load monitoring using Strava data.
A web application to find patients, build cohorts and visualize health records
Algorithmic Marketing based Project to do Customer Segmentation using RFM Modeling and targeted Recommendations based on each segment
A Snakemake workflow to process single samples or cohorts of Illumina paired-end sequencing data (WGS or WES) using trim galore/bwa/GATK4/parabricks.
Cohort graph (Cohort Analysis)
A fully interactive data storytelling dashboard for e-commerce analytics. Built with Python, Streamlit, and Plotly, it transforms transactional data into actionable insights through KPIs, cohort retention, RFM segmentation, and global visualizations, perfect for analysts and data scientists.
A comprehensive guide and codebase for building interactive storytelling dashboards with Python, Streamlit, and Plotly. Learn how to transform static analytics into dynamic, user-driven data experiences that engage and inspire, featuring RFM segmentation, cohort analysis, and real-world insights.
Flowchart is a STATA module/package that generates publication-quality Subject Disposition Flowchart Diagrams in LaTeX Format. This package generates PGF/TikZ code through texdoc, compiled in LaTeX to produce the diagram as a PDF. The final diagram is the same in style as ones used in the PRISMA Statement, CONSORT 2010 Statement, or STROBE State…
Custom Cohort Visualization based on Kibana NP
An R package for easy cohort analysis with event data
A long-form analytics article on why KPIs fail when the denominator silently changes. Covers denominator contracts, eligibility vs observed vs attempted populations, drift/coverage failure modes, mix shifts, time alignment, and a practical audit checklist to design decision-safe ratio metrics that don’t lie.
NHC: A computational approach to detect physiological homogeneity in the midst of genetic heterogeneity
A deep-dive analytics article on why most KPI “trends” are actually measurement artifacts. Covers the fake-trend taxonomy (schema drift, coverage loss, time shifts, backfills, dedupe, sampling, mix change), a Trend Courtroom evidence protocol, segment invariance tests, and copy-ready checklists + a Trend Report Card for decision safety.
Jupyter Notebook Praktikum Projects. This is repository with data analyst educational projects from Yandex.Praktikum.
Longform data analysis article arguing every “dataset” is actually three: Observed (captured rows), Missing (what should exist but doesn’t), and Excluded (what filters/joins/dropna removed). Includes dataset accounting, join-loss and missingness audits, segmentation checks, and practical templates to prevent biased KPIs and wrong conclusions.
Deciphering Bitcoin Blockchain Data by Cohort Analysis
This project uses Python and Jupyter Notebook to perform time-based Cohorts Analysis to assess and compare retention, order items quantity and order revenue of different customer cohorts.
The fastest way to make sense of a transaction log.
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