Big Data Is Dead — Why Your Laptop Is Probably Big Enough
The 'big data' era was real, but it ended quietly. Hardware caught up, working sets shrank, and single-node engines like Polars and DuckDB beat the cluster on most workloads.
Read articleNotes on local data platforms, Polars and visual ETL
Practical writing on building data pipelines that run on your laptop — from Excel automation to Delta Lake catalogs to the Polars vs Pandas debate. Updated as Flowfile ships.
Automate Your Excel Workflows Without Writing Code
If you rebuild the same Excel report every week, you don't need Python. Here's how visual data pipelines turn that work into a repeatable, one-click process.
Read articleThe Best Way to Learn Python Is to Build Something You'd Actually Use
Tutorials teach syntax. Building real things teaches everything else. Reflections on learning Python the hard way — through a year-long project called Flowfile.
Read articleFrom Alteryx to Flowfile: A Practical Migration Walkthrough
How to rebuild a real Alteryx workflow in Flowfile — a weekly sales report with lookups, a pivot, and an Excel output — node by node, in under an hour.
Read articleDemystifying Delta Lake: What It Is and Why It Matters
Delta Lake is not a database. It's a transaction log over Parquet that gives you ACID, time travel, and schema evolution — without a server. Here's what it does, in plain English.
Read article76× Faster Fuzzy Joins: How pl-fuzzy-frame-match Works
Brute-force fuzzy matching is O(N×M) — at 1.2 billion comparisons it falls over. Here's how a two-stage hybrid (ANN + exact scoring) reduces that to seconds while preserving accuracy.
Read articleFlowfile's Kafka Source: How Micro-Batching Actually Works
A code-level walkthrough of Flowfile's Kafka source: the 500-message poll, the 100k-row spill to Arrow, Polars LazyFrames, and consumer-group offsets.
Read articleFuzzy Match in Polars: Joining on Dirty Data with Flowfile
Every real dataset has 'Acme Corp' vs 'ACME Corporation' somewhere. Here's how Flowfile's fuzzy_join — built on Polars and Levenshtein — handles it without a regex in sight.
Read articleConnections, Secrets, and the Catalog in Flowfile's Python API
How Flowfile registers database and cloud-storage connections once — in Python or the UI — and references them everywhere by name, with encryption handled for you.
Read articleKafka for Analysts: A Practical Guide to Streaming as Micro-Batches
Most analytics 'streaming' is really a sequence of micro-batches. How to think about cleaning, combining, and enriching Kafka data without a streaming engine.
Read articleWhy Your Data Should Stay on Your Laptop
Local compute plus a built-in data catalog gives you the speed of a desktop tool and the structure of a warehouse — without sending a single row to the cloud.
Read articleOpen-Source Alternatives to Alteryx in 2026
Alteryx is powerful, but the licensing has gotten brutal. An honest comparison of the open-source visual ETL tools worth evaluating in 2026.
Read articlePolars vs Pandas in 2026: A Practical Guide
Polars is faster, lazier, and stricter than Pandas. Pandas has 15 years of ecosystem. A practical, honest take on when to use which in 2026.
Read articleVirtual Flow Tables: When a Catalog Entry Is a Pipeline
Most data catalogs know about materialized tables and SQL views. Flowfile adds a third option: a catalog entry that points at a pipeline and resolves lazily. Here's how and why.
Read articleWhat Is a Data Pipeline? A Plain-English Guide for Analysts
A data pipeline is a saved recipe that turns raw data into something useful. Here's what one is, what the parts are called, and how to build your first one without a data engineering degree.
Read articleBubble + Stripe + Mailchimp: A Non-Technical Founder's Playbook
You built a product on Bubble, you charge with Stripe, you email with Mailchimp. Here's how to connect all three into one view of who signs up, who pays, and who sticks around.
Read articleCRM, ERP, ETL: Which Three-Letter Acronyms a Small Business Actually Needs
Software vendors love three-letter acronyms. Here's a plain-English guide to which ones matter for a small business, which ones you can ignore, and what to buy when.
Read articleMeta vs. Google Ads: How to Actually Tell Which One Is Selling
Meta says 40 sales. Google says 32. Shopify says 58. Here's why all three are 'right' and how to build a single number you can trust.
Read articleRFM: The 50-Year-Old Customer Segmentation Every Small Business Should Steal
Your VIPs, your churn risks, and your dead weight are hiding in the same customer list. RFM is the simple scoring model that separates them in under an hour.
Read articleStop Copy-Pasting Between Spreadsheets
If your weekly routine involves downloading three exports and stitching them into one master sheet, you're doing a robot's job. Here's the non-technical way to hand it off.
Read articleThe 10 Numbers Every Small Business Should Track Each Week
A flagship weekly scorecard for small business owners: what to track, where to find each number, and how to stitch them into one report in under an hour.
Read articleWhat Is a Data Pipeline? A Small Business Owner's Guide
If you've heard the term 'data pipeline' and assumed it wasn't for you, here's the plain-English version for small business owners — no engineering background required.
Read articleNo posts match your search.