looker

Looker: Where Business Lives In Code

In its heart of hearts, Looker is a business intelligence (BI) and data analytics platform designed to help organizations explore, analyze, visualize, and share insights from their data. Originally developed independently and released in the early 2010s, Looker was built with the specific aim of working directly with large, cloud-scale data warehouses rather than importing data into an in-memory engine, which was the dominant approach among BI tools of its era. In 2019 (a lifetime ago in tool years), Google gobbled Looker for $2.6 billion, and since then it’s been appropriated into the broader Google Cloud ecosystem while still serving customers across diverse cloud environments. The platform is now positioned as one of the top-tier enterprise-grade data analysis tools that … Read more

The Best Data Analysis Tool Doesn’t Exist

The question of which is the best data analysis tool – and this is something the vendors won’t tell you – is a question without an answer. As I said in my survey piece, Overview of Data Analysis Tools, what makes one tool better than another is a combination of five qualities: governance, concurrency, simplicity, extensability, and cost. This simple list begs the question: which tool (or tools) capably checks all these boxes? The answer is: none of them. The reason this question lacks a satisfying answer is because those five qualities aren’t a list you check off, they are political/phiosophical choices, many in direct tension with one another. For example, a tool that absolutely crushes governance tends to lose … Read more

Data Analytics: An Overview of the Architecture

Ask ten developers what data analytics actually is, and you’ll get ten slightly different answers — each involving some combination of dashboards, SQL queries, and a vague promise of “insights.” What Is Data Analytics, Really? At its core, data analytics is the process of collecting, transforming, and interpreting data to support decision-making. That might sound abstract, but think of it as a pipeline with three distinct engineering challenges: A good analytics system automates all three. It bridges the gap between data in the wild (raw, messy, inconsistent) and data in context (structured, queryable, meaningful). Let’s go deeper… What Data Analytics Means To You Data analytics isn’t just for analysts anymore. Engineers now sit at the center of how data flows … Read more