263 Blog Posts To Learn About Analytics

2026-04-26 · Source: HackerNoon · Field: Technology & Digital — Data Science & Analytics, Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, extended

Summary

HackerNoon has compiled 263 free blog posts on analytics, ranked by reader engagement, covering a broad spectrum of topics from web and mobile app analytics to advanced data science techniques and business intelligence. The collection includes guides on building web analytics measurement plans, implementing omnichannel analytics for notifications, and automating Instagram API with Python. It also delves into SQL techniques, financial predictions, Apache Superset deployment, LTV modeling, and creating dashboards with Google Forms and Data Studio. Further topics include multi-tenant analytics challenges, knowledge graphs, API explanations, vesting schedule analysis, causal impact measurement, and the rise of blockchain data tools like Dune Analytics. The posts also address commercial analytics, scaling NestJS applications, and the application of AI and machine learning in various industries.

Key takeaway

For data scientists and business analysts seeking to enhance their analytical capabilities, explore HackerNoon's extensive collection of analytics articles. You can gain practical knowledge on diverse tools and methodologies, from web analytics to advanced machine learning applications, to inform your strategic decisions and optimize business outcomes. Focus on articles detailing specific techniques like SQL window functions or causal impact analysis to directly apply new skills.

Key insights

Analytics is crucial for business, encompassing diverse tools and methods for data-driven decision-making across industries.

Principles

• Data-driven decisions outperform assumptions.
• Clean data is essential for accurate insights.
• User-centricity improves data team effectiveness.

Method

Implement a web analytics measurement plan, utilize omnichannel analytics for notifications, and apply LTV modeling for customer acquisition evaluation. Employ SQL techniques for data warehousing and build dashboards with tools like Google Data Studio.

In practice

• Self-host website analytics using Umami.
• Track email effectiveness with Mixpanel and Mailgun.
• Use causal impact analysis as an A/B testing alternative.

Topics

• Web Analytics
• Data Engineering
• AI/ML Applications
• Business Intelligence
• Knowledge Graphs

Code references

• hackernoon/learn

Best for: Data Scientist, Data Analyst, Software Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by HackerNoon.