Three Data Point Thursday

Three Data Point Thursday is a Substack dedicated to enhancing business intelligence through data and AI. It explores the strategic implementation of data teams, AI advancements, data analytics, synthetic data, and open-source contributions to building data-driven companies. The newsletter emphasizes practical approaches for leveraging data for business value, innovation, and efficiency.

Data Strategy Artificial Intelligence Data Analytics Business Intelligence Open Source in Data Synthetic Data Data Engineering Machine Learning Data-Driven Decision Making Community Building in Tech

The hottest Substack posts of Three Data Point Thursday

And their main takeaways

3 Actionable Tactics To Create A Good Data Strategy

39 implied HN points • 01 Feb 24
💼 Business Data Strategy Product Management
  1. Netflix transformed into a data company by focusing on leverage and transitions in their value chain.
  2. To create a good data strategy, consider mapping out your value chain, playing Perfect World scenarios, and performing pipeline analysis.
  3. Use data and algorithms to increase the bottleneck in your value pipelines for impactful data strategies.
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Unstructured Data Unravelled

19 implied HN points • 14 Dec 23
🕹 Technology Data AI Tools Processes
  1. Unstructured data is better understood when seen as 'complex' data.
  2. Structured data is in the format tools can process; unstructured data needs transformation.
  3. Focus on what you want to do with data and the cost of transforming it to the right format.

Analytics Engineering (NOT DBT!) 101

39 implied HN points • 14 Sep 23
🕹 Technology Data Analytics Cyber Security AI Organizational Change
  1. Cyber security is evolving due to personalized threats; data-driven security is critical.
  2. Synthetic video presenters are emerging as a trend with growth potential in various sectors.
  3. Analytics engineering involves bridging the gap between data analytics and engineering through organizational change.
  4. Companies need to consider upskilling analysts or hiring analytics engineers to streamline data flow.

What people are not seeing about TimeGPT

19 implied HN points • 16 Nov 23
🕹 Technology AI Data Analysis Machine Learning Forecasting
  1. Time series models, like TimeGPT, are advancing and will provide a significant boost in machine learning capabilities.
  2. Adding time as a feature in models can enhance data analysis due to the information richness of recent data.
  3. Although skepticism exists around time series machine learning models, advancements in generic models like TimeGPT are removing some barriers.

Why You’re Missing The Point Of Analytics

19 implied HN points • 05 Oct 23
🕹 Technology Data Analytics Data Management Data products Data Storage
  1. Analytics and Business Intelligence are about turning data into actionable insights, not just analyzing historical data.
  2. Separating data into 'hot' and 'cold' categories can lead to cost savings and less complexity in data management.
  3. Be cautious of the term 'data product' as it can have different meanings to different people, and ensure clarity in hiring, marketing, and tool usage.

How to become a data business

19 implied HN points • 20 Jul 23
🕹 Technology AI Data Business Products Innovation
  1. The key to becoming a data business is focusing on smart products over improving business decisions.
  2. When integrating AI into products, focus on solving bigger problems for customers instead of just improving efficiency.
  3. Artificial Intelligence can accumulate knowledge without the burden that humans face, leading to unpredictable situations.

Data and Predictions for 2023! ThDPTh #81

19 implied HN points • 08 Dec 22
  1. Focus on tools and practices that reduce time on non-value producing activities in data engineering.
  2. Transition from big data to fast data by empowering all employees to use data, using multiple data sources, and focusing on speed.
  3. Despite some slowdown, IoT growth remains at 8% YoY with significant investments in analytics, AI, and security.

You're successfully been migrated

39 implied HN points • 05 May 22
  1. The migration to Substack was successful.
  2. The next newsletter will be on the 6th for a Thoughtful Friday.
  3. Sven Balnojan is keeping readers informed and engaged.

# 100th Newsletter - Let’s look back just for 3 minutes

19 implied HN points • 18 Nov 22
  1. The author reflects on the history of their newsletter and how it evolved over time.
  2. The author's newsletter focuses on building exceptional data companies, products, teams, and utilizing open-source.
  3. The readership of the newsletter includes people from data companies, investment-focused individuals, open-source founders, data leaders, engineers, and scientists.

Thoughtful Friday #18: Winning in Snowflake-like Markets

19 implied HN points • 23 Sep 22
  1. To win in data markets, network effects are crucial.
  2. Open Source is not the only method for creating network effects.
  3. Companies like Databricks, Dbt, and Airbyte use different strategies to solve the 'snowflake problem' in data markets.

Dagster 1.0, VAST, Democratic AI; ThDPTh #75

19 implied HN points • 01 Sep 22
  1. Data developer experience is crucial for platforms like Dagster 1.0.
  2. VAST addresses network security needs with its open-source protocol.
  3. Democratic AI explores human-centered mechanism design for social mechanisms.

Thoughtful Friday #12: Thin vs. Fat Platforms

19 implied HN points • 20 May 22
  1. Twitter opts for a 'thin' platform interface that changes minimally.
  2. Building thin interfaces is recommended for platforms.
  3. Platform interfaces should be simple and hidden complexities inhibit platform growth.

🐰 #17 Singer SDK, Data as a Product, Readmes for Data; ThDPTh #17 🐰

0 implied HN points • 29 Apr 21
  1. Future of data is open-source with tools like Singer SDK advancing data-related work products.
  2. Viewing data as a product, managed with product techniques, is crucial for effective data management.
  3. Utilizing Readme Driven Development can simplify the documentation process, making work products more focused and clear.