The hottest Data Analytics Substack posts right now

And their main takeaways
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GroupBy #9: FDAP stack, Iceberg and Hudi ACID Guarantees, Data Driven Management

VuTrinh. • 0 implied HN points • 14 Nov 23
đź•ą Technology Data Engineering Data Analytics Machine Learning Software Development Data Management
  1. The FDAP stack is important in building reliable data systems. It helps to manage data more efficiently by using advanced technologies.
  2. Learning about data quality is crucial. It ensures that the information used for decision-making is accurate and trustworthy.
  3. Data-driven management is all about making decisions based on solid data insights. It helps businesses understand what works and what doesn't.

Unlocking Insights with Apache Spark: A Beginner's Guide to Data Aggregation

DataSketch’s Substack • 0 implied HN points • 03 Apr 24
đź•ą Technology Data processing Software Engineering Big Data Data Analytics Programming
  1. Apache Spark is a powerful tool for analyzing big data due to its speed and user-friendly features. It helps data engineers to work with large datasets effectively.
  2. Data aggregation involves summarizing data to understand trends better. It includes basic techniques like summing and averaging, grouping data by categories, and performing calculations on subsets.
  3. Windowing functions in Spark allow for advanced calculations, like running totals and growth rates, by looking at data relative to specific rows. This helps to analyze trends without losing the detail in the data.

Harnessing Data Architecture: Practical Models and SQL Solutions

DataSketch’s Substack • 0 implied HN points • 26 Mar 24
đź•ą Technology Data Engineering Database Design Software Development Information Systems Data Analytics
  1. Creating effective data models is crucial for businesses to organize and use their data efficiently.
  2. Different industries like eCommerce, healthcare, and retail have unique data needs that can be addressed with tailored database solutions.
  3. Understanding SQL and how to create tables and relationships helps in developing strong data architecture.

Is dbt Labs cannibalizing the modern data stack with dbt Cloud?

clkao@substack • 0 implied HN points • 18 Oct 24
đź•ą Technology Data Management Software Development Cloud Computing Data Analytics Machine Learning
  1. dbt Labs is expanding its features to create a more unified data platform. This means users won’t need multiple tools since dbt can handle many basic data needs.
  2. Applying software development practices to data workflows can be tricky. The way we test data is different, and adopting these practices hasn’t been easy for everyone.
  3. Recce is designed to improve the software development workflow for data. It helps users validate changes easily and ensures everyone understands what correctness means in the data context.

Precog and Bittensor: Redefining Crypto Market Intelligence

Coin Metrics' State of the Network • 0 implied HN points • 28 Jan 25
đź”® Crypto Blockchain Market Trends Decentralization Data Analytics
  1. Bittensor is a decentralized network that rewards users for solving AI tasks. This way, the best performers get recognized and compensated for their work.
  2. Precog, built on Bittensor's infrastructure, allows users to compete in predicting crypto prices. Those who make accurate forecasts can earn rewards, making the process both competitive and engaging.
  3. The entire system uses blockchain technology to ensure fairness and transparency. This way, everyone involved can trust that rewards are distributed based on performance.
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