In this tutorial, we demonstrate how we use Ibis to build a portable, in-database feature engineering pipeline that looks and […]
Category: Big Data
Why keeping old customer records could cost millions [Q&A]
The modern world thrives on data, but what happens when that data has outlived its usefulness? Legacy data can become […]
Why concentrating data in AI models demands greater vigilance [Q&A]
Data that was once scattered across sprawling systems and silos — providing natural obstacles to attackers — is now concentrated […]
How to Build an End-to-End Data Engineering and Machine Learning Pipeline with Apache Spark and PySpark
In this tutorial, we explore how to harness Apache Spark’s techniques using PySpark directly in Google Colab. We begin by […]
A Coding Implementation to Build a Unified Tool Orchestration Framework from Documentation to Automated Pipelines
In this tutorial, we build a compact, efficient framework that demonstrates how to convert tool documentation into standardized, callable interfaces, […]
Dirty data and why it’s a problem for business [Q&A]
Organizations are sitting on troves of information yet struggle to leverage this data for quick decision-making. The challenge isn’t just […]
Poor data quality is the biggest barrier to AI in insurance
Almost three-quarters of insurance underwriters say fragmented, siloed, and unstructured data — not technology — is the main barrier to […]
Huawei CloudMatrix: A Peer-to-Peer AI Datacenter Architecture for Scalable and Efficient LLM Serving
LLMs have rapidly advanced with soaring parameter counts, widespread use of mixture-of-experts (MoE) designs, and massive context lengths. Models like […]
The practical approach to building a data mesh [Q&A]
As businesses continue to generate and rely on vast amounts of data, the traditional approach to managing that data is […]
How data sovereignty is becoming mission critical to enterprises
New research shows that 30 percent of large enterprises have already made the strategic commitment to a sovereign AI and […]
