Browsing: Analytics

print(“\n” + “=”*70 + “\n SECTION 6 — NetworkX analytics\n” + “=”*70) def kg_to_networkx(graph): G = nx.MultiDiGraph() for e in graph.entities: G.add_node(e) for s, p, o…

Organizations today are increasingly looking to combine analytics and AI to accelerate insights and decision-making. Amazon Quick, a unified agentic AI-powered analytics and decision intelligence service,…

Modern enterprises face mounting challenges in extracting actionable insights from vast data lakes and lakehouses spanning petabytes of structured and unstructured data. Traditional analytics require specialized…

In this tutorial, we build a comprehensive, hands-on understanding of DuckDB-Python by working through its features directly in code on Colab. We start with the fundamentals…

Image by Author | Canva   # Introduction  Data analysis problems aren’t really unique. However, “though your problems are non-unique, that doesn’t make them go away,” to…

For different learning styles, career goals, and comfort with tools, finding the right data analyst course is HARD. Some people start with Excel. Others into Python.…

Sponsored Content      Gartner’s new insights, “5 Critical Shifts D&A Leaders Must Make to Drive Analytics and AI Success,” delivers essential, evidence-based guidance for Chief…

In this tutorial, we implement a production-grade, large-scale graph analytics pipeline in NetworKit, focusing on speed, memory efficiency, and version-safe APIs in NetworKit 11.2.1. We generate…

Call center analytics play a crucial role in improving customer experience and operational efficiency. With foundation models (FMs), you can improve the quality and efficiency of…

In this tutorial, we design an end-to-end, production-style analytics and modeling pipeline using Vaex to operate efficiently on millions of rows without materializing data in memory.…