This guide provides a foundational overview of data analytics and its role in helping organizations become AI-ready. It explains key analytics types—descriptive, predictive, and prescriptive—and why analytics is critical for competitiveness, innovation, and informed decision-making. The document explores common data architectures, including data warehouses, lakes, lakehouses, and data mesh, and discusses the evolution from legacy systems to cloud-based platforms. It highlights challenges such as data silos, cost inefficiencies, and scalability limits, and shows how modern cloud analytics platforms address them. The guide emphasizes analytics as the backbone for AI, enabling faster insights, collaboration, and long-term strategic planning.

Join for free to read