Overview

Google, IBM & Meta Certificates – 40% Off

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By the end of this course, you'll be able to define what makes data "big," distinguish Big Data from a traditional data warehouse, and map the core layers of a Big Data architecture from ingestion to serving. You'll compare processing approaches like batch, streaming, and Lambda, weigh core technologies such as Hadoop, Spark, and Kafka, and evaluate on-premise, cloud, and hybrid hosting against the principles that matter most: performance, availability, scalability, flexibility, and cost. Led by a data and AI cloud architect with over a decade of hands-on experience building solutions for companies of all sizes, this course turns an intimidating buzzword into practical, decision-ready knowledge. You'll move beyond theory with a real-world case study, an inside look at cloud services, and a clear view of the business side of Big Data, from building data teams to avoiding the pitfalls that quietly derail projects. Whether you're a manager scoping your first Big Data initiative or a professional strengthening your foundations, you'll finish ready to make confident, informed choices about implementing Big Data in your own organization.

Syllabus

Defining Big Data

Big Data sits behind nearly every app you touch, yet the term is easy to misread and costly to get wrong. In this module, you'll pin down what makes data "big," tell it apart from a traditional data warehouse, and spot real use cases so you can put your organization's data to work.

Processes and Concepts

A Big Data project succeeds or stalls based on how well its moving parts fit together. In this module, you'll map the layers of a Big Data architecture, compare processing approaches and core technologies like Hadoop, and weigh hosting options so you can design solutions that fit your needs.

The Cloud

The cloud has reshaped how organizations build and scale Big Data without buying a single server. In this module, you'll distinguish the major cloud delivery models and weigh the benefits of running Big Data in the cloud so you can decide where your solutions belong.

Case Study

Seeing Big Data solve a real business problem makes the concepts click in a way theory can't. In this module, you'll examine how Home Depot moved to cloud-based Big Data and trace the results so you can apply the same thinking to your own data challenges.

Building Data-Driven Organizations

Technology alone doesn't make an organization data-driven; people, products, and process do. In this module, you'll apply the Data as a Product model, map out the roles of a strong data team, and pinpoint the pitfalls that derail projects so you can build solutions that deliver lasting value.