Module 7 Assignment: Need for Big Data Technologies Read the assigned Shapiro Library article ("Need for Big Data Technologies: A Review") for an overview of big data basics and the technologies needed to process large volumes of unstructured data. In your journal (or discussion post/reflection),...
Module 7 Overview & Assignment ExpectationsFocus Module 7 emphasizes why traditional data management and analytics approaches fail with big data, and why specialized big data technologies are essential. It synthesizes prior modules: cloud scalability (Modules 1–2), big data tools (Module 3), NoSQL vs. SQL (Module 4),...
Module 6 Overview & Assignment ExpectationsFocus Module 6 examines how AI and IoT converge to enhance industrial operations, building on AI/ML in healthcare (Module 5), big data tools (Module 3), and cloud foundations (Module 1). Key themes: predictive capabilities, real-time monitoring, reduced downtime, and data-driven optimization...
Module 5 Overview & Assignment ExpectationsFocus Module 5 explores emerging technologies like AI, machine learning (ML), and IoT, with the assignment centering on how AI/ML transforms a specific industry context (healthcare is the most common choice). It builds on prior modules by linking AI/ML to big...
Project One Overview & ExpectationsAssignment Title Variations (from student docs): Cloud Computing Evaluation Paper Feasibility Proposal on Cloud Computing Models Exploring Cloud Computing & Big Data Challenges Key Requirements (based on templates and examples): 6–10 pages (including cover, sections, references). Structured...
Module 4 Overview & Discussion Expectations Focus Module 4 explores data storage and management in big data environments, contrasting traditional relational (SQL) databases with non-relational (NoSQL) systems. It ties into previous modules by showing how databases support big data tools (Module 3) in cloud-migrated setups (Module...
Module 3 Overview & Assignment Expectations Focus Module 3 introduces core big data concepts (from Big Data, Big Analytics Chapters 1–3) and examines tools that process, store, query, and analyze large-scale data. It builds on Module 1 (cloud) and Module 2 (migration) by exploring technologies that...
DAT 260 Module 2: SWOT Analysis – Cloud Migration Insights (Southern New Hampshire University – Emerging Technologies and Big Data course) Module 2 Overview & Assignment ExpectationsFocus Module 2 builds on cloud deployment models by analyzing the strategic decision to migrate to the cloud (often public, hybrid,...
DAT 260 Module 1 Journal: Exploring Cloud Deployment Models (Southern New Hampshire University – Emerging Technologies and Big Data course). Class Guide: Overview & Learning Objectives for Module 1Course Context DAT 260 introduces emerging technologies that support big data and analytics, with Module 1 focusing on cloud...
Abstract Cloud computing represents a fundamental shift in IT resource management, enabling on-demand access to scalable infrastructure, platforms, and software. This journal explores the four primary cloud deployment models—public, private, community, and hybrid—as formally defined by the National Institute of Standards and Technology (NIST). Each model...