Software Engineering Institute | Carnegie Mellon University
Software Engineering Institute | Carnegie Mellon University

Digital Library

Javascript is currently disabled for your browser. For an optimal search experience, please enable javascript.

Advanced Search

Basic Search

Content Type

Topics

Publication Date

Showing 1 - 10 of 41 results for the Big Data

Presentation | August 2017 - Presentation Data Science Tutorial By Eliezer Kanal, Daniel DeCapria

This tutorial offers training on data science in cybersecurity principles and practices.

Collection | August 2017 - Collection CERT Data Science and Cybersecurity Symposium

The CERT Data Science and Cybersecurity Symposium highlighted advances in data science, reviewed government use cases, and demonstrated related tools.

Presentation | March 2017 - Presentation 6 Things You Need to Know About Data Governance By John Klein

This presentation presents a framework to guide governance decisions.

Presentation | November 2016 - Presentation Data Science: What It Is and How It Can Help Your Company By Eliezer Kanal, Brian Lindauer

In this presentation, the speakers discussed what the term “data science” means, what skills a data scientist brings to the table, and what competitive edge data science can bring to your team.

Brochure | December 2016 - Brochure Big Data Architectures and Technologies: SEI Training

This infosheet describes the benefits of and requirements for taking the Big Data Architectures and Technologies course for architects and technical stakeholders.

Conference Paper | May 2016 - Conference Paper A Reference Architecture for Big Data Systems in the National ... By John Klein, Ross Buglak (Data to Decisions Cooperative Research Centre), David Blockow (Data to Decisions Cooperative Research Centre), Troy Wuttke (Data to Decisions Cooperative Research Centre), Brenton Cooper (Data to Decisions Cooperative Research Centre)

This paper presents a reference architecture for big data systems that is focused on addressing typical national defense requirements and that is vendor-neutral.

Conference Paper | April 2016 - Conference Paper Model-Driven Observability for Big Data Storage By John Klein, Ian Gorton (Northeastern University), Laila Alhmoud (Carnegie Mellon University), Joel Gao (Carnegie Mellon University), Caglayan Gemici (Carnegie Mellon University), Rajat Kapoor (Carnegie Mellon University), Prasanth Nair (Carnegie Mellon University), Varun Saravagi (Carnegie Mellon University)

This paper presents an architecture that automates metric collection processes for big data systems using a distributed runtime observability framework.

Presentation | August 2017 - Presentation Applied Machine Learning in Software Security By Eliezer Kanal

In this presentation, Eliezer Kanal discusses how machine learning speeds prediction and classification in cybersecurity.

Conference Paper | January 2015 - Conference Paper Runtime Performance Challenges in Big Data Systems By John Klein, Ian Gorton

This paper presents a reference architecture for big data systems. It uses a model-driven engineering toolkit to generate architecture-aware monitors and application-specific visualizations.

Article | May 2014 - Article Distribution, Data, Deployment: Software Architecture ... By Ian Gorton, John Klein

This paper describes the challenges of big data systems for software architects, including harmonizing designs across the software, data, and deployment architectures.

Refine