Tag Archives: big data

SEI Offers Courses on Big Data, DevOps, and Technical Debt at SATURN 2015

At SATURN 2015, to be held in Baltimore, Maryland, April 27-30, 2015, the SEI will augment the three-day technical program with three one-day courses offered on Monday, April 27.

SEI courses are created and delivered by recognized experts who have practical experience in the disciplines they teach. Our courses feature participatory tasks and real-world scenarios to enhance your learning.

Big Data: Architectures and Technologies (instructors, Ian Gorton and John Klein)

Scalable big-data systems are significant long-term investments that must scale to handle ever-increasing data volumes, and therefore represent high-risk applications in which the software and data architectures are fundamental components of ensuring success. This one-day course is designed for architects and technical stakeholders such as product managers, development managers, and systems engineers involved in the development of big data applications.

More information
Register now

DevOps and Continuous Delivery: Software Architecture, Security, and Interactive Learning (instructor, Stephany Bellomo)
Continue reading

Advertisements

SEI Offers Course on Big Data

Software Engineering Institute (SEI) research forms the foundation for a new one-day course from the SEI, Big Data: Architectures and Technologies.

To learn more, see this article about the SEI big-data course on the SEI website.

The new big-data course, along with one-day courses on DevOps and technical debt, will be offered at SATURN 2015, which will be held in Baltimore, Maryland, April 27-30.

SATURN 2014 Art and Science of Scalability Session (notes)

Notes by Ziyad Alsaeed, edited by Tamara Marshall-Keim

BI/Big Data Reference Architectures and Case Studies
Serhiy Haziyev and Olha Hrytsay, SoftServe, Inc.

Serhiy and Olha shared their experience with the tradeoff between modern and traditional (non-relational and relational) reference architectures. They looked into the challenges associated with each approach and gave tips from real-life case studies on how to deal with big data reference architecture. As a reminder, they visited some of the known big data challenges:

  • Data is generated from many and different sources.
  • As data grows, it becomes complicated and heterogeneous (velocity and volume) until it’s no longer manageable.

Continue reading