Replay video sessions and keynotes from the No Magic World Symposium 2016 with presentations focusing on Technology & Enterprise Architecture, Model-Based Systems Engineering (MBSE), and Workshops & Tutorials.

Technology & Enterprise Architecture: Big Data from a Rookie's Perspective

Speaker: Matt Sheranko - Systemize Corp
When: Day 4 - Wednesday, May 25, 2016

Big data projects are becoming ever more prevalent across both industry and government. Unfortunately, initial implementations are often more difficult than anticipated and benefits more elusive than real. This presentation focuses on the three key facets of all big data projects: problems, people, and technology. Understanding each is a big step towards a successful project for the big data rookie.

1. Big Data Problems: Does your organization have a big data problem? Big data means bringing together and analyzing large amounts of heterogeneous data to solve a decision maker’s problem. We discuss the attributes of big data problems and discuss strategies to clearly identify the customer’s problem. This is the first step in a successful project.

2. Big Data People - Big data projects are highly dependent on the skills of the project team. This includes domain experts, data scientists and the technical staff. The difficulty is bringing together the smallest team with the skills required to cover all tasks. People resources are scarce and expensive. We outline the makeup of an ideal big data team to guide you in selecting the right people with the right skills.

3. Big Data Technologies - Big data is not one software or even one technology. It is a quickly evolving ecosystem that can seem impenetrable to rookies. We show how to partition the scores of products into related functional groups that can together deliver value to customers.

Overall, this presentation strives to provide valuable insight to the big data rookie preparing for their first enterprise big data project. Insights are presented from multiple project stakeholder perspectives and center on the three key facets of a big data project: problems, people, and technology.