Many organizations now understand relational databases are not optimized at integrating highly variable data from many sources. They were simply not designed for the task. Today, there are a confusing array of non-relational technology options available. You could choose a file system (like the Hadoop file system HDFS) and build a Data Lake. Or you could choose from a number of non-relational database types and options to build an operational Data Hub. What are the differences? What are the pros and cons? In this presentation, Dan McCreary will review these integration strategies and help you decide which one is right for you.

About Dan McCreary
Dan is an enterprise data architect with a focus on NoSQL database architectures. He's worked at Bell Labs and Steve Jobs's NeXT Computer as well as founding his own consulting firm of over 75 people. His interests include topics such as distributed computing, programming languages, databases and XML standards. He has published articles on the semantic web, metadata registries, US Federal XML standards, XForms, XQuery and XRX. He is co-founder of the "NoSQL Now!" conference and is a co-author of the book "Making Sense of NoSQL" by Manning Publications. Dan was also a Principal Consultant for MarkLogic for 2.5 years. Dan is currently an independent consultant with a focus on AI and natural language query front-ends to Data Hubs.

As long as there has been data, there has been metadata. It is the critical component that adds crucial business and technical context to information in order to effectively leverage it for business value. With the rapid advances in database technology in recent years, has metadata kept pace? Are there new methods for managing metadata for the vast range of new technologies currently available? Or do the traditional methods still apply? Join Donna Burbank as she discusses the latest trends in metadata technology and, most importantly, how these can be leveraged to provide value to your organization.

About Donna Burbank
Donna Burbank, is a recognized industry expert in information management with over 20 years of experience in data management, metadata management, and enterprise architecture. She currently is Managing Director of Global Data Strategy Ltd, an international data management consulting company. Her background is multi-faceted across consulting, product development, product management, brand strategy, marketing, and business leadership.

In the database design world we’ve had tools, notations, and methods to architect and design relational database solutions for multiple decades. But with the arrival of NoSQL databases and features, we’ve struggled with leveraging our current way of doing things with new database technologies.

So how does a great data professional survive the expansion of data technologies and cloud architectures? In this session Karen will walk us through her tips on delivering data governance, processes and modeling in a polyglot, hybrid solution world.

This session will include:
- Design Approaches
- Data Modeling & Design Support
- NoSQL extensions in Relational Database Systems
- Governance in a Schemaless Solution

About Karen Lopez
Karen Lopez is a Senior Project Manager and Architect at InfoAdvisors. She has 20+ years of experience in project and data management on large, multi-project programs. Karen is a popular speaker known for her highly interactive, practical and sometimes irreverent presentation style. She is a Microsoft SQL Server MVP, and she wants you to love your data.

The cloud is proving immensely useful to providing elastic, measurable, on-demand, self-service resources to organizations. The uptake has been phenomenal, continuing the biggest transformation that technology professionals will experience in their careers. Just about any software, including databases, can be placed in a public cloud these days by simply utilizing cloud resources as an extended data center. This may solve an immediate pressing problem, but the opportunities missed without true cloud integration are huge. Some relational databases have undergone significant cloud-related development in their latest releases.

Disruption vectors (criteria prominent in a cloud analytic database selection) will be discussed with a view to help the attendee select their cloud analytic database in 2017.

What Will Be Discussed:
– Data architecture for 2017
– Data platform selection in 2017
– Major criteria often overlooked in database selection
– Why a tight integration with the cloud is imperative (“born in the cloud”)

About William McKnight
William McKnight is President of McKnight Consulting Group. He is an internationally recognized authority in information management. His teams have won several best practice competitions for their implementations, and many of his clients have gone public with their success stories. His strategies form the information management plan for leading companies in various industries. William is author of several books including “Integrating Hadoop" and “Information Management: Strategies for Gaining a Competitive Advantage with Data." He has published over 25 white papers, and his blog has been syndicated for many years. William is a very popular speaker worldwide, having given well over 100 days of training on diverse data subjects such as NoSQL, Graph Databases, Data Governance, Data Architecture, Data Return on Investment, Agile Methodology, Organizational Change Management, and Master Data Management. William is a mentor in information for a startup accelerator, and taught at Santa Clara University, UC-Berkeley, and UC-Santa Cruz.

Which marriages in the village will last? Which chicken is the queen of the coop? How many crayons do you need to color a county map of Tennessee? What do all of these questions have in common? They're all graph problems. Graphs are simultaneously the most intuitive data structure and host to some of the most esoteric algorithms and properties most technology developers are likely to encounter. Given the increasing popularity of graph databases, a small investment in this important topic is timely. Come to this talk for a friendly and approachable introduction to graph theory, application, and implementation.

About Tim Berglund
Tim is a teacher, author, and technology leader with Confluent, where he serves as the Senior Director of Developer Experience. He can frequently be found speaking at conferences around the world. He is the co-presenter of various O’Reilly training videos on topics ranging from Git to Distributed Systems, and is the author of Gradle Beyond the Basics. He tweets as @tlberglund, blogs very occasionally at http://timberglund.com, is the co-host of the http://devrelrad.io podcast, and lives in Littleton, CO, USA with the wife of his youth and their youngest child, the other two having mostly grown up.

Relational data modeling has several weaknesses. It shreds the data in a business entity into multiple tables. Queries and views slow performance and complicate development. Sparse data is hard to represent in relational models. Complex relationships (such as networks and hierarchies of data) are hard to represent and are slow to query. Search is difficult, because data is shredded into tables deliberately to remove context. Document modeling combined with graph modeling solves these problems and creates a powerful new data modeling paradigm. In this session, Mike Bowers will show you how to do document-graph modeling.

About Mike Bowers
Michael Bowers is principal enterprise data architect at the LDS Church. He has spent over 20 years as an enterprise architect, software developer, and database architect. In 2008, Michael brought the MarkLogic NoSQL database to LDS. Today it delivers 1.8 TB of data to 95 million annual visitors with billions of page hits across 182 websites, transactional applications, and web services.