Check out the presentations listed below.



Data Streaming and Analytic Microservices
Stewart Bryson , Red Pill Analytics
Topic: Data Warehousing & Big Data - Subtopic: Data Architecture

While traditional data warehouses excel at sourcing data from enterprise applications, they usually fail at handling the volume, velocity, and variety of data for modern analytics applications relying on big and fast data. Instead of modeling these data sources into a system that doesn't fit, let's apply a new software design pattern to analytics: microservices. Microservices are small, independent applications – building blocks that provide only a distinct subset of functionality – that can be stacked together to build an end-to-end platform.

In this presentation, we'll explore using Apache Kafka and the Confluent Platform 3.0 as the data streaming hub for ingesting data bound for downstream analytic applications: an enterprise data warehouse, a Hadoop cluster for batch processing, and lightweight, purpose-built microservices in the cloud or on-premises. Experience the next generation of analytic platforms.

Back to Top
Architecture Live: Designing an Analytics Platform for the Big Data Era
Jean-Pierre Dijcks , Oracle Corporation
Co-presenter(s): Stewart Bryson, Red Pill Analytics
Topic: Data Warehousing & Big Data - Subtopic: Data Architecture

Don't miss the Architecture Live experience! In this interactive session, you'll witness two industry experts digitally illustrating data-driven architectures live, with input and feedback from the audience.

Kafka, Lambda, and Streaming Analytics will be all covered. We’ll tell you what these words mean and more importantly how they affect the choices we make building an enterprise architecture. With the Oracle Information Management Reference Architecture as the backdrop, we'll clarify and delineate the different components involved in delivering big data, fast data, and all the gray area in between. The Architecture Live experience will be fun and different, and we'll all learn something along the way.

Back to Top
Things Every Oracle DBA Needs to Know About the Hadoop Ecosystem
Zohar Elkayam , Brillix-DBAces
Topic: Data Warehousing & Big Data - Subtopic: Other

Big data is one of the biggest buzzwords in today's market. Terms such as Hadoop, HDFS, YARN, Sqoop, and non-structured data have been scaring DBAs since 2010, but where does the DBA team really fit in?

In this session, we will discuss everything database administrators and database developers need to know about big data. We will demystify the Hadoop ecosystem and explore the different components. We will learn how HDFS and MapReduce are changing the data world and where traditional databases fit into the grand scheme of things. We will also talk about why DBAs are the perfect candidates to transition into big data and Hadoop professionals and experts.

Back to Top
Analytic Views: A New Type of Database View for BI and Data Warehousing
William Endress , Oracle Corporation
Topic: Data Warehousing & Big Data - Subtopic: Data Modeling

Analytic views are a new type of view in Oracle Database 12c Release 2 that organize data for simplified access via SQL, extend data sets with aggregate data and measure calculations, and provide a rich metadata layer to support BI applications. In this session, learn how analytic views embed joins and aggregation rules, and measure calculations and navigation paths into a single view that is queried with very simple SQL. Use cases include simplifying access to data star schema, Oracle Big Data SQL, and JavaScript Object Notation and as an alternative to exporting data for the analysis in spreadsheets.

This session will be of particular interest to data warehouse architectures and developers and Business Intelligence application developers.

Back to Top
The Hybrid World – RDBMS + Hadoop
Kerry Osborne , Accenture Enkitec Group
Topic: Data Warehousing & Big Data - Subtopic: Data Architecture

The hybrid world is coming! There is no doubt that hadoop has established a foothold in traditional enterprises by now. On the other hand, the well-established RDBMS products are far from dead. One of the major problems with hadoop is that the native open source SQL engines are just not as capable as the traditional RDBMS engines. That’s understandable since the traditional RDBMS guys have a 20+ year head start. Oracle for example is the king of the hill with regards to complex transactional systems and has the most powerful SQL engine on the planet. What that means is that moving an application to hadoop generally requires a major effort to re-write the data access layer (i.e. the SQL). Nevertheless, the power and the scalability of the distributed hadoop architecture are undeniable. So why not use the best of both worlds? The combination of the two can create a platform that combines the best of both architectures. This presentation will discuss approaches for building just such a hybrid platform. This presentation includes a case study showing a hybrid architecture combining Oracle and hadoop in an innovative use case that shows ankle bracelet tracking data with a google map interface.

Back to Top
Streaming #Election2016 with Oracle Data Integration
Michael Rainey , Gluent Inc
Topic: Data Warehousing & Big Data - Subtopic: Data Integration

Let’s take a look back at one of the more “interesting" election years in the history of the United States using data produced on that day. And not just any data, Twitter data using the #Election2016 hashtag. With so many different opinions being shared on social media, analysis of this data could provide insight into who might win the public vote. Working with open source technologies such as Logstash, Apache Kafka, and Spark Streaming, we can perform in-flight transformations to prepare the Twitter data for analysis. But what about relational data? Quite often we forget that products incubated in the Apache Foundation can also serve a purpose for “standard” relational databases, as well. Introducing Oracle GoldenGate and Oracle Data Integrator for Big Data. GoldenGate can extract relational data in real time and produce Kafka messages, ensuring relational data is a part of the enterprise data bus. These messages can then be ingested via ODI through a Spark Streaming process, integrated with additional data sources, such as other relational tables, flat files, etc, as needed, and finally published to one or more targets. Working through the setup, configuration and execution of the #Election2016 social media data experiment, this session will ensure attendees will walk away with a framework on which they can build their data streaming projects, combining relational data with big data and using a common, structured approach via the Oracle Data Integration product stack. And hopefully they take away some “interesting" insight into Election Day 2016 on social media.

Back to Top
Making Smart Devices Even Smarter (Including iKettles) with Oracle Cloud and Oracle Big Data Discovery
Mark Rittman , Rittman
Topic: Data Warehousing & Big Data - Subtopic: Data Integration

My story about taking 11 hours to make a cup of tea with a WiFi kettle was a fun story that went viral around the world, but it was really a story about data, analytics, and the value in bringing these internet-connected devices together. In this session we'll look at how IoT devices can be connected together, their data streams combined and analyses in real-time, and insights gained via Oracle Big Data Discovery used to make these devices even smarter.

Back to Top
I Know Why the On-Premise Oracle BI Applications Sings: Migrating OBIA to the Cloud
Christian Screen , Datavail
Topic: Data Warehousing & Big Data - Subtopic: Data Architecture

Cloud solutions continue to expand into the mainstream with obvious material value for businesses that have historically focused on their on-premise solutions. With all major concerns for security in the cloud addressed by bank grade encryption, integration by REST APIs and other supported interfaces, and a growing base of supported production customers, the concerns are turning to action. But there are still lingering questions on architectural best practices and the general approach to move from on premise to the cloud especially for multi-tiered solutions such as Oracle BI Applications. Questions are now less about concern and more about how to move forward. How much of the on-premise software architecture can be migrated to the cloud? And, how can it be done with best practices with the least risk and exposure? And, while getting it right the first time? This session discusses best practice architecture for migrating the Oracle BI Applications to the cloud. It focuses on the Oracle cloud platform and database services, with a nod to infrastructure services, to lay out the idea of the hybrid cloud, and variations of the new age cloud BI/DW architecture for your analytics environment to succeed while operating at the same reliability or better all the while benefiting from what the cloud offers best.

Back to Top