Analytics and Data Summit 2018

Oracle recently expanded its Data Management Cloud portfolio with the addition of the Oracle Autonomous Data Warehouse Cloud Service to help customers and partners with the deployment of data-mart or data warehouse environments to gain faster insights from their critical business data. Oracle Autonomous Data Warehouse Cloud is the first of many cloud services built on the “self-driving” Oracle Autonomous Cloud Database technology. This service is integrated with applied machine learning to deliver unmatched high performance, reliability, and instant elasticity.
Oracle Autonomous Data Warehouse Cloud uses the same Oracle Database software and technology found in existing on-premises data warehouse deployment, and is compatible with Oracle’s in-database machine learning algorithms, analytics and BI tools, as well as popular 3rd party offerings. Oracle Autonomous Data Warehouse Cloud is simple to deploy, enabling traditional data mart environments or new monetization use cases.\

With the drastic rise in cloud offerings from Oracle, developers and users are scrambling to integrate data from on-premise and cloud solutions. This can range from small file transfers containing financial data to solutions for tools like Essbase Cloud Services, to large data sets containing millions of records sourced from a data warehouse loaded into Oracle Analytics Cloud (OAC). We also find ourselves integrating across cloud applications (for example, sourcing data from financial systems for reporting and analytics in other cloud tools). This presentation focuses on the gears that move the data, and presents an array of options and best practices to manage data integration and data movement. Come learn about a variety of methodologies available, as well as a cross-product overview. Finally, hear about real world examples, and how data integration actually works with various Oracle cloud products.

Lending Club’s Big Data Analytics platform is going through a major transformation to adopt the Lambda Architecture with Real-Time reporting and execution of AI/ML models on Real-Time data. Lending Club's OLTP platform is transitioning to a Microservice-based architecture. At the heart of both solutions is GoldenGate for BigData. We are using a single server configured to run the replicats serving JSON payloads and Avro formats using same set of trail files. We implemented a custom java replicat to stream JSON messages to AWS Kinesis. We are using HDFS handler to stream data in Avro format to HDFS and AWS S3 to be consumed by AWS EMR, Hive on Tez/Presto/Spark. The solutions have been architected in a secure, reliable, and resilient manner.

Join Oracle Engineering to hear real world use cases of how Oracle Customers have utilized Data Integration Platform Cloud – Governance Edition, DIPC-GE, as the foundation for data governance across their big data enterprise. This will include use case patterns, known pitfalls, as well as tips and tricks for future proofing your data governance investment. Oracle Engineering will review how our customers have utilized DIPC-GE to provide a proactive, trusted big data platform, which enables collaboration and enforces compliance across the enterprise. At the core of DIPC-GE is the data catalog which is used to create comprehensive catalog of data entities as well as business terms. The data catalog enables many advanced use cases within data governance, such as; data classification, data quality insights, data profiling, data lineage, impact analysis, AI/ML linkage of data assets to a business glossary, all with rich collaboration and built in flexible workflows and auditing. Join us!