Analytics and Data Summit 2018

As early as 2001 Enterprise Data Warehousing (EDW) design patterns like "Corporate Information Factory" (CIF) began to emerge. Theses patterns established EDW as the central focus of reporting. Current BI/DW 1.0 projects still follow these patterns today. Problems in the BI/DW 1.0 methodology have appeared. Increases in data volume, variety and velocity have all created considerable challenges for this legacy architecture. In this presentation we will review the legacy of BI/DW 1.0 and dive into the future BI/DW 2.0 and 3.0 architectures. Taking a close look and advanced staging areas, operational data stores and how those architectures can be used for cloud facilitation in BI/DW 2.0. Additionally, this presentation will drive into the BI/DW 3.0 data tipping point and where various Oracle products fit in these new emerging modern data architectures.

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.

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!