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.\

This session answers architecture questions related to the overall structure and strategy for an enterprise analytics system. How do we design a data warehouse for analytics purposes? What do we integrate into a central warehouse or maintain in separate data marts? How do we integrate long term storage systems that we need to query only occasionally? Data lakes? Big Data?? What are the tradeoffs with different tools and how much do we invest in custom code? How do we integrate real-time data streaming? What ETL and integration strategies are we going to use? Where and how do we extend our raw data with calculated measures and analytic functions? How do we create a system that has a strong foundation, but can grow and evolve over time? This presentation will draw from real-world data architecture projects that were designed with analytics in mind.

Oracle Database In-Memory introduces a new in-memory columnar format that is compatible with all existing applications. Join Oracle Product Management to learn in detail what motivated Oracle to develop this new technology and how it works alongside the traditional row format to provide a unique “dual format” architecture. This session will explore how Database In-Memory enables "Real-Time Analytics" by allowing analytic style queries to be run directly on source data. It will also explore the key performance enhancing features of Database In-Memory including in-memory scans, predicate push down, hash joins with bloom filters, vector group by aggregation, and new high-performance features like In-Memory Expressions and Join Groups. The session will conclude by exploring how the new in-memory functionality interacts with key database performance features such as Real Application Clusters (RAC), Partitioning, parallel execution, and much more.

Analytic workloads are dominated by joins, aggregations, and scans. In-Memory columnar databases have optimized scans using compressed data formats and SIMD vectorization techniques, but have made little impact to the rest of the query execution plan. The Oracle Database In-Memory (DBIM) Option introduced new SQL execution operators that accelerate analytic queries by optimizing aggregation over joins for star schemas. Group-by expressions are pushed down into the scans of dimension tables, creating a unique key per distinct group called a Dense Grouping Key (DGK). A Key Vector is allocated that maps join keys to DGKs, which is used to filter non-matching rows during the fact table scan. Passing rows are then aggregated directly on compressed codes into DGK-indexed result buffers using SIMD. Our solution replaces traditional join and group-by processing (bloom filters, hash table build/probe, etc) with blazing fast inlined scan operators, improving query elapsed time by as much as 10X.

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.

This presentation will cover the process of resolving performance issues in OBIEE 12c. We will explain how to analyze poorly performing reports and dashboards. How to view the sql behind poorly performing analytics and dashboards. Explain the process implementing aggregate tables to improve performance.

Oracle Database recently switched to new annual Release Model with Oracle Database 18c the first annual release in the new model. This session is a unique opportunity to get ahead of the curve and learn what's new in Oracle Database 18c directly from the Oracle Database development team.

There is a long list of products and services, but what do I need for Analytics? Is it just the Cloud service? Can I simply connect everything? Let's get to the bottom of this. Let’s get a holistic view on the infrastructure for hybrid cloud analytics. These topics are based on an onshore/offshore industry company moving it's analytics to the cloud, while having to deal with offshore locations as well.
This session will elaborate on how Analytics Cloud, RDC, VPN, GoldenGate, Data Integrator, ETL, FastConnect, Internet Exchanges, your ISP and datacenters are related to each other. 
The case study is a datawarehouse and analytics platform in the Oracle Cloud connecting to on-premises sources. The analytics-to-the-cloud first approach is often a great start in the cloud, but at that time you need to think beyond running queries, offloading the ETL-load and moving BI users to the Cloud.
We will mind the gap and compare the upside and downside of different infrastructural approaches.

So you want to use Oracle Business Intelligence but your organization doesn't have an Oracle Database, or maybe you do but most of your data sources are stored in a warehouse such as Redshift or Snowflake.

At first glance it might seem that Oracle BI is no longer an option, but don't worry -- it is. In this presentation, we'll guide the audience through the nuanced complexity faced when installing a JDBC Driver for the purpose of connecting Oracle Business Intelligence to a database that isn't Oracle. While we use Redshift as an example, the shared insights will be helpful for anyone connecting Oracle BI to any warehouse or database.

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!

This session is given by Oracle's Global Leaders organization.  Attendance is limited and requires a full-day commitment, as material builds throughout the day.

See https://eventreg.oracle.com/profile/web/index.cfm?PKwebID=0x519423abcd to sign up.

Join Cemil Alper, Consulting Member of Technical Staff, and Alexey Filanowisky, and more from Oracle Product Development at this in-depth workshop

In partnership with the Analytics and Data Summit, Global Leaders Program are offering a deeper dive full day class to Autonomous Data Warehouse Cloud. This class is open to all attendees of the A&D summit, and other approved registrants - contact Laura.j.mckechnie@oracle.com for further details and approval.

You will learn about Oracle's information management strategy in the Cloud, the different cloud services that are available in the information management space, with particular focus on the new Autonomous Data Warehouse Cloud Service (ADWC).

Content will cover a general architecture overview, various cloud service capabilities such as ADWC, Big Data Cloud Service (BDCS), Data Integration Platform Cloud (DIPC) and Oracle Analytics Cloud, and how to migrate existing environments to the Oracle Cloud Platform.

Finally, life on the cloud and how things change will be discussed.  

Supporting Your Needs
As this workshop aims to support your needs, you may be asked to complete a short survey about your current Oracle environment and workloads. If so, this survey will be sent via email following your registration.  

PZU is the largest financial institution in Central and Eastern Europe and the leader in Polish insurance market.  According to the new strategy, focuses on the growth through use of the latest technological achievements, such as process automation and artificial intelligence. Foundation for this is an efficient and modern Data Warehouse, which provides information about clients and processes taking place within          the company. For this purpose, the insurer undertook a migration project of current SAS SPDS solution to an innovative product - Exadata Database Machine. Thanks to collaboration of specialists from SAS and Oracle, migration to a new environment composed of the SAS Grid analytical platform and Exadata Database Machine, is possible. The migration process is a big challenge, but necessary to guarantee PZU's success in the future.

Oracle Database In-Memory is one of the most fascinating new database features in a long time, promising an incredible performance boast for analytics. This presentation provides a step-by-step guide on when and where you should take advantage of Database In-Memory, as well as outlining strategies to help you ensure you get the promised performance boast regardless of your database environments. These strategies include how to identify which objects to populate into memory, how to identify which indexes to drop, and details on how to integrate with other performance enhancing features. With easy-to-follow real-world examples, this presentation explains exactly what steps you need to take to get up and running on Oracle Database In-Memory.