Oracle Analytics Cloud version 18.3.3 includes improvements and enhancements over the previous version. These enhancements are in areas such as data preparation, data visualization, data flows & data sources, and more.
While much of the news on Oracle Analytics has been about capabilities in the Oracle Analytics Cloud (OAC) service, Oracle Business Intelligence Enterprise Edition (OBIEE) has gained many new features in version 12.2.1.4, released in the past month or so. In this release are many features in the Data Visualization interface that have made their way into various releases of OAC, but are new to the on-premise release of OBIEE.
Oracle Analytics Cloud (OAC) provides a powerful tool to get insight from your data, wherever it is. This session will describe the many ways to get your data into OAC, from enterprise data sources all the way to the humble, but mighty CSV file.
In this session, we’ll show you how to use the automated tools in Oracle Analytics Cloud in order to create and visualize forecasts including confidence ranges, discrete forecasts, and back casting. We’ll share the “gotchas” we’ve uncovered utilizing exponential smoothing, ARIMA, and other automated tools in real-world enterprise implementations. We’ll also explain how to build predictive models using the included capabilities of Oracle Analytics Cloud and Data Visualization Desktop.
What can machine learning do and not do? We’ll discuss openly the natural tradeoffs that exist between different options for building advanced analytics capabilities in your business: outsource vs. inhouse, cloud vs on-premise, prepackaged analytics vs. opensource custom code.
The process of scientifically uncovering insights in complex data sets is one of the most exciting and compelling areas of visual analytics. Sankey graphs, parallel coordinates, radar graphs, and trellis charts all have the potential to reveal important patterns, relationships, and trends in highly dimensional data.
Data is king and IT and business struggle between one version of the truth and needing to add data into the system quickly for analysis purposes. While you may need validated data residing in a data warehouse, there is also a need for users to supplement this data on the fly. Successful analytics applications require the ability to mash up external data with data warehouse data.
OAC and Data Visualization Desktop 4.0 now include a huge set of machine learning processes and algorithms. We’ll demonstrate the new interface, explain which algorithms to use in which business cases, show how to interpret results, and review how to explain it all to nosy bosses and others who always want to know “just how does this thing work”.
What can machine learning do and not do? We’ll discuss openly the natural tradeoffs that exist between different options for building advanced analytics capabilities in your business: outsource vs. inhouse, cloud vs on-premise, prepackaged analytics vs. opensource custom code. You’ll learn what language you need to know, how to explain the common concepts of adaptive intelligence, and how to tie your experience to the new techniques and tools. You likely already know enough, you just need some guidance.
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??
The process of scientifically uncovering insights in complex data sets is one of the most exciting areas of Visual Analytics. You’ll see how to break down the steps in data exploration so that you discover key findings quickly, efficiently, and comprehensively. Showing and telling others your data stories use many of the same visualization tools and concepts, but the challenge is making this effective for different people with different backgrounds, skills, and abilities.
You have a significant investment in Oracle Business Intelligence Enterprise Edition (OBIEE). You hear from Oracle that you should move everything to Oracle Analytics Cloud (OAC). But what’s really involved in this migration? Why spend more money with Oracle to host an environment that you already have? And what benefits will you experience beyond just the benefits from moving to OBIEE 12c?
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