Analytics and Data Summit 2018

One of the biggest ongoing discussion points, and in fact a key decision factor to be bedded down prior to implementing a BI, Analytics application is whether it should be implemented as an on premises system, or as a cloud solution. We have come fairly quickly from a place where we had hardware on raised pallets in dark corners of basement floors. By contrast, we are now in the place where as far as possible, the business attempts to give the individual user access to self-served information on their personal device, at any time. The analogy I often use for this is one where my Grandfather one day clung to one end of a firmly planted Tulip and said to me; “ Look how strong I am, I have the world on the other end of this!” The internet used to be the domain of the few, and now it is almost impossible for an individual to function without it. In this discussion I will cover some fairly weighty topics, but in plain ‘ol English! This discussion is for Senior Executives in Finance or IT.

The International Production Assessment Division (IPAD) of the USDA’s Foreign Agricultural Service predicts two of the leading economic indicators: Global Agricultural Output and US Agricultural Output.
The Division uses a convergence of evidence approach that incorporates observation and ground truth but is also heavily dependent on remotely sensed satellite (raster) data.
IPAD’s approach has been to unpack rasters and store them as vectors in database rows and columns and then to create derivative products. Decades of product development were built on this model.
Vectorizing rasters is slow and wasteful. With pixel sizes decreasing from 25 km to 10 km for IPAD's main data streams in 2018, data size and CPU usage are expected to grow by a factor of 2.5.
IPAD will stop preparing rolled up answers to questions that may never be asked. This presentation will focus on the use of Oracle technologies including the native SDO_GEORASTER type, Columnar In Memory, and the Exadata.

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.

Essbase is finally in the cloud! So should you consider migrating to the cloud? Join us for the session where we will introduce and demo Essbase cloud services. We will show you all the features and functions available in Oracle Analytics Cloud, show you what is the same between on-prem and the cloud and what is different. We will review how the steps to migrate your Essbase applications to the cloud and what roadblocks and pitfalls to look out for. We will then show you how to maintain your Essbase applications in the cloud. - dimension builds, data integrations, automations, and more. Come to the session to learn when and why migrating to the cloud may make sense for you.

This presentation focuses on unlocking the power of Data Science for data-driven decision support. It details the pragmatics of using Machine Learning techniques in OBIEE for actionable BI and Predictive Analytics from a business standpoint. Two industry use cases are presented to illustrate the implementation of the same using OBIEE 12c.

Organizations are managing greater amounts of information from different sources and countries, and face complex privacy and data protection requirements. The European Union has introduced a sweeping General Data Protection Regulation (GDPR). As of May 2018, GDPR will enforce new accountability obligations and restrictions on international data flows affecting all organizations offering goods or services to EU residents.

GDPR SMART is an Oracle Consulting solution designed to help organizations address and mitigate potential risks associated with data processing activities. GDPR SMART is a graph-enabled platform that identifies all user Personal Information stored in their systems; automatically categorizes existing data sets; and analyzes potential risks inherent in these data. We will show how GDPR SMART supports the 2018 mandate. We will demo its rich functionality using Oracle Big Data Spatial and Graph technologies, with Big/Fast Data processing, NLP and machine learning.

Measure Processes, Manage Feedback, Link to Process, Drill to detail, From Insight to Action…
You've heard of all this before, but it is hardly ever completely implemented. The steps from Insight to Action are hard to capture with Action Links as we try to do with Business Intelligence. But when you use the capabilities of platforms such as BICS and PCS the implementation and adjustments can be very easily accomplished. You can even empower your business users to adjust the solution themselves. Creating BPM / BAM / BI solutions can now be done with webbased tools only that appear like low-code solutions. Can you use this to empower the business to stay connected and stay on track with your ever changing environment?
We will set out a few steps to gather the right input and to stay flexible with your integrated Business solution. The demo includes integrations between BICS and PCS that are the cornerstones for digitally empowered business by using self service as the starting point.

With data volumes exploding and a greater variety of data available,business users want to explore more data and discover new insights that they can apply readily to improve business strategies, operations and customer engagement.With easier data exploration,users are seeking to increase the depth and frequency of their data analysis.This is a significant change because users who engage in analytics processes interact with data differently from what has been the norm with traditional BI.Rather than just consume data,they ask questions,try different views and approaches,build predictive models, and more.Supporting users’ forays into analytics is critical because it’s becoming clear in nearly every industry that organizations need to be more analytical to compete effectively.Visual analytics can help users become more productive with data by using software to integrate data analysis capabilities with modern,graphical ways of expressing information.Such technologies give users more power. This study that examines experiences with BI, visual analytics, and visual data discovery to uncover how organizations can move forward to make users more productive with data and use technologies to improve collaboration. This study explores where users are succeeding with BI and analytics and where visual analytics can improve their decisions. Currently, users are not fully satisfied with their ability to use visual analytics functionality. Training and education are needed to help them understand how to use visualization effectively and exploit new methods of data analysis. 

Oracle Data Visualization (DV) and Oracle Analytics Cloud (OAC) include powerful features to gain insights from spatial and location-based information. This session will first review the built-in spatial and mapping capabilities of DV and OAC. We will then cover techniques to extend these built-in capabilities with additional spatial analytics and mapping using using features of Oracle Spatial and Graph in Oracle Database Cloud Service.