Analytics and Data Summit 2018

A leading cause of power outages in the US is weather driven equipment failure events. Oracle utility customers are seeking machine learning techniques (recommended by the USDOE) to improve real-time risk assessment for critical assets based upon incoming weather forecast. Given an accurate prediction for the location, type, and amount of the storm-damaged equipment, the utility company can position the right number of specialized crews and material resources ahead of time. We develop a novel machine-learning model trained on the history of asset failures and reported weather. Since the weather-reporting stations might be far from the assets and some weather data measurements might be missing, we interpolate the weather conditions at the asset locations using a triangularization function computed with a barycentric coordinates technique implementation. We report performance comparison of multiple machine learning models to recommend the best damage prediction tool.

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.

In this session, you will learn how DiLytics integrated Oracle Planning and Budgeting Cloud Service (PBCS) data into Oracle Analytics Cloud Service. DiLytics designed a Data Warehouse for Planning and Budgeting Analytics and developed a package to load data from Oracle Planning and Budgeting Cloud Service into the data warehouse. This enabled creation of metrics, KPIs and Dashboards in Oracle Analytics Cloud for extensive insight into the PBCS data. This empowered City of Oakland’s Financial Planning team to analyze budget details, actual spend, planned position details by job class, one-time and ongoing costs, Variance by department, etc. FP&A team is able to get insight into performance of planning process, effectiveness of budget, etc.

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.

You know you need to get started on that Oracle Business Intelligence upgrade from 11g to 12c so you do a “lift and shift” to the cloud, but IT resources are tight, plus you’re not really sure how everything is going to fit together and you are going to have to wait for the Database and Server Administrators to get the environments set up. No problem, just use your laptop or PC to pilot the entire migration using Virtual Box and Sample Applications. In no time you will be up and running, using the migration and baseline validation tools, connecting to your real data, verifying dashboards and running reports in 12c. Once that is taken care of you can proceed to the cloud. 
This is a case study of how Aleris International piloted its migration from OBIEE 11.1.1.7 to 12.2.1.1 using a laptop, Virtual Box and Sample applications for OBIEE.

Tektronix is a world-leading manufacturer of test and measurement equipment. Like many global organizations with complex business operations, the process of bringing together data resources for analysis is a challenging but critically important business function. Several business units at Tektronix used independent BI platforms, leading to integration challenges. A fast-track project run by Vlamis Software Solutions using Oracle Analytics Cloud (OAC) data visualizations consolidated these disparate systems into one modernized their business analytic platform. This all built upon the good work done in various departmental silos as well as their data warehouse and legacy OBIEE system. Come with your questions about how to balance the technology preferences of different functional user groups, how to evaluate the strengths and weaknesses of your current OBIEE implementation, and how to build momentum during a modernization initiative.