Wednesday Feb 03, 2016

Links to Presentations: BIWA Summit'16 - Big Data + Analytics User Conference Jan 26-28, @ Oracle HQ Conference Center

We had a great www.biwasummit.org event with ~425 attendees, in depth technical presentations delivered by experts and even had several 2 hour Hands on Labs training classes that used the Oracle Database Cloud!  Watch for more coverage of event in various Oracle marketing and partner content venues.

Many thanks to all the BIWA board of directors and many volunteers who have put in so much work to make this BIWA Summit the best BIWA user event ever.  Mark your calendars for BIWA Summit’17, January 31, Feb. 1 & Feb. 2, 2017.  We’ll be announcing Call for Abstracts in the future, so please direct your best customers and speakers to submit.  We’re aiming to continue to make BIWA + Spatial + YesSQL Summit the best focused user gathering for sharing best practices for novel and interesting use cases of Oracle technologies.

BIWA is an IOUG SIG run by entirely by customers, partners and Oracle employee volunteers.  We’re always looking for people who would like to be involved.  Let me know if you’d like to contribute to the planning and organization of future BIWA events and activities.

See everyone at BIWA’17!

Charlie, on behalf of the entire BIWA board of directors  (charlie.berger@oracle.com)

(see www.biwasummit.org for more information)

See List of BIWA Summit'16 Presentations below.  Click on Details to access the speaker’s abstract and download the files (assuming the speaker has posted them for sharing).

We now have a schedule at a glance to show you all the sessions in a tabular agenda.

BIWASummit2016Tue.png

See bottom of page for the Session Search capability

Below is a list of the sessions and links to download most of the materials for the various sessions.  Click on the DETAILS button next to the session you want to download, then the page should refresh with the session description and (assuming the presenter uploaded files, but be aware that files may be limited to 5MB) you should see a list of files for that session.  See the full list below:

Advanced Analytics

Presentations (Click on Details to access file if submitted by presenter)

Dogfooding – How Oracle Uses Oracle Advanced Analytics To Boost Sales Efficiency

Details

Oracle Modern Manufacturing - Bridging IoT, Big Data Analytics and ERP for Better Results

Details

Predictive Modelling and Forecasting using OER

Details

Enabling Clorox as Data Driven Enterprise

Details

Fault Detection using Advanced Analytics at CERN's Large Hadron Collider: Too Hot or Too Cold

Details

Large Scale Machine Learning with Big Data SQL, Hadoop and Spark

Details

Stubhub and Oracle Advanced Analytics

Details

Fiserv Case Study: Using Oracle Advanced Analytics for Fraud Detection in Online Payments

Details

Advanced Analytics for Call Center Operations

Details

Machine Learning on Streaming Data via Integration of Oracle R Enterprise and Oracle Stream Explorer

Details

Learn Predictive Analytics in 2 hours!! Oracle Data Miner 4.0 Hands on Lab

Details

Scaling R to New Heights with Oracle Database

Details

Predictive Analytics using SQL and PL/SQL

Details

Big Data Analytics with Oracle Advanced Analytics 12c and Big Data SQL and the Cloud

Details

Improving Predictive Model Development Time with R and Oracle Big Data Discovery

Details

Oracle R Enterprise 1.5 - Hot new features!

Details

Is Oracle SQL the best language for Statistics

Details

BI and Visualization

Presentations (Click on Details to access file if submitted by presenter)

Electoral fraud location in Brazilian General Elections 2014

Details

The State of BI

Details

Case Study of Improving BI Apps and OBIEE Performance

Details

Preparing for BI 12c Upgrade

Details

Data Visualization at Sound Exchange – a Case Study

Details

Integrating OBIEE and Essbase, Why it Makes Sense

Details

The Dash that changed a culture

Details

Optimize Oracle Business Intelligence Analytics with Oracle 12c In-Memory Database option

Details

Oracle Data Visualization vs. Answers: The Cage Match

Details

What's New With Oracle Business Intelligence 12c

Details

Workforce Analytics Leveraging Oracle Business Intelligence Cloud Serivces (BICS)

Details

Defining a Roadmap for Migrating to Oracle BI Applications on ODI

Details

See What’s There and What’s Coming with BICS & Data Visualization

Details

Free form Data Visualization, Mashup BI and Advanced Analytics with BI 12c

Details

Oracle Data Visualization Cloud Service Hands-On Lab with Customer Use Cases

Details

On Metadata, Mashups and the Future of Enterprise BI

Details

OBIEE 12c and the Leap Forward in Lifecycle Management

Details

Supercharge BI Delivery with Continuous Integration

Details

Visual Analyzer and Best Practices for Data Discovery

Details

BI Movie Magic: Maps, Graphs, and BI Dashboards at AMC Theatres

Details

Oracle Business Intelligence (OBIEE) the Smart View Way

Details

Big Data

Presentations (Click on Details to access file if submitted by presenter)

Oracle Big Data: Strategy and Roadmap

Details

Oracle Modern Manufacturing - Bridging IoT, Big Data Analytics and ERP for Better Results

Details

Leveraging Oracle Big Data Discovery to Master CERN’s Control Data

Details

Enrich, Transform and Analyse Big Data using Big Data Discovery and Visual Analyzer

Details

Oracle Big Data SQL: Unified SQL Analysis Across the Big Data Platform

Details

High Speed Video Processing for Big Data Applications

Details

Enterprise Data Hub with Oracle Exadata and Oracle Big Data Appliance

Details

How to choose between Hadoop, NoSQL or Oracle Database

Details

Analytical SQL in the Era of Big Data

Details

Cloud Computing

Presentations (Click on Details to access file if submitted by presenter)

Oracle DBaaS Migration Road Map

Details

Centralizing Spatial Data Management with Oracle Cloud Databases

Details

End Users data in BI - Data Mashup and Data Blending with BICS , DVCS and BI 12c

Details

Oracle BI Tools on the Cloud--On Premise vs. Hosted vs. Oracle Cloud

Details

Hybrid Cloud Using Oracle DBaaS: How the Italian Workers Comp Authority Uses Graph Technology

Details

Build Your Cloud with Oracle Engineered Systems

Details

Safe Passage to the CLOUD – Analytics

Details

Your Journey to the Cloud : From Dedicated Physical Infrastructure to Cloud Bursting

Details

Data Warehousing and ETL

Presentations (Click on Details to access file if submitted by presenter)

Getting to grips with SQL Pattern Matching

Details

Making SQL Great Again (SQL is Huuuuuuuuuuuuuuuge!)

Details

Controlling Execution Plans (without Touching the Code)

Details

Taking Full Advantage of the PL/SQL Result Cache

Details

Taking Full Advantage of the PL/SQL Compiler

Details

Advanced SQL: Working with JSON Data

Details

Oracle Database In-Memory Option Boot Camp: Everything You Need to Know

Details

Best Practices for Getting Started With Oracle Database In-Memory

Details

Extreme Data Warehouse Performance with Oracle Exadata

Details

Real-Time SQL Monitoring in Oracle Database 12c

Details

A Walk Through the Kimball ETL Subsystems with Oracle Data Integration

Details

MySQL 5.7 Performance: More Than 1.6M SQL Queries per Second

Details

Implement storage tiering in Data warehouse with Oracle Automatic Data Optimization

Details

Edition-Based Redefinition Case Study

Details

12-Step SQL Tuning Method

Details

Where's Waldo? Using a brute-force approach to find an Execution Plan the CBO hides

Details

Delivering an Enterprise-Wide Standard Chart of Accounts at GE with Oracle DRM

Details

Agile Data Engineering: Introduction to Data Vault Data Modeling

Details

Worst Practice in Data Warehouse Design

Details

Same SQL Plan, Different Performance

Details

Why Use PL/SQL?

Details

Transforming one table to another: SQL or PL/SQL?

Details

Understanding the 10053 Trace

Details

Analytic Views - Bringing Star Queries into the Twenty-First Century

Details

The Place of SQL in the Hybrid World

Details

The Next Generation of the Oracle Optimizer

Details

Internet of Things

Presentations (Click on Details to access file if submitted by presenter)

Oracle Modern Manufacturing - Bridging IoT, Big Data Analytics and ERP for Better Results

Details

Meet Your Digital Twin

Details

Industrial IoT and Machine Learning - Making Wind Energy Cost Competitive

Details

Fault Detection using Advanced Analytics at CERN's Large Hadron Collider: Too Hot or Too Cold

Details

Big Data and the Internet of Things in 2016: Beyond the Hype

Details

IoT for Big Machines

Details

The State of Internet of Things (IoT)

Details

Oracle Spatial Summit

Presentations (Click on Details to access file if submitted by presenter)

Build Your Own Maps with the Big Data Discovery Custom Visualization Component

Details

Massively Parallel Calculation of Catchment Areas in Retail

Details

Dismantling Criminal Networks with Graph and Spatial Visualization and Analysis

Details

Best Practices for Developing Geospatial Apps for the Cloud

Details

Map Visualization in Analytic Apps in the Cloud, On-Premise, and Mobile

Details

Best Practices, Tips and Tricks with Oracle Spatial and Graph

Details

Delivering Smarter Spatial Data Management within Ordnance Survey, UK

Details

Deploying a Linked Data Service at the Italian National Institute of Statistics

Details

ATLAS - Utilizing Oracle Spatial and Graph with Esri for Pipeline GIS and Linear Asset Management

Details

Oracle Spatial 12c as an Applied Science for Solving Today's Real-World Engineering Problems

Details

Assembling a Large Scale Map for the Netherlands Using Oracle 12c Spatial and Graph

Details

Using Open Data Models to Rapidly Develop and Prototype a 3D National SDI in Bahrain

Details

Implementation of LBS services with Oracle Spatial and Graph and MapViewer in Zain Jordan

Details

Interactive map visualization of large datasets in analytic applications

Details

Gain Insight into Your Graph Data -- A hands on lab for Oracle Big Data Spatial and Graph

Details

Applying Spatial Analysis To Big Data

Details

Big Data Spatial: Location Intelligence, Geo-enrichment and Spatial Analytics

Details

What’s New with Spatial and Graph? Technologies to Better Understand Complex Relationships

Details

Graph Databases: A Social Network Analysis Use Case

Details

High Performance Raster Database Manipulation and Data Processing with Oracle Spatial and Graph

Details

3D Data Management - From Point Cloud to City Model

Details

The Power of Geospatial Visualization for Linear Assets Using Oracle Enterprise Asset Management

Details

Oracle Spatial and Graph: New Features for 12.2

Details

Fast, High Volume, Dynamic Vehicle Routing Framework for E-Commerce and Fleet Management

Details

Managing National Broadband Infrastructure at Turk Telekom with Oracle Spatial and Graph

Details

Other

Presentations (Click on Details to access file if submitted by presenter)

Taking Full Advantage of the PL/SQL Compiler

Details

Taking Full Advantage of the PL/SQL Result Cache

Details

Meet Your Digital Twin

Details

Making SQL Great Again (SQL is Huuuuuuuuuuuuuuuge!)

Details

Lightning Round for Vendors

Details


Sunday Jul 26, 2015

Big Data Analytics with Oracle Advanced Analytics: Making Big Data and Analytics Simple white paper

Big Data Analytics with Oracle Advanced Analytics:

Making Big Data and Analytics Simple

Oracle White Paper  |  July 2014 

Executive Summary:  Big Data Analytics with Oracle Advanced Analytics

(Click HERE to read entire Oracle white paper)   (Click HERE to watch YouTube video)

The era of “big data” and the “cloud” are driving companies to change.  Just to keep pace, they must learn new skills and implement new practices that leverage those new data sources and technologies.  Increasing customer expectations from sharing their digital exhaust with corporations in exchange for improved customer interactions and greater perceived value are pushing companies forward.  Big data and analytics offer the promise to satisfy these new requirements.  Cloud, competition, big data analytics and next-generation “predictive” applications are driving companies towards achieving new goals of delivering improved “actionable insights” and better outcomes.  Traditional BI & Analytics approaches don’t deliver these detailed predictive insights and simply can’t satisfy the emerging customer expectations in this new world order created by big data and the cloud.

Unfortunately, with big data, as the data grows and expands in the three V’s; velocity, volume and variety (data types), new problems emerge.  Data volumes grow and data becomes unmanageable and immovable.  Scalability, security, and information latency become new issues.  Dealing with unstructured data, sensor data and spatial data all introduce new data type complexities.  

Traditional advanced analytics has several information technology inherent weak points: data extracts and data movement, data duplication resulting in no single-source of truth, data security exposures, separate and many times, depending on the skills of the data analysts/scientists involved, multiple analytical tools (commercial and open source) and languages (SAS, R, SQL, Python, SPSS, etc.).  Problems become particularly egregious during a deployment phase when the worlds of data analysis and information management collide.   

Traditional data analysis typically starts with a representative sample or subset of the data that is exported to separate analytical servers and tools (SAS, R, Python, SPSS, etc.) that have been especially designed for statisticians and data scientists to analyze data.  The analytics they perform range from simple descriptive statistical analysis to advanced, predictive and prescriptive analytics.  If a data scientist builds a predictive model that is determined to be useful and valuable, then IT needs to be involved to figure out deployment and enterprise deployment and application integration issues become the next big challenge. The predictive model(s)—and all its associated data preparation and transformation steps—have to be somehow translated to SQL and recreated inside the database in order to apply the models and make predictions on the larger datasets maintained inside the data warehouse.  This model translation phase introduces tedious, time consuming and expensive manual coding steps from the original statistical language (SAS, R, and Python) into SQL.  DBAs and IT must somehow “productionize” these separate statistical models inside the database and/or data warehouse for distribution throughout the enterprise.  Some vendors will charge for specialized products and options for just for predictive model deployment.  This is where many advanced analytics projects fail.  Add Hadoop, sensor data, tweets, and expanding big data reservoirs and the entire “data to actionable insights” process becomes more challenging.  

Not with Oracle.  Oracle delivers a big data and analytics platform that eliminates the traditional extract, move, load, analyze, export, move load paradigm.  With Oracle Database 12c and the Oracle Advanced Analytics Option, big data management and big data analytics are designed into the data management platform from the beginning.  Oracle’s multiple decades of R&D investment in developing the industry’s leading data management platform, Oracle SQL, Big Data SQL, Oracle Exadata, Oracle Big Data Appliance and integration with open source R are seamlessly combined and integrated into a single platform—the Oracle Database.  

Oracle’s vision is a big data and analytic platform for the era of big data and cloud to:

  • Make big data and analytics simple (for any data size, on any computer infrastructure and any variety of data, in any combination) and

  • Make big data and analytics deployment simple (as a service, as a platform, as an application)

Oracle Advanced Analytics offers a wide library of powerful in-database algorithms and integration with open source R that together can solve a wide variety of business problems and can be accessed via SQL, R or GUI.  Oracle Advanced Analytics, an option to the Oracle Database Enterprise Edition 12c, extends the database into an enterprise-wide analytical platform for data-driven problems such as churn prediction, customer segmentation, fraud and anomaly detection, identifying cross-sell and up-sell opportunities, market basket analysis, and text mining and sentiment analysis.  Oracle Advanced Analytics empowers data analyst, data scientists and business analysts to more extract knowledge, discover new insights and make informed predictions—working directly with large data volumes in the Oracle Database.   

Data analysts/scientists have choice and flexibility in how they interact with Oracle Advanced Analytics.  Oracle Data Miner is an Oracle SQL Developer extension designed for data analysts that provides an easy to use “drag and drop” workflow GUI to the Oracle Advanced Analytics SQL data mining functions (Oracle Data Mining).  Oracle SQL Developer is a free integrated development environment that simplifies the development and management of Oracle Database in both traditional and Cloud deployments. When Oracle Data Miner users are satisfied with their analytical methodologies, they can share their workflows with other analysts and/or generate SQL scripts to hand to their DBAs to accelerate model deployment.  Oracle Data Miner also provides a PL/SQL API for workflow scheduling and automation.  

R programmers and data scientists can use the familiar open source R statistical programming language console, RStudio or any IDE to work directly with data inside the database and leverage Oracle Advanced Analytics’ R integration with the database (Oracle R Enterprise).  Oracle Advanced Analytics’ Oracle R Enterprise provides transparent SQL to R translation to equivalent SQL and Oracle Data Mining functions for in-database performance, parallelism, and scalability—this making R ready for the enterprise.  

Application developers, using the ODM SQL data mining functions and ORE R integration can build completely automated predictive analytic solutions that leverage the strengths of the database and the flexibly of R to integrate Oracle Advanced Analytics analytical solutions into BI dashboards and enterprise applications.

By integrating big data management and big data analytics into the same powerful Oracle Database 12c data management platform, Oracle eliminates data movement, reduces total cost of ownership and delivers the fastest way to deliver enterprise-wide predictive analytics solutions and applications.  

(Click HERE to read entire Oracle white paper)

Wednesday Aug 06, 2014

New Book: Predictive Analytics Using Oracle Data Miner


Great New Book Now Available:  Predictive Analytics Using Oracle Data Miner, by Brendan Tierney, Oracle ACE Director

If you have an Oracle Database and want to leverage that data to discover new insights, make predictions and generate actionable insights, this book is a must read for you!  In Predictive Analytics Using Oracle Data Miner: Develop & Use Oracle Data Mining Models in Oracle Data Miner, SQL & PL/SQL, Brendan Tierney, Oracle ACE Director and data mining expert, guides the user through the basic concepts of data mining and offers step by step instructions for solving data-driven problems using SQL Developer’s Oracle Data Mining extension.  Brendan takes it full circle by showing the reader how to deploy advanced analytical methodologies and predictive models immediately into enterprise-wide production environments using the in-database SQL and PL/SQL functionality.  

Definitely a must read for any Oracle data professional!

See Predictive Analytics Using Oracle Data Miner, by Brendan Tierney on Amazon.com  



Tuesday May 06, 2014

Oracle Data Miner 4.0/SQLDEV 4.0 New Features - Watch Demo!

Oracle Data Miner 4.0 New Features 

Oracle Data Miner/SQLDEV 4.0 (for Oracle Database 11g and 12c)

  • New Graph node (box, scatter, bar, histograms)
  • SQL Query node + integration of R scripts
  • Automatic SQL script generation for deployment

Oracle Advanced Analytics 12c New SQL data mining algorithms/enhancements features exposed in Oracle Data Miner 4.0

  • Expectation Maximization Clustering algorithm
  • PCA & Singular Vector Decomposition algorithms
  • Decision Trees can also now mine unstructured data
  • Improved/automated Text Mining, Prediction Details and other algorithm improvements
  • SQL Predictive Queries—automatic build, apply within simple yet powerful SQL query


Friday Mar 23, 2012

NEW 2-Day Instructor Led Course on Oracle Data Mining Now Available!

A NEW 2-Day Instructor Led Course on Oracle Data Mining has been developed for customers and anyone wanting to learn more about data mining, predictive analytics and knowledge discovery inside the Oracle Database.  To register interest in attending the class, click here and submit your preferred format.

Course Objectives:

  • Explain basic data mining concepts and describe the benefits of predictive analysis
  • Understand primary data mining tasks, and describe the key steps of a data mining process
  • Use the Oracle Data Miner to build,evaluate, and apply multiple data mining models
  • Use Oracle Data Mining's predictions and insights to address many kinds of business problems, including: Predict individual behavior, Predict values, Find co-occurring events
  • Learn how to deploy data mining results for real-time access by end-users

Five reasons why you should attend this 2 day Oracle Data Mining Oracle University course. With Oracle Data Mining, a component of the Oracle Advanced Analytics Option, you will learn to gain insight and foresight to:

  • Go beyond simple BI and dashboards about the past. This course will teach you about "data mining" and "predictive analytics", analytical techniques that can provide huge competitive advantage
  • Take advantage of your data and investment in Oracle technology
  • Leverage all the data in your data warehouse, customer data, service data, sales data, customer comments and other unstructured data, point of sale (POS) data, to build and deploy predictive models throughout the enterprise.
  • Learn how to explore and understand your data and find patterns and relationships that were previously hidden
  • Focus on solving strategic challenges to the business, for example, targeting "best customers" with the right offer, identifying product bundles, detecting anomalies and potential fraud, finding natural customer segments and gaining customer insight.

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