We had a great www.biwasummit.orgevent 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).

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

BI and Visualization

Big Data

Cloud Computing

Data Warehousing and ETL

Internet of Things

Oracle Spatial Summit

Other

Recently, I was asked by a friend and colleague, Chris Claterbos, Lecturer at University of Kansas' Business School, to deliver a guest lecture to his business analytics students.  

In preparation, so as to not make it an entirely Oracle "product" presentation, I tried to gather some general information on the big data + analytics market, job opportunities & careers and future musings about where the industry is headed.  I liked resulting presentation so am posting and sharing it here.  

U. Kansas Guest Lecture on Big Data Analytics with Oracle's Advanced Analytics, Big Data SQL and Cloud

• Big Data + Analytics “Phenomenon”
• Careers in Big Data Analytics
• Product
• Oracle Advanced Analytics Overview & Features/Benefits
• Brief Demos
• Example Customer References
• Applications “Powered by OAA”
• Getting Started
• Q & A

Enjoy!  Hopefully all you all become data'n'science stars!  

Charlie 

What you will learn:  This Predictive Analytics using Oracle Data Mining Ed 1 training will review the basic concepts of data mining. Expert Oracle University instructors will teach you how to leverage the predictive analytical power of Oracle Data Mining, a component of the Oracle Advanced Analytics option.

Learn To:

• 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, apply, and deploy multiple data mining models.
• Use Oracle Data Mining's predictions and insights to address many kinds of business problems.
• Deploy data mining models for end-user access, in batch or real-time, and within applications.

Benefits to You

When you've completed this course, you'll be able to use the Oracle Data Miner 4.1, the Oracle Data Mining "workflow" GUI, which enables data analysts to work directly with data inside the database. The Data Miner GUI provides intuitive tools that help you explore the data graphically, build and evaluate multiple data mining models, apply Oracle Data Mining models to new data, and deploy Oracle Data Mining's predictions and insights throughout the enterprise.

Oracle Data Miner's SQL APIs - Get Results in Real-Time

Oracle Data Miner's SQL APIs automatically mine Oracle data and deploy results in real-time. Because the data, models, and results remain in the Oracle Database, data movement is eliminated, security is maximized and information latency is minimized.

Introduction

• Course Objectives
• Suggested Course Prerequisites
• Suggested Course Schedule
• Class Sample Schemas
• Practice and Solutions Structure
• Review location of additional resources

Predictive Analytics and Data Mining Concepts

• What is the Predictive Analytics?
• Introducting the Oracle Advanced Analytics (OAA) Option?
• What is Data Mining?
• Why use Data Mining?
• Examples of Data Mining Applications
• Supervised Versus Unsupervised Learning
• Supported Data Mining Algorithms and Uses

Understanding the Data Mining Process

• Common Tasks in the Data Mining Process
• Introducing the SQL Developer interface

Introducing Oracle Data Miner 4.1

• Data mining with Oracle Database
• Setting up Oracle Data Miner
• Accessing the Data Miner GUI
• Identifying Data Miner interface components
• Examining Data Miner Nodes
• Previewing Data Miner Workflows

Using Classification Models

• Reviewing Classification Models
• Adding a Data Source to the Workflow
• Using the Data Source Wizard
• Using Explore and Graph Nodes
• Using the Column Filter Node
• Creating Classification Models
• Building the Models
• Examining Class Build Tabs

Using Regression Models

• Reviewing Regression Models
• Adding a Data Source to the Workflow
• Using the Data Source Wizard
• Performing Data Transformations
• Creating Regression Models
• Building the Models
• Comparing the Models
• Selecting a Model

Using Clustering Models

• Describing Algorithms used for Clustering Models
• Adding Data Sources to the Workflow
• Exploring Data for Patterns
• Defining and Building Clustering Models
• Comparing Model Results
• Selecting and Applying a Model
• Defining Output Format
• Examining Cluster Results

Performing Market Basket Analysis

• What is Market Basket Analysis?
• Reviewing Association Rules
• Creating a New Workflow
• Adding a Data Source to the Workflow
• Creating an Association Rules Model
• Defining Association Rules
• Building the Model
• Examining Test Results

Performing Anomaly Detection

• Reviewing the Model and Algorithm used for Anomaly Detection
• Adding Data Sources to the Workflow
• Creating the Model
• Building the Model
• Examining Test Results
• Applying the Model
• Evaluating Results

Mining Structured and Unstructured Data

• Dealing with Transactional Data
• Handling Aggregated (Nested) Data
• Joining and Filtering data
• Enabling mining of Text
• Examining Predictive Results

Using Predictive Queries

• What are Predictive Queries?
• Creating Predictive Queries
• Examining Predictive Results

Deploying Predictive models

• Requirements for deployment
• Deployment Options
• Examining Deployment Options

Part 1 (of a planned series of blog posts):  Here are a few of my favorite Oracle Data Miner demo workflows.  They all are simple, easy to create examples of data mining and predictive analytics using Oracle Advanced Analytics and SQL Developer's Oracle Data Miner extension.

CUST_INSUR_LTV

Oracle Data Miner ships with some small datasets to get users started including INSUR_CUST_LTV_SAMPLE (1,015 records).  While this tiny dataset doesn't bloat the SQL Developer download size and helps get Oracle Data Miner users quickly up and running, the data size is so small that the the resulting predictive models and insights can seem at times a bit trivial.  Hence, I prefer to use larger files that ship with the Oracle 12c Database Sample Examples (SH.schema, MINING_DATA_BUILD, etc.) and this CUST_INSUR_LTV demo data:  

CUST_INSUR_LTV.DMP (~25K records, ~25 attributes)  

CUST_INSUR_LTV_APPLY.DMP (~25K records, ~25 attributes)  

Predicting Insurance Buyers ODMr workflow

You can import the workflow and and datasets and everything should run.  

This workflow includes an Explore node and Graph node that are typically used to visualize the data before performing data mining.  The Explore node step is important to make sure the data you are about to analyze makes sense and seems accurate and reasonable.  For example, AGE should all be positive numbers and range from 0 to say 100+.

The Column Filter node performs data profiling and data quality checks on the data and is also used to perform an Attribute Importance analysis to determine which attributes (or input variables) have the largest correlation with the target attribute (Buy_Insurance).  Sometimes this step alone provides significant value to a company to better understand the key factors, but here, we're also using it to better understand which attributes have the most inpact on our business problem--targeting customers who are likley to buy insurance.  Note:  Each of the OAA/ODM algorithms have their own embedded attribute importance/feature selection capabilties and each can handle hundreds to thousands of input attributes.  However, many times we want to get a feel for what's driving our business problem and learn where we could focus to pull in additional attributes and "engineered features" e.g "AGE/INCOME ratio" or "Maximum_Amount" etc..  

We build four (4) Oracle Data Mining Classification models by default (Decision Tree, Naive Bayes, GLM Logistic Regression and Support Vector Machine (SVM)).  For simplicity, we accept the ODMr defaults for Data Preparation and Algorithm Settings and can be assured that with Oracle Data Miner default settings, we should achieve a "good predictive model".

Decision Trees generally produce good predictive models and have the added benefit of being easy to understand. Notice the IF.... THEN... rules.

Lastly, we use the Apply node and our Classification node to make predictions on our CUST_INSUR_LTV_APPLY table and get our predictions.  

The predictions and associated Prediction_Details are stored inside the Oracle Database and hence easily available for inclusion in any BI Dashboard or real-time application.  

Oracle Data Miner generates the PL/SQL and SQL scripts for accelerating deploying analytical methodologies that leverage the scalability and infrstructure of the Oracle Database.  See this Oracle Data Miner: Use Reposiitory APIs to Manage and Schedule Workflows to Run White Paper for more details on the many model deployment options. 

Hope you enjoy!

Charlie 

Thanks to a great and clever Oracle Gold Partner, Vlamis Software, you can now take a "test drive" of Oracle Advanced Analytics on the Oracle Cloud.  Simple, fast, easy--fun!

Oracle Advanced Analytics 12c delivers parallelized in-database implementations of data mining algorithms and integration with open source R. Data analysts use Oracle Data Miner GUI and R to build and evaluate predictive models and leverage R packages and graphs. Application developers deploy Oracle Advanced Analytics models using SQL data mining functions and R. With the Oracle Advanced Analytics option, Oracle extends the Oracle Database to an sclable analytical platform that mines more data and data types, eliminates data movement, and preserves security to anticipate customer behavior, detect patterns, and deliver actionable insights. 

Oracle Advanced Analytics, a combination of Oracle Data Mining and Oracle R Enterprise, delivers predictive analytics, data mining, text mining, statistical analysis, advanced numerical computations and interactive graphics inside the database. It brings powerful computations to the database resulting in dramatic improvements in information discovery, scalability, security, and savings. Data analysts, data scientists, statistical programmers, application developers and DBAs can develop and automate sophisticated analytical methodologies inside the database and gain competitive advantage.

And now you can try it for a Test Drive for free on the Oracle Cloud!

Oracle Advanced Analytics - Oracle Data Mining

The Advanced Analytics environment allows you to try using the Data Mining option of the Oracle Database against very large data sets. The database is hosted with Oracle's Database Cloud service. We also give you full SQL access to your very own Pluggable Database so that you may experiment as you wish.

Sign Up

Fill out the form. Select the environment you'd like to try, give Vlamis your name, work email address, phone number, and any comments or questions. Hit submit. You will get a confirmation email from the Vlamis web server. Vlamis will look your information over and send you an email with instructions on how to connect. Once you receive your email with connection information, your environment will be functional for 24 hours. Vlamis will also provide a PDF of lab materials for you to try. After a day or two, Vlamis will call you to see how you liked it.

Oracle Customer:Zagrebačka Bank (Zagrebačka banka d.d.)
Location:  Zagreb, Croatia
Industry:Financial Services
Employees:  4,500
Annual Revenue:  $1 to $5 Billion

Zagrebačka Bank (Zagrebačka banka d.d., ZABA) is the biggest bank in Croatia, one of the country’s largest employers, and part of the Italian Unicredit Group where it regularly belongs among the most profitable subsidiaries. Through its 130 branches and 850 automatic teller machines (ATM), the bank serves 80,000 corporate customers and more than 1.1 million private customers nationwide, making one in four citizens a ZABA customer. ZABA accounts for 25% of the Croatian banking sector’s total assets and almost 60% of its profits. The bank controls 35% of the country’s investment funds, 41% of obligatory pension funds, and 30% of specialized savings accounts for real estate transactions. Euromoney and Global Finance publications named ZABA Croatia’s best bank in 2011.

 A word from Zagrebačka Bank (Zagrebačka banka d.d.)

“With Oracle Advanced Analytics we execute computations on thousands of attributes in parallel—impossible with open-source R. Analyzing in Oracle Database without moving data increases our agility. Oracle Advanced Analytics enables us to make quality decisions on time, increasing our cash loans business 15%.”– Jadranka Novoselovic, Head of Business Intelligence Development, Zagrebačka Bank 

Challenges

• Increase bank performance of statistical modeling and predictive analytics, which can take three days for data preparation and model scoring and at least 24 hours for model building
• Improve ZABA’s business agility by increasing the efficiency of building and testing predictive models in the Oracle Database platform rather than moving large volumes of financial and customer data between servers and databases to generate predictive analytics
• Gain the ability to use predictive analytics for commercial activities in order to better target customers for new banking products and services
• Reduce the risks and costs of executing statistical modeling which requires transfers of data to individual analytical servers with dedicated hardware resources using specialized manpower
• Strengthen prediction power by increasing model hit ratio and making it easy for analysts to refresh scores

Solutions

• Used Oracle Advanced Analytics on Oracle Database to transform traditional predictive analytics that could take days to prepare and execute all tasks, including data import and export, into a seamless process executed in seconds, minutes, or hours—increasing cash loans by 15% within 18 months due to improved hit ratio
• Saved 1,000 man-days in IT maintenance per year by using Oracle Exadata, Oracle GoldenGate, and Oracle Data Integrator for data warehouse integration with extension to predictive and statistical modeling using Oracle Advanced Analytics Database
• Increased prediction performance and delivered comprehensive statistical functionality for in-database computation by leveraging the security, reliability, performance, and scalability of Oracle Database and Oracle Advanced Analytics for predictive analytics—running data preparation, transformation, model building, and model scoring within the database
• Enabled analysts to leverage in-database mining algorithms with both Oracle Advanced Analytics’ Oracle Data Mining and Oracle’ R enterprise components to achieve much faster access to analytics data such as credit risk scoring and customer retention, without needing to transfer data between servers and databases for statistical modeling
• Empowered the bank’s IT team to focus on business-triggered statistical modeling—for example to increase the hit ratio of target customers for a newly developed credit card or to improve customer retention—rather than spending most of their time addressing regulatory projects
• Empowered the organization to improve prediction accuracy by simplifying the development effort for analytics and minimizing developer intervention during model design, making it easy for analysts to refresh scores such as customer retention, with an updated data set
• Strengthened decision-making across the bank’s regulatory and commercial activities by delivering business analytics more rapidly, for example enabling risk managers to improve credit risk scorings with fast ad-hoc analysis
• Facilitated enterprise-wide access to statistics and advanced analytics through delivery of Oracle Advanced Analytics’ actionable insights via Oracle Business Intelligence Enterprise Editiondashboards and business applications
• Improved total cost of ownership by eliminating the need for dedicated analytical servers and improving development and execution time of business analytics by 30%, thanks to Oracle Advanced Analytics in-database architecture
• Incorporated Oracle Database as an enterprisewide analytical platform—eliminating the need for two dedicated administrators focused on server maintenance and administrative tasks
• Ensured compliance with regulatory demands in terms of consistent, punctual filing of regulatory reports—avoiding heavy penalties from the Croatian National Bank
• Why Oracle?

“We chose Oracle because our entire data modeling process runs on the same machine with the highest performance and level of integration. With Oracle Database we simply switched on the Oracle Advanced Analytics option and needed no new tools,” said Sinisa Behin, ICT coordinator at business intelligence development, Zagrebačka Bank.

“Our plan is to maximize coverage of our commercial activities, so that each process of campaign management and sales of financial products and services is empowered by statistical analysis. Oracle’s engineered high-performance platform met our analytical requirements for a low cost of ownership,” said Lidija Glavinic, ICT coordinator at business intelligence development, Zagrebačka Bank.

Implementation Process

The deployment of Oracle Advanced Analytics represented the final stage of ZABA’s consolidation on Oracle technology. The organization migrated current clients, products, and portfolio models together while starting to develop predictive analytics for its commercial department from scratch. The retention model migration from SAS to the Oracle Advanced Analytics platform was one of the first migrations of this type in the region. Oracle’s Advanced Analytics Development team specifically designed the functionality of clustering variables for ZABA and implemented the Oracle R Enterprise Varclus package in the 1.5 release.

Partners:

Zagrebačka Bank collaborated with Oracle Partner Combis to successfully migrate its predictive models from SAS to the Oracle Advanced Analytics platform. Combis completed the migration on time and trained ZABA employees in the use of Oracle tools.

Multicom d.o.o
Combis d.o.o
Neos d.o.o

Oracle Product and Services

• Oracle Database
• Oracle Advanced Analytics
• Oracle GoldenGate
• Oracle Business Intelligence Enterprise Edition
• Oracle Enterprise Performance Management
• Oracle Exadata

Oracle Advanced Analytics (OAA) Database Option leverages Oracle Text, a free feature of the Oracle Database, to pre-process (tokenize) unstructured data for ingestion by the OAA data mining algorithms.  By moving, parallelized implementations of  machine learning algorithms inside the Oracle Database, data movement is eliminated and we can leverage other strengths of the Database such as Oracle Text (not to mention security, scalability, auditing, encryption, back up, high availability, geospatial data, etc.

This Mining Structured Data and Unstructured Data using Oracle Advanced Analytics 12c YouTube video presents an overview of the capabilities for combining and performing data mining on both structured and unstructured data.  The YouTube includes several quick demonstrations on classification and clustering using unstructured data and provides instructions and links on how to get started--either on premise or on the Oracle Cloud.  

I hope you find this helpful and a pleasure to watch.   

Presentation Slides.

You can also access similar YouTube videos at this Oracle Data Mining at the Movies blog posting.

Follow CharlieDataMine on Twitter.

Thanks for watching!

Charlie

Sr. Dir. of Product Management, Oracle Advanced Analytics and Data Mining

charlie.berger@oracle.com 

Machine Learning in the Cloud from Oracle?   Yes!  

Did you know that Oracle's Database as a a Cloud Service High and Extreme Editions bundle Oracle Advanced Analytics Database Option?

High Performance: Multitenant, Partitioning, Real Application Testing, Advanced Compression, Advanced Security, Label Security, Database Vault, OLAP, Advanced Analytics, Spatial and Graph, Diagnostics Pack, Tuning Pack, Database Lifecycle Management Pack, Data Masking & Subsetting Pack and Cloud Management Pack for Oracle Database.

Extreme Performance: In-Memory Database, Active Data Guard, Multitenant, Partitioning, Real Application Testing, Advanced Compression, Advanced Security, Label Security, Database Vault, OLAP, Advanced Analytics, Spatial and Graph, Diagnostics Pack, Tuning Pack, Database Lifecycle Management Pack, Data Masking & Subsetting Pack and Cloud Management Pack for Oracle Database.

Now, you can get a "Smart" Database in the Cloud with Oracle Advanced Analytics.  

After all, who wants a "Dumb" Database anyway?!  

For more information on Oracle Advanced Analytics on-premise or in the Cloud, visit Oracle Advanced Analytics on the Oracle Technology Network (OTN) or view this latest Oracle's Advanced Analytics - Making Big Data + Analytics Simple! presentation.

Also, you might be interested in the DX MarketingOAA in the Cloud Customer Success Story.  

There are two YouTube testimonials as well as the story write up.

See everyone on the Oracle Advanced Analytics machine learning Cloud!

Charlie 

BIWA Summit’17 - THE Big Data + Analytics + Spatial + Cloud +IoT + Everything CoolOracle User Conference

January 31 - February 2, 2017 @ the Oracle HQ Conference Center in Redwood Shores, CA.

The BIWA Summit’17, held in conjunction with Spatial Summit’17 at the Oracle HQ Conference Center, annually draws several hundred customers, partners and Oracle experts who share best practices, “novel and interesting” use cases, customer case studies, and present on emerging technologies.   Featured talks by Oracle executives, technical sessions delivered by experts and user friendly introductory talks make this a great event for customers.  There are several 2 hour Hands on Labs running Oracle products on the Oracle Public Cloud where users can learn how to use Oracle software.   

See www.biwasummit.org for full agenda and registration information.

BIWA and Spatial Summit’17 Agenda: Tuesday, January 31 + Reception sponsored by Deloitte

BIWA and Spatial Summit’17 Agenda: Wednesday, February 1 + Reception sponsored by L&T InfoTech

BIWA and Spatial Summit’17 Agenda: Thursday, February 2

NOTE:  BIWA and Spatial IOUG SIGs are managed and run as independent organizations.  Oracle Employees (who are not speakers) must register as any customer does.  However, you can use the BIWAALUMNI discount code when registering to receive a $150 discount.

Hope to see everyone at BIWA Summit’17!

Charlie

BIWA Summit 2017

Event Details:

• Date:
  _{January 31st – February 2nd}
• Location:
  _{Oracle Convention Center
       Oracle Campus
       350 Oracle Pkwy
       Redwood City, Ca}

Guests on theCUBE:

New Blog Template Coming Soon....  I don't know much more than that, but Oracle blogger HQ informs us that we'll be receiving a new blog template and process, so stay tuned.  Hopefully it is better!

Charlie 

Oracle's Machine Learning and Advanced Analytics 12.2 and Oracle Data Miner 4.2 New Features.  This presentation highlights the new machine learning algorithms, features, functions and "differentiators" added to Oracle Database Release 12.2 and Oracle SQL Developer4.2. These features and functioned are "packaged" as part of the Oracle Advanced Analytics Database Option and Oracle Data Miner workflow UI on-premise and in the Oracle Database Cloud Service High and Extreme Editions. I hope you enjoy the video!

Oracle's Machine Learning and Advanced Analytics 12.2 and Oracle Data Miner 4.2 New Features! on YouTube 

Download the Oracle's Machine Learning and Advanced Analytics 12.2 and Oracle Data Miner 4.2 New Features .pdf presentation.

Slide excerpts:

Charlie Berger

charlie.berger@oracle.com

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

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

BIWA is an IOUGSIG run by entirely by customers, partners and Oracle employeevolunteers.  We’re always looking for people who would like to beinvolved.  Let me know if you’d like to contribute to the planning andorganization of future BIWA events and activities.

See everyone atBIWA’17!

Charlie, onbehalf 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).

See bottom of page for the Session Search capability

Below is a list of the sessions and links to download mostof the materials for the various sessions.  Click on the DETAILS buttonnext to the session you want to download, then the page should refresh with thesession description and (assuming the presenter uploaded files, but be awarethat files may be limited to 5MB) you should see a list of files for thatsession.  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

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

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Graph Databases: A Social Network Analysis Use Case

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

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3D Data Management - From Point Cloud to City Model

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

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Oracle Spatial and Graph: New Features for 12.2

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

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

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Other

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

Taking Full Advantage of the PL/SQL Compiler

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Taking Full Advantage of the PL/SQL Result Cache

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Meet Your Digital Twin

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Making SQL Great Again (SQL is Huuuuuuuuuuuuuuuge!)

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Lightning Round for Vendors

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Recently, I was asked by a friend and colleague, Chris Claterbos, Lecturer at University of Kansas' Business School, to deliver a guest lecture to his business analytics students.  

In preparation, so as to not make it an entirely Oracle "product" presentation, I tried to gather some general information on the big data + analytics market, job opportunities & careers and future musings about where the industry is headed.  I liked resulting presentation so am posting and sharing it here.  

U. Kansas Guest Lecture on Big Data Analytics with Oracle's Advanced Analytics, Big Data SQL and Cloud

• Big Data + Analytics “Phenomenon”
• Careers in Big Data Analytics
• Product
• Oracle Advanced Analytics Overview & Features/Benefits
• Brief Demos
• Example Customer References
• Applications “Powered by OAA”
• Getting Started
• Q & A

Enjoy!  Hopefully all you all become data'n'science stars!  

Charlie 

What you will learn:  This Predictive Analytics using Oracle Data Mining Ed 1 training will review the basic concepts of data mining. Expert Oracle University instructors will teach you how to leverage the predictive analytical power of Oracle Data Mining, a component of the Oracle Advanced Analytics option.

Learn To:

• 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, apply, and deploy multiple data mining models.
• Use Oracle Data Mining's predictions and insights to address many kinds of business problems.
• Deploy data mining models for end-user access, in batch or real-time, and within applications.

Benefits to You

When you've completed this course, you'll be able to use the Oracle Data Miner 4.1, the Oracle Data Mining "workflow" GUI, which enables data analysts to work directly with data inside the database. The Data Miner GUI provides intuitive tools that help you explore the data graphically, build and evaluate multiple data mining models, apply Oracle Data Mining models to new data, and deploy Oracle Data Mining's predictions and insights throughout the enterprise.

Oracle Data Miner's SQL APIs - Get Results in Real-Time

Oracle Data Miner's SQL APIs automatically mine Oracle data and deploy results in real-time. Because the data, models, and results remain in the Oracle Database, data movement is eliminated, security is maximized and information latency is minimized.

Introduction

• Course Objectives
• Suggested Course Prerequisites
• Suggested Course Schedule
• Class Sample Schemas
• Practice and Solutions Structure
• Review location of additional resources

Predictive Analytics and Data Mining Concepts

• What is the Predictive Analytics?
• Introducting the Oracle Advanced Analytics (OAA) Option?
• What is Data Mining?
• Why use Data Mining?
• Examples of Data Mining Applications
• Supervised Versus Unsupervised Learning
• Supported Data Mining Algorithms and Uses

Understanding the Data Mining Process

• Common Tasks in the Data Mining Process
• Introducing the SQL Developer interface

Introducing Oracle Data Miner 4.1

• Data mining with Oracle Database
• Setting up Oracle Data Miner
• Accessing the Data Miner GUI
• Identifying Data Miner interface components
• Examining Data Miner Nodes
• Previewing Data Miner Workflows

Using Classification Models

• Reviewing Classification Models
• Adding a Data Source to the Workflow
• Using the Data Source Wizard
• Using Explore and Graph Nodes
• Using the Column Filter Node
• Creating Classification Models
• Building the Models
• Examining Class Build Tabs

Using Regression Models

• Reviewing Regression Models
• Adding a Data Source to the Workflow
• Using the Data Source Wizard
• Performing Data Transformations
• Creating Regression Models
• Building the Models
• Comparing the Models
• Selecting a Model

Using Clustering Models

• Describing Algorithms used for Clustering Models
• Adding Data Sources to the Workflow
• Exploring Data for Patterns
• Defining and Building Clustering Models
• Comparing Model Results
• Selecting and Applying a Model
• Defining Output Format
• Examining Cluster Results

Performing Market Basket Analysis

• What is Market Basket Analysis?
• Reviewing Association Rules
• Creating a New Workflow
• Adding a Data Source to the Workflow
• Creating an Association Rules Model
• Defining Association Rules
• Building the Model
• Examining Test Results

Performing Anomaly Detection

• Reviewing the Model and Algorithm used for Anomaly Detection
• Adding Data Sources to the Workflow
• Creating the Model
• Building the Model
• Examining Test Results
• Applying the Model
• Evaluating Results

Mining Structured and Unstructured Data

• Dealing with Transactional Data
• Handling Aggregated (Nested) Data
• Joining and Filtering data
• Enabling mining of Text
• Examining Predictive Results

Using Predictive Queries

• What are Predictive Queries?
• Creating Predictive Queries
• Examining Predictive Results

Deploying Predictive models

• Requirements for deployment
• Deployment Options
• Examining Deployment Options