Monday Jan 20, 2014

Video Lecture Series Data Science Boot-Camp Tutorials

To introduce you to some topics in “Data Science”, below are some direct links to access a good set of ~ 30 minute Boot-Camp Tutorials by our Dan McClary, Ph.D., Oracle Principal Product Manager Big Data

Lessons: @ Video Lecture Series: Data Science Boot Camp

This lecture series utilizes data sets and example code: to access @ Data Science Bootcamp Data Sets and Example Code

You might also like to view the Oracle R Enterprise Tutorial Series.

Oracle R Enterprise Tutorial Series

Below are some direct links to access a good set of ~ 30 minute tutorials to introduce you to “R”, Oracle R Enterprise and R for Hadoop By Brian Pottle, Senior Principal. You can also see from this link How much faster is the Oracle R implementation compared to “Normal” R ?.

Lessons: @ Oracle R Enterprise Tutorial Series on Oracle Learning Library

You might also like to view the Video Lecture Series: Data Science Boot-Camp Tutorials.

Tuesday Nov 26, 2013

Small Steps to Big Data BI&EPM Partner Community Forum January 2014

Open to all OPN partners in EMEA, we are running the Business Analytics Partner Community Forum over two days in London, on 16th and 17th January 2014 - Register Now Here.

This forum entitled “Small Steps to Big Data” will focus on discussing with Partners, how best to exploit the tremendous interest in “Big Data Analytics” and to clarify under what circumstances “R” and “Hadoop” are best deployed, and how these co-exist, integrate with, and extend the capabilities of tools you are already familiar with such as Oracle BI, ODI, Endeca and the Oracle Database. We will consider guidelines to hardware deployments, but the main focus of the forum will be how the software inter-operates: with guest speakers from Cloudera, and other partners who have experience in this field.

On the one hand, I do not think “Big Data=Hadoop”. While on the other, Oracle whole-heartedly embraces useful Open Source innovations such as “R” and “Hadoop”: we are, after all, a big player in Open Source with for example JAVA, NoSql and MySql.

You can download the agenda here.  We will seek to answer questions such as:

· How Big is “Big” ? ... at what size is Hadoop’s MPP approach beneficial ?

· What about “Variety” ? ... how do we digest “Any Data” ?

· Who uses this analytics ? ... a few “Data Scientists” or 100s of “Business Users” ?

· How do you spot a “Big Data Analytics” opportunity ?

· If someone is already using Hadoop, do they want to talk to Oracle ?

· What is NEW, and what is Business-as-Usual ?

Audience: This forum will appeal to CTOs, Solution architects and consultants in Oracle Partners familiar with Oracle’s Business Analytics solutions. We will examine the economics and business cases driving “Big Data Analytics” projects, and dive into the pros-and-cons of technology options available to your customers.

· Day 1 – Thursday 16th Jan. 2014: Starts 11.0 am – Sales and Executive briefing.

o Networking Dinner in Evening

· Day 2 – Friday 17th Jan. 2014: Ends 4.0 pm – Deeper dive technical discussions.

Register Now Here

Thursday Apr 25, 2013

How much faster is the Oracle R implementation compared to “Normal” R ?

For those of you just getting interested in “Advanced Analytics”, you may still be wondering “What is R ?”… R is an open-source language and environment for statistical computing and data visualization: and it works with OBI to enrich the graphics and predictive capabilities: see here a quick preview on YouTube.

It is being taught in colleges and universities in courses on statistics and advanced analytics – often in preference to more traditional statistical software tools – and so skills in R are readily available among younger graduates.

For you experts in the field who use R anyway, the key question is why use “Oracle’s version” ?

The tight integration between R, Oracle Database 11g, and Hadoop enables R users to write one R script that can run in three different environments: a laptop running open source R, Hadoop running with Oracle Big Data Connectors, and Oracle Database 11g.

For large analyses on large Oracle data-sets, it is much faster and easier to do this “inside” the database, than exporting the data into another specialised external data format.  Some of the benchmarks below, show 4x ~ 20x + faster for various operations, and even 100x + for some data scoring algorithms.

For Oracle Advanced Analytics Option, Oracle R Enterprise in-DB functionality, the performance gains come through the R-to-SQL transparency layer for native SQL performance and the OAA/ORE “mapping” to the OAA/Oracle Data Mining SQL based hi-performance data mining algorithms and statistical functions that are native in-DB parallelized implementations of the algorithms. 

Also, besides the simpler and more scalable architecture, the majority of the performance gains stem from eliminating the extract, mine, apply models, import outer loop which can take weeks to months, largely due to “human time” sinks to manually translate the data transformations and model logic to native SQL for in-DB deployment.  That conversion process is tedious, time consuming and error prone.  The OAA in-DB performance therefore cuts that latency time down to secs / mins / hours.

Wednesday Aug 29, 2012

R Statistical Analytics with Faster Performance for Enterprise Database Access and Big Data

Further demonstrating commitment to the open source community, Oracle has just released enhanced support of the R statistical programming language for Oracle Solaris and AIX in addition to Linux and Windows, connectivity to Oracle TimesTen In-Memory Database in addition to Oracle Database, and integration of hardware-specific Math libraries for faster performance.  Oracle’s Open Source distribution of R is available with the Oracle Big Data Appliance and available for download now.

Oracle also offers Oracle R Enterprise, a component of Oracle Advanced Analytics that enables R processing on Oracle Database servers.   This all goes to make big data analytics more accessible in the enterprise and improving data scientist productivity with faster performance

Since its introduction in 1995, R has attracted more than two million users and is widely used today for developing statistical applications that analyze big data.

Analyst Report: Oracle Advances its Advanced Analytics Strategy

 

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