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 Oracle white paper)

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.

The world of traditional advanced analytics is inherently wrought with weak points of server analytical servers, data movement, data duplication, data security, different tools for different analysis purposes and ever growing information latency. Significant challenges become especially clear during predictive models deployment projects when attempts to mash together the separate worlds of DBAs, IT and the database with the worlds of data scientists, advanced analytics and separate analytical servers highlight these differences.

Traditional data analysis typically start with a representative sample or subset of the data that is exported to separate analytical servers (SAS, SPSS or R, etc.) that have been especially designed for statisticians and data scientists who analyze the data. These analytics 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 translated to SQL somehow and recreated inside the database in order to apply the models to make predictions on the larger datasets maintained inside the data warehouse. Or, sometimes vendors will change for additional model deployment products. 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. 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, 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.

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. Oracle Advanced Analytics in-database analytical functionality and predictive algorithms are all accessible via the SQL API data mining and statistical functions (Oracle Data Mining), via the SQL Developer 4.1 Oracle Data Miner “workflow” GUI extension, and via integration with the R open source statistical programming language (Oracle R Enterprise). Oracle Advanced Analytics’ SQL transparently layer pushes down R functions to equivalent ODM and SQL functions for in-database performance and scalability. By integrating big data management and big data analytics into the same Oracle Database 12c platform, Oracle eliminates data movement, reduces total cost of ownership and delivers the fastest way to deliver enterprise-wide predictive analytics solutions and applications.

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.

About

Everything about Oracle Data Mining, a component of the Oracle Advanced Analytics Option - News, Technical Information, Opinions, Tips & Tricks. All in One Place

Search

Categories
Archives
« July 2015
SunMonTueWedThuFriSat
   
1
2
3
4
5
6
7
8
9
10
11
12
13
14
16
17
18
19
20
21
22
23
25
27
28
29
30
31
 
       
Today