Learn to manage Big Data and understand the fundamentals of data science in this series.  

The videos in this series provide concise explanations of how to use Oracle products, open source tools, and data science to quickly find value in Big Data.  

(No previous background in statistics is necessary.)

Gain insight into how Big Data works. Learn the step for implementing a big data project.

Read the comprehensive new e-book to get advice from Oracle and industry leaders on how you can use big data to generate new business insights and make better decisions.

In this set of video tutorials, you are shown how to use Oracle Big Data.

Topics covered include:

Using Big Data to Improve the Customer Experience

Using Big Data to Deliver a Personalized Service

The tutorials in this series teach you how to perform administration tasks for the Oracle Big Data Appliance.

At the end of this course, you should be able to:

• Learn about the Hadoop ecosystem and its components
• Learn how to setup, install, use, and secure the Oracle Big Data Appliance (BDA):
  • Complete the Oracle BDA Site Checklists
  • Run the Oracle BDA Configuration Utility
  • Install the Oracle BDA Mammoth software on the Oracle BDA
  • Securing the Oracle BDA
• Use, administer, and manage the Oracle BDA 
  • Cloudera Manager (CM)
  • Enterprise Manager (EM) 
• Use the Oracle Big Data Connectors
  • Oracle SQL Connector for Hadoop Distributed File System (OSCH)
  • Oracle Loader for Hadoop (OLH), and Oracle Data Integrator (ODI)
  • Oracle XQuery for Hadoop (OXH)
  • Oracle R Advanced Analytics for Hadoop (ORAAH)

Although you may view these sessions in any order, this series is designed in a linear fashion, with each tutorial building upon the previous ones. Therefore, if you are new to Big Data or the Oracle Big Data Appliance (BDA), it is recommended that you view these lessons in order.

This set of videos covers the Oracle MoviePlex - a big data end-to-end demonstration. It  highlights many of the key components of the Oracle big data platform.  There are 6 recorded  videos - each under 10 minutes.

This tutorial illustrates how you can securely analyze all of your data across the big data platform - whether that data resides in Oracle Database 12c, Hadoop, Oracle NoSQL Database or a combination of these sources.

Watch this playlist on Oracle Big Data SQL. Learn about monitoring and tuning, Enterprise Manager, Cloudera Manager, and analyzing statistics.

This series features an OBE and a recorded webcast. Learn how to use  SQL for Pattern Matching. Row pattern matching in native SQL improves application and development productivity and query efficiency for row-sequence analysis.

Recognizing patterns in a sequence of rows has been a capability that was widely desired, but not possible with SQL until now. There were many workarounds, but these were difficult to write, hard to understand, and inefficient to execute. With Oracle Database 12c Release 1 (12.1), you can use the MATCH_RECOGNIZE clause to perform pattern matching in SQL to do the following:

1. Logically partition and order the data that is used in the MATCH_RECOGNIZE clause with its PARTITION BY and ORDER BY clauses.
2. Define patterns of rows to seek using the PATTERN clause of the MATCH_RECOGNIZE clause. These patterns use regular expressions syntax, a powerful and expressive feature, applied to the pattern variables you define.
3. Specify the logical conditions required to map a row to a row pattern variable in the DEFINE clause.
4. Define output measures, which are expressions usable in the MEASURES clause of the SQL query.
5. Control the output (summary vs. detailed) from the pattern matching process

Recognizing patterns in a sequence of rows has been a capability that was widely desired, but not possible with SQL until now. There were many workarounds, but these were difficult to write, hard to understand, and inefficient to execute. With Oracle Database 12c Release 1 (12.1), you can use the MATCH_RECOGNIZE clause to perform pattern matching in SQL to do the following:

1. Logically partition and order the data that is used in the MATCH_RECOGNIZE clause with its PARTITION BY and ORDER BY clauses.
2. Define patterns of rows to seek using the PATTERN clause of the MATCH_RECOGNIZE clause. These patterns use regular expressions syntax, a powerful and expressive feature, applied to the pattern variables you define.
3. Specify the logical conditions required to map a row to a row pattern variable in the DEFINE clause.
4. Define output measures, which are expressions usable in the MEASURES clause of the SQL query.
5. Control the output (summary vs. detailed) from the pattern matching process

Watch this playlist on Oracle Big Data SQL. Learn about monitoring and tuning, Enterprise Manager, Cloudera Manager, and analyzing statistics.

Watch these demonstrations to get started with the Oracle NoSQL Database.

In these self-paced tutorials, you learn about few of the new features in the latest release of Oracle NoSQL Database. In these short tutorials, you are provided with an overview of the features and also a few demos on how these features are implement in an application.

In this tutorial, you do a bulk insert across different shards of an Oracle NoSQL Database.

Oracle NoSQL Database is an advanced key-value database that is designed to be highly scalable with predictable low latency. In this video, learn how to deploy Oracle NoSQL Database on AWS in 10 minutes. We also demonstrate high availability features in case of node failure.

In this demonstration, the Oracle NoSQL Database, Release 2 features are described and discussed.

In this Webinar, learn about the Oracle NoSQL Database. This recording will explain to you what the Oracle NoSQL Database is, how sizing is done, and cluster information including 3x3 deployment, expansion, and upgrade.

 

In this Webinar, learn about table based data modeling with the Oracle NoSQL Database. You will learn how to approach data modeling using real world situations. Examples used are email client app as a driver, schema design and deployment, and queried into data access methods. Architecture is also covered.

Perform the steps required to configure and use Oracle NoSQL Database with Oracle SQL Developer.

Oracle NoSQL Database is a scalable, distributed NoSQL database, designed to provide highly reliable, flexible and available data management across a configurable set of storage nodes.

Apache Hive is a data warehouse infrastructure built on top of Hadoop for providing data summarization, query, and analysis. Hive also provides a pluggable programming model that allows you to specify custom interfaces and classes that support querying data residing in data sources like an Oracle NoSQL Database table.

Oracle NoSQL Database Hadoop Integration Classes support running Hadoop MapReduce jobs and Hive queries against data stored in an Oracle NoSQL Database table.

In this tutorial, you retrieve data stored in an Oracle NoSQL Database using Hive Query Language. 

The Oracle NoSQL Database is a distributed key-value database. It is designed to provide highly reliable, scalable and available data storage across a configurable set of systems that function as storage nodes. Data is stored as key-value pairs, which are written to particular storage node(s), based on the hashed value of the primary key. Storage nodes are replicated to ensure high availability, rapid failover in the event of a node failure and optimal load balancing of queries. Customer applications are written using an easy-to-use Java/C API to read and write data.

In this tutorial, you prepare three Rasperry Pis to act as three storage nodes and form a 1x3 cluster. All the storage nodes have the same copy of data.

In this tutorial, you retrieve data from an Oracle NoSQL Database by providing multiple primary keys.

Watch how the Failover feature works in the Oracle NoSQL Database.  The Failover feature is used to fix a loss of quorum situation which can occur due to zone failure or in case of planned maintenances.

The tutorials in this series teach you how to perform data mining with Oracle Database 12c, by using Oracle Data Miner 17.2. Oracle Data Miner 17.2 is included as an extension of Oracle SQL Developer, version 17.2.

The OBEs in this series provide you with instructions on how to use Oracle Data Mining 11g Release 2

Oracle Database 12c: Oracle Data Mining New Features

Ever want to just sit and watch a YouTube-like presentation and "live" demos of Oracle Advanced Analytics/Oracle Data Mining?
This 1+ hour long session focuses primarily on the Oracle Data Mining component of the Oracle Advanced Analytics Option and is tied to the Oracle SQL Developer Days virtual and onsite events.

* Big Data + Big Data Analytics
* Competing on analytics & value proposition
* What is data mining?
* Typical use cases
* Oracle Data Mining high performance in-database SQL based data mining functions
* Exadata "smart scan" scoring
* Oracle Data Miner GUI (an Extension that ships with SQL Developer)
* Oracle Business Intelligence EE + Oracle Data Mining results/predictions in dashboards
* Applications "powered by Oracle Data Mining for factory installed predictive analytics methodologies
* Oracle R Enterprise

This tutorial covers the use of Oracle Data Miner 4.0 to perform data mining activities on the Big Data Lite 4.0 VM.

Oracle R Enterprise (ORE), a component of the Oracle Advanced Analytics Option, makes the open source R statistical programming language and environment ready for the enterprise and big data.

This series teaches you how to use Oracle R Enterprise, version 1.4.

Although you may view these tutorials in any order, this series is designed in a linear fashion, with each tutorial building upon the previous ones. Therefore, if you are new to the R language, or to Big Data, it is recommended that you view these tutorials in order.

Is this demonstration, you are shown how to integrate your data with the Oracle Big Data Connectors.

In this demo, you are shown how to Use Oracle Direct Connector for HDFS to Read the Data from HDFS.

In this demo, you are introduced to how to use Oracle R Connector for Hadoop for analyzing data.

In this self-study, you learn how to use the Oracle Data Integrator Application Adapter for Hadoop. Topics include an overview of big data and the ODI application adapter. You learn how to load from a file into hive, transform data on hive, and load hive data into Oracle.

This tutorial covers steps to set up, configure, and run Summary Advisor on an Exalytics machine using TimesTen database as a target for storing aggregates.

The tutorials in this series teach you how to use Oracle Big Data Spatial and Graph components, including Property Graph, Spatial Vector analysis, and Spatial Raster analysis.