Tuesday Dec 09, 2014

Big Data Governance– Balancing Big Risks and Bigger Profits

To me, nothing exemplifies the real value that Big Data brings to life than the role it played in the last edition of the FIFA soccer world cup. Stephen Hawkins predicted that England’s chance of winning a game drops by 60 percent every time the temperature increases by 5ºC. Moreover, he found that England plays better in stadiums situated 500 meters above sea level, and perform better if the games kick off later than 3PM local time. In short, England’s soccer team struggles to cope with the conditions in hot and humid countries.

We all have heard, meditated and opined about the value of Big Data, the panacea for all problems. And it is true. Big Data has started delivering real profits and wins to businesses. But as with any data management program, profit benefits should be maximized while striving to minimize potential risks and costs.

Customer Data is Especially Combustible Data

The biggest lift in businesses using Big Data is obtained through the mining of customer data. By storing and analyzing seemingly disparate customer attributes and running analytic models through the whole data set (data sampling is dying a painful demise), businesses are able to accurately predict buying patterns, customer preferences and create products and services that cater to today’s demanding consumers. But this veritable mine of customer information is combustible. And by that, what I mean is that a small leak is enough to undo any benefits hitherto extracted from ensuing blowbacks like financial remuneration, regulatory constrictions and most important of all the immense reputational damage. And this is why Big Data should always be well governed. Data Governance is an aspect of data security that helps with safeguarding Big Data in business enterprises.

Big Data Governance

Big Data Governance is but a part (albeit a very important part) of a larger Big Data Security strategy. Big Data security should involve considerations along the efficient and economic storage of data, retrieval of data and consumption of data. It should also deal with backups, disaster management and other traditional considerations.

When properly implemented a good Governance program serves as a crystal ball to the data flow within the organizations. It will answer questions on how safe the data is, who can and should be able to lay their hands on the data and proactively prevent data leakage and misuse. Because when dealing with Big Reservoirs of Data, small leakages can go unnoticed. 

Thursday Nov 20, 2014

Let Oracle GoldenGate 12c Take You to the Cloud

If your organization is in the ~80% of the global business community, you are most likely working on a cloud computing strategy for your organization, or actively implementing. The cloud computing growth rate is 5X more than the overall IT growth rate because of the clear and already proven cost savings, agility, and  scalability benefits of cloud architectures.

When organizations decide to embark on their cloud journey, they notice there are several questions and challenges to be addressed, involving data accessibility, security, availability, system management, performance etc. Oracle GoldenGate's real-time data integration and bi-directional transactional replication technology addresses critical challenges such as:

  • How to move my systems to the cloud without interrupting operations?
  • How to enable timely data synchronization between the systems on the cloud and on-premises to ensure access to consistent data for all end users?
  • How do I run operational reports with the data I have in cloud environments, or feed my analytical systems in cloud solutions?
  • In managed or private clouds, how do I keep the cloud platform highly available when I need to do maintenance, upgrades?

 On Tuesday,  December 2nd we will tackle these questions in a free webcast:

Live Webcast: Oracle GoldenGate 12c for the Enterprise and the Cloud

Tuesday, December 2nd, 2014 10am PT/ 1pm ET 

In this webcast, you will not only hear about Oracle GoldenGate's strong solutions for cloud environments, but also the latest features that strengthen its offering. The new features we will discuss include:

  • Support for Informix, SQL Server 2014, MySQL Community Edition, and big data environments
  • Real-time data integration between on premises and cloud with SOCKS5 compliance
  • New data repair functionality to help ensure database consistency across heterogeneous systems
  • Moving from Oracle Streams to GoldenGate with the new migration utility

 I would like to invite you to join me and my colleague Chai Pydimukkala, Senior Director of Product Management for Oracle GoldenGate in this session to learn the latest on GoldenGate 12c and ask your questions in a live Q&A.

Hope to see you there!

Tuesday Nov 18, 2014

Oracle GoldenGate for Informix is Released

Oracle GoldenGate for Informix 12.1.2.1.0 is available on OTN and Oracle eDelivery. This is a new addition to Oracle GoldenGate's heterogeneous database support.[Read More]

Wednesday Nov 12, 2014

ODI 12c - Spark SQL and Hive?

In this post I'll cover some new capabilities in the Apache Spark 1.1 release and show what they mean to ODI today. There's a nice slide shown below from the Databricks training for Spark SQL that pitches some of the Spark SQL capabilities now available. As well as programmatic access via Python, Scala, Java, the Hive QL compatibility within Spark SQL is particularly interesting for ODI...... today. The Spark 1.1 release supports a subset of the Hive QL features which in turn is a subset of ANSI SQL, there is already a lot there and it is only going to grow. The Hive engine today uses map-reduce which is not fast today, the Spark engine is fast, in-memory - you can read much more on that elsewhere.

Figure taken from from the Databricks training for Spark SQL, July 2014.

In the examples below I used the Oracle Big Data Lite VM, I downloaded the Spark 1.1 release and built using Maven (I was on CDH 5.2). To use Spark SQL in ODI, we need to create a Hive data server - the Hive data server masquerades as many things, it can can be used for Hive, for HCatalog or for Spark SQL. Below you can see my data server, note the Hive port is 10001, by default 10000 is the Hive server port - we aren't using Hive server to execute the query, here we are using the Spark SQL server. I will show later how I started the Spark SQL server on this port (Apache Spark doc for this is here).

I started the server using the Spark standalone cluster that I configured using the following command from my Spark 1.1 installation;

./sbin/start-thriftserver.sh --hiveconf hive.server2.thrift.bind.host bigdatalite --hiveconf hive.server2.thrift.port 10001 --master spark://192.168.122.1:7077

You can also specify local (for test), Yarn or other cluster information for the master. I could have just as easily started the server using Yarn by specify the master URI as something like --master yarn://192.168.122.1:8032 where 8032 is my Yarn resource manager port. I ran using the 10001 port so that I can run both Spark SQL and Hive engines in parallel whilst I do various tests. To reverse engineer I actually used the Hive engine to reverse engineer the table definitions in ODI (I hit some problems using the Spark SQL reversing, so worked around it) and then changed the model to use my newly created Spark SQL data server above.

Then I built my mappings just like normal - and used the KMs in ODI for Hive just like normal. For example the mapping below aggregates movie ratings and then joins with movie reference data to load movie rating data - the mapping uses the datastores from a model obtained from the Hive metastore;

If you look at the physical design the Hive KMs are assigned but we will execute this through the Spark SQL engine rather than through Hive. The switch from engine to engine was handled in the URL within our our Hive dataserver.

When the mapping is executed you can use the Spark monitoring API to check the status of the running application and Spark master/workers.

You can also monitor from the regular ODI operator and ODI console. Spark SQL support uses the Hive metastore for all the table definitions be they internally or externally managed data. 

There are other blogs from tools showing how to access and use Spark SQL, such as the one here from Antoine Amend using SQL Developer. Antoine has also another very cool blog worth checking out Processing GDELT Data Using Hadoop. In this post he shows a custom InputFormat class that produces records/columns. This is a very useful post for anyone wanting to see the Spark newAPIHadoopFile api in action. It has a pretty funky name, but is a key piece (along with its related methods) of the framework.

  1. // Read file from HDFS - Use GdeltInputFormat
  2. val input = sc.newAPIHadoopFile(
  3.    "hdfs://path/to/gdelt",
  4.    classOf[GdeltInputFormat],
  5.    classOf[Text],
  6.    classOf[Text]

Antoine also provides the source code to GdeltInputFormat so you can see the mechanics of his record reader, although the input data is delimited data (so could have been achieved in different ways) it's a useful resource to be aware of.

If you are looking at Spark SQL, this post was all about using Spark SQL via the JDBC route - there is another whole topic on transformations using the Spark framework alongside Spark SQL that is for future discussion. You should be aware of and check out the Hive QL compatibility documentation here, check what you can do can't do within Spark SQL today. Download the BDA Lite VM and give it a try.

Monday Nov 10, 2014

Big Data Governance and Metadata Management - A Recap

On the 30th of November we held a webcast on governing Big Data. It was the second in the series on Big Data (if you missed the first you can register for it here). We discussed the importance of bringing transparency to the Big Data Reservoir architecture and how to improve and enrich data within the reservoir using Oracle's Enterprise Data Quality (OEDQ). Oracle also announced Oracle Enterprise Metadata Management (OEMM), a comprehensive metadata management tool that is built with a business friendly search driven interface. 

Here is a quick recap of some of the questions that came through. 

Do these principles and technology of Metadata Management, Data Governance and Data Quality apply to Big Data as well as traditional Data?

All the technologies are equally applicable to Big Data as well as traditional data warehousing. In fact, Oracle Enterprise Data Quality and Oracle Enterprise Metadata Management are designed to bridge these two worlds.   

 Does Oracle Enterprise Metadata Management work with 3rd party metadata?

 Yes. We recognize that to truly govern data life cycle  Oracle Enterprise Metadata Management should be able to harvest data across multiple technologies and platforms including Oracle and Non Oracle Data bases, Business Analytics, Data Warehouses and ETL engines.

Is Oracle Enterprise Metadata Management compatible with 11g?

Oracle Enterprise Metadata Management is compatible with many 11g products too.

Where can I get more information about Oracle’s Data Integration products?

The best resource for Oracle Data Integration Products are

The Oracle Data Integration Home Page,

The Oracle Data Integration Technology Network,

The Oracle Data Integration Blog

Also connect with us on facebook and twitter (#OEDQ, #OEMM, ORCLGoldenGate, ODI12c)

Thursday Nov 06, 2014

Oracle Data Integrator and Hortonworks

Check out Oracle's Alex Kotopoulis being features on Hortonworks blog discussing how Oracle Data Integrator is the best tool for data ingest to Hadoop!

Remember to register for the November 11th joint webinar presented by Jeff Pollock, VP Oracle, and Tim Hall, VP Hortonworks.  Click here to register.  

Tuesday Oct 28, 2014

ODI 12c and DBaaS in the Oracle Public Cloud

This article illustrates how to connect ODI on premise to Oracle in the cloud (OPC), specifically the Database as a Service (DBaaS, see doc here) offering. You will see how easy it is to configure connectivity from within ODI and the use of familiar tools gives you the same consistency from on premise use to the cloud. A big concern for cloud computing is security and ensuring access is restricted and as secure as possible. For ODI on premise the challenge is how to connect to such a secure service. ODI provides tasks for transferring files to and from locations - databases are generally accessed via JDBC.

The initial state of an Oracle DBaaS service restricts remote access to SSL - so you can't just remotely connect by default to an Oracle database listener for example (it is possible to open that up by configuring this within DBaaS). File transfer to the cloud can be done out of the box using sftp capabilities, access to the database in order to load it with data, to transform data within it and to extract data from it can be done with a small bit of SSL tunneling - let's see how. The examples discussed in this article have been developed with ODI 12.1.3, a copy of the driver which performs the SSL tunneling can be found on java.net here. With this driver it is effortless to work with an on premise ODI and an Oracle database in the cloud.

Before we get to the ODI parts let's look at the basics, this is mentioned in the DBaaS documentation but sometimes it's simpler to read what someone has done than follow the doc.....

If you want to be using ODI or other remote capabilities such as ssh, sftp then before creating the Oracle database instance in the cloud you should generate a secure private key-public key pair. The public key gets used when you create the Oracle database instance in the cloud and the private key is used by SSL tools (such as sftp, ssh or the driver used) to securely connect to the cloud. 

When you create the key using something like PUTTY, then ensure you save the public key, private key and export the key using the OpenSSH key option also. ODI actually needs the OpenSSH format right now as the version of a library it depends on supports this.


You can see where the public key is provided below in the Instance Configuration section.....


The great news about the DBaaS capabilities is that it is all very familiar for Oracle database folks also the service itself can be managed from the command line - so as well as the web pages console and EM etc, you can use the command line and work the way you are used to.

Anyway, back on course... when you have the instance up and running it's time to have some fun with it!

File Transfer to the Oracle Public Cloud

In ODI you can use the OdiSftpPut/Get tool in a package, procedure or KM to transfer data to/from the cloud. You can see in the example below the OdiSftpPut tools is being used to transfer a file 'm.csv' from the local filesystem (d:\data) to the directory (/home/oracle) in the cloud. The private key is specified in the property 'SSH Identity File' and the key file password is specified in 'Remote User Password'. The OS user to use for the ftp is specified as 'oracle' in the property 'Remote User Name'.

Very simple. The DBaaS instance has OS users created when initialized you can read more about the users 'opc' and 'oracle' in the DBaaS documentation.

Transforming Data in the Oracle Public Cloud

Mappings are used to transform data from one representation to another. In this example you will see how the file staged in the Oracle Public Cloud is integrated with an Oracle target - just like standard ODI on premise use cases. It is no different. Below you can see the image has the logical mapping at the top, with the file being mapped to an Oracle target table, then the middle part of the image shows the physical design, the map uses the LKM File to Oracle (External Table) KM to create an external table on top of the file in the cloud and then the target is integrated with the Oracle Insert KM. 

When I execute the mapping all of the statements to transform are executed in the OPC - in this particular design everything is executed inside the Oracle database.

The ODI data server definition is using a custom driver (here) which extends the Oracle JDBC driver. The driver creates a SSH tunnel between the host executing the connect and the instance in the cloud. This means all ODI objects such as procedures, mappings and so forth that execute statements on regular Oracle systems can execute them on the cloud instances too. I actually created my demonstration schemas and granted all the permissions using a procedure in ODI. The procedure is shown below, see the snippet of the statements creating the users - the target logical schema was my DBAAS_INSTANCE.

Let's dig under the covers and have a look at how the physical schema is defined. You'll need the driver, and have it copied into your oracledi/userlib directory (or wherever your agent is installed if using an agent). You can then define the connection, specify the database user name and password for that database user;

Then you specify the driver, the driver you need to download and mentioned above. The URL is of the form of the Oracle JDBC driver. The difference is in how you specify the host, port and sid/service. The sid/service are your actual cloud service details. Since we are using the SSH tunnel technique, we actually specify the local host and a port number (default 5656) on the local host.

The properties to configure the SSH tunnel are defined either in the properties panel or in a file specified in the properties panel. I've decided here to use the file approach, so can specify the file name in the property propertiesFile.

In my example, this file contains;

  • sslUser=oracle
  • sslHost=<my_cloud_ip_address>
  • sslRHost=<my_cloud_ip_address>
  • sslRPort=1521
  • sslPassword=my_private_key_password
  • sslPrivateKey=D:\\credentials\\dbcloud12c_private_key_openssh.ppk

That is all that is needed and you can be very creative using all the powers of Oracle in the cloud and ODI for integration. Here is a summary of the properties supported by the driver.

Property Name Property Description
sslUser The OS user to connect via SSL with.
sslHost The address of the host to SSL to.
sslRHost The tunnel can be made between the client through the SSL host to this host. In my case this was the same as the SSL host.
sslRPort The port to tunnel to. The Oracle listener is often run on 1521, so this is the default if this property is not specified.
sslPassword The password for the private key file. In ODI you must use OpenSSH formatted private key file.
sslPrivateKey The SSL private key file location.
sslLPort By default the local port used is 5656, it can be changed with this property. You must reference this port number in the URL also.

The driver is a fairly simple wrapper around the Oracle JDBC driver, it leverages SSL tunneling to forward requests on a secure port to the Oracle TNS listener. This technique enables a very familiar way of connecting and interacting with the Oracle database, the driver is on java.net and is available to try and get feedback on. So try it and let us know what you think. Familiarity and consistency are very important both from the stance of the tooling and leveraging existing knowledge (including modules). This allows ODI users to work with the Oracle Public Cloud DBaaS instance just as they do with their on premise systems. Have fun!

Monday Oct 27, 2014

Updated Statement of Direction for Oracle Business Intelligence Analytics (OBIA)

Oracle's product strategy around the Oracle Business Intelligence Analytics (OBIA) has been published this October in the latest Statement of Direction.

Interesting points relative to the BI Applications around data integration:

  • Oracle’s strategic development for ELT for BI Applications will focus on the Oracle Data Integrator and related technologies. Since the fielding of the ODI compatible version of BI Applications in the 11g series, customers have realized substantial financial and operational benefits from reduced time to value and improved speed of operations. Oracle continues to evolve and develop ODI, and Oracle’s BI Applications will take advantage of the latest capabilities as they become available.

  • Oracle will continue to support the 7.9.6.x product series according to the Oracle Lifetime Support policy including certifications of databases, operating systems, and enabling 3rd  party technologies.  However, Oracle will no longer develop new content for this series, nor extend the 7.9.6.x support or any series based on an ETL architecture with Informatica.

You can find the related blog entry with additional details from the BI Team here.

Raymond James Financial Leverages Oracle Data Integration

Hot off the press! 

Raymond James Financial shares how it uses Oracle Data Integrator and Oracle GoldenGate in establishing an enterprise information platform that integrates data from multiple heterogeneous sources such as HP NonStop, Microsoft SQL Server, etc and provides a consolidated company view.  This solution provides quicker access to actionable, timely data that helps operational efficiency for its 6,000 financial advisers by enabling repeatable processes in data migration and loading.

Read the press release.

For more information on this solution, this blog may be of interest also.

Friday Oct 24, 2014

Automating ODI development tasks using the SDK

By Ayush Dash, Oracle Consulting Services

Oracle Data Integrator (ODI) 11g uses Interfaces to move data from a source to a target datastore. ODI Studio is a very convenient drag and drop UI to build, test and execute such interfaces. These interfaces can have different processing logic and complex transformations for disparate requirements, but there could be interfaces which behave in the exact same manner except the source and target are different.

Let’s say, I have these requirements defined, able to identify the different buckets of processing required and develop respective interfaces. That’s easily done! However, if I change the requirement such that I need 10 interfaces for each bucket, the requirement gets little complex and am I face increased level of effort. What about 100 such interfaces for each buckets? Much more effort required now! It’s the same repetitive set of tasks but it needs to be done for each interface for each bucket. The problem we face here is to somehow expedite and automate the entire sequence of steps for each bucket and reduce the redundant, manual development of ODI interfaces. As the number of interface grows, our problem (increase in effort) compounds.

Note, this is not limited to interfaces only, it can be extended to generate scenarios, packages etc.

Use Case:

In one of my ODI engagements, we had the below requirements with aggressive timelines.

  1. Incremental Loads from a Source Database to Incremental Database. (ODI interfaces)
  2. Data masking on Incremental Database (not an ODI task)
  3. Incremental loads from Incremental Database to Target Database. (ODI Interfaces)

This had to be done for Oracle and PeopleSoft (2 buckets) and a total of 2300 tables (So a total of 4600 interfaces. 2300 interfaces for step 1 and 2300 for step 3) and eventually respective scenarios.

ODI SDK Groovy Scripts:

ODI Studio provides a Groovy Editor; a java based scripting language as part of its install. Groovy can be leveraged to work with ODI SDK and build automation scripts. Below is the list of scripts;

  • CreateProject – Creates an ODI Project with a ProjectName and FolderName.
  • ImportKnowledgeModules – Imports the specified Knowledgemodules to the KM directories.
  • CreateModels – Creates the source and target Models for existing Datastores.
  • CreateModelsandDatastore – Creates Datastores and Models.
  • CreateInterfaceIterative – Iterates through all the Source Datastores and generates an interface for each with respective Target Datastores.
  • CreateInterfaceIterativeandSetKMOptions – Creates Interfaces and set a KM options iteratively.
  • CreateScenario – Create scenarios for all the interfaces.
  • ExecuteScenario – Executes all the scenarios under all the interfaces.
  • CountInterface – Counts the no. of interfaces, can be used al validation.

The scripts and guide have been uploaded to the Oracle Data Integration project on Java.net: https://java.net/projects/oracledi.

All the scripts can be downloaded from here: https://java.net/projects/oracledi/downloads/download/ODI/SDK%20Samples/ODI%2011g%20SDK%20Automation/Automation%20Scripts/Automation%20Scripts.zip

Please refer to the ODI SDK Automation Guide for detailed steps: https://java.net/projects/oracledi/downloads/download/ODI/SDK%20Samples/ODI%2011g%20SDK%20Automation/ODI%2011g%20SDK%20Automation%20Guide.doc

Thursday Oct 23, 2014

Big Data Governance Webcast

Earlier during the week we announced Oracle Enterprise Metadata Management (OEMM). Join us as we follow up the release with a webcast where we discuss the pressing issue of Data Governance and how it applies to Big Data. Jeff Pollock, Vice President of Product Management, talks about 

  • Applying Governance to Big Data 
  • The role that managing metadata plays in Governance
  • How data quality fits into the whole Governance framework and 
  • The actual product Oracle Enterprise Metadata Management.

Register here and join us for the webcast on the 30th.

Monday Oct 20, 2014

Announcing Availability of Oracle Enterprise Metadata Management

Oracle today announced the general availability of Oracle Enterprise Metadata Management (OEMM), Oracle's comprehensive Metadata Management technology for Data Governance. With this release Oracle stresses the importance that it lays on it's product strategy that not just offers best in class Data Integration solutions like Oracle Data Integrator (ODI), Oracle GoldenGate (OGG) and Oracle Enterprise Data Quality (OEDQ), but also on technology that ties together business initiatives like governance.

Data Governance Considerations

Organizations have been struggling to impose credible governance onto their data for long with ad-hoc processes and technologies that are unwieldy  and unscalable. There were a number of reasons why this was the case.

  • a. Data Governance cannot be done without managing metadata.
  • b. Data Governance cannot be done without extending across all platforms irrespective of technologies.
  • c. Data Governance cannot be done without a business and IT friendly interface.

Complete Stewardship -  Data Transparency from Source to Report

The biggest advantages of having an airtight Data Governance program is to reduce data risk, increase security and to manage your organization's Data Life-cycle. Any governance tool should be able to surface lineage, impact analysis and data flow not just within a Business Analytics, or within a Data Ware house but across all these systems, no matter what technology one is using. This increased transparency assesses accurately risks and impacts during changes to data. 


Data Flow Diagram across platforms.

With a focus on stewardship OEMM is designed to be intuitive and search based. It's search catalog allows easy browsing of all objects with collaboration and social features for the Data Steward.

 Search based catalog and Business Glossary for easy browsing of objects.

Big Data Governance

OEMM along with Oracle Data Integrator provides a powerful combination to govern Big Data standards including HBase, SQOOP and JSON. With ODI providing complete support to these data standards for Data loading and transformation, OEMM harvests the ODI metadata to stitch together a complete data map that even traverses through any Big Data Reservoir that organizations have in place. 

Oracle and 3rd Party Metadata

OEMM is truly heterogeneous. It is designed to pull in and manage metadata from Oracle and 3rd party Data Bases, Data Warehouses, ETL, Business Intelligence, and other Reporting Tools. 

Visit the OEMM homepage for more information about Oracle Enterprise Metadata Management.

Friday Oct 17, 2014

Upcoming Webinar: Data Transformation and Acquisition Techniques, to Handle Petabytes of Data

Many organizations have become aware of the importance of big data technologies, such as Apache Hadoop but are struggling to determine the right architecture to integrate it with their existing analytics and data processing infrastructure. As companies are implementing Hadoop, they need to learn new skills and languages, which can impact developer productivity. Often times they resort to hand-coded solutions which can be brittle, impact the productivity of the developer and the efficiency of the Hadoop cluster.

To truly tap into the business benefits of the big data solutions, it’s necessary to ensure that the business and IT have simple tools-based methods to get data in, change and transform it, and keep it continuously updated with their data warehouse.

In this webinar you’ll learn how the Oracle and Hortonworks solution can:

  • Accelerate developer productivity
  • Optimize data transformation workloads for on Hadoop
  • Lower cost of data storage and processing
  • Minimize risks in deployment of big data projects
  • Provide proven industrial scale tooling for data integration projects

We will also discuss how technologies from both Oracle and Hortonworks can deploy the big data reservoir or data lake, an efficient cost-effective way to handle petabyte-scale data staging, transformations, and aged data requirements while reclaiming compute power and storage from your existing data warehouse.

Speakers:
Jeff Pollock, Vice President, Oracle
Tim Hall, Vice President, Hortonworks

Hosted by:
Tim Matteson
, Co-Founder, Data Science Central

Click Here to Register.

Wednesday Oct 15, 2014

Oracle Data Integrator Certified with Hortonworks HDP 2.1

To often companies fall into what they perceive is the path of least resistance by using custom, hand-coded methods to create big data solutions but with the rush to production these hand coded solutions more often perform slower and are more costly to maintain.   To truly tap into the business benefits of the big data solutions, a simple tools based solutions is required to move large volumes of data into Hadoop and efficiently transform it without the need for costly mid-tier servers.    The Oracle Data Integration Solutions team is pleased to announce the certification of Oracle Data Integrator with Hortonworks HDP 2.1. 

This collaboration between both the Oracle Data Integrator and Hortonworks teams will provide customers a familiar and comprehensive data integration platform for Hadoop covering high-volume, high-performance batch-loads,  agile transformations using the power of Hadoop and a superior developer experience with the flow-based declarative user interface of Oracle Data Integrator. 

To learn more, click here.    

Also, on November 11th, 2014 Jeff Pollock, VP Oracle Data Integration Solutions and Tim Hall, VP of Product Management Hortonworks will be hosting a joint webinar to discuss the certification and how technologies from both Oracle and Hortonworks can be used to deploy big data reservoirs.    To register, click here

Friday Oct 10, 2014

Oracle Data Integrator Webcast Archives

Check out the recorded webcasts on Oracle Data Integrator! 

Each month the Product Management Team hosts a themed session for your viewing pleasure.  Recent topics include Oracle Data Integrator (ODI) and Big Data, Oracle Data Integrator (ODI) and Oracle GoldenGate Integration, BigData Lite, the Oracle Warehouse Builder (OWB) Migration Utility, the Management Pack for Oracle Data Integrator (ODI), along with other various topics focused on Oracle Data Integrator (ODI) 12c.

You can find the Oracle Data Integrator (ODI) Webcast Archives here.

Take a look at the individual sessions:

The webcasts are publicized on the ODI OTN Forum if you want to view them live.  You will find the announcement at the top of the page, with the title and details for the upcoming webcast.

Thank you – and happy listening!

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