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  • SQL Server 2012 Integration Services- Using Environments in Package Execution

    SQL Server 2012 Integration Services offers several different options for deploying and storing SSIS packages along with their associated projects, two of which are directly related to two deployment models available in SQL Server Data Tools console. Marcin Policht presents one of these methods, which deals with packages deployed using Project Deployment Model and leverages newly introduced Environments.

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  • SQL Server 2012 Integration Services - Implementing Package Security using Access Control

    SQL Server 2012 Integration Services offers a wide range of powerful features that allow you to streamline and automate tasks involving data extraction, transformation, and loading. However, incorporating these features into your existing business intelligence framework frequently necessitates additional security measures ensuring that data which is being processed remains protected from unauthorized access.

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  • Application Integration Architecture – Bringing It All Together - Part 1

    Oracle's Application Integration Architecture (AIA) provides Oracle customers,prospects and partners with the capability to more easily integrate and orchestrate information and transactions across multiple systems. Learn more about Oracle AIA and get an update on new and planned integrations from Jose Lazares,Vice President, Oracle Applications Development.

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  • Application Integration Architecture – Bringing It All Together - Part 2

    Oracle's Application Integration Architecture (AIA) provides Oracle customers,prospects and partners with the capability to more easily integrate and orchestrate information and transactions across multiple systems. Learn more about Oracle AIA and get an update on new and planned integrations from Jose Lazares,Vice President, Oracle Applications Development.

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  • SQL Server 2012 Integration Services - Project Deployment

    SQL Server 2012 Integration Services parameters introduce a new way of dealing with package development, deployment, and execution. In order to truly appreciate their relevance, it is necessary to take a look at the new Project Deployment Model. Get smart with SQL Backup ProGet faster, smaller backups with integrated verification.Quickly and easily DBCC CHECKDB your backups. Learn more.

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  • Data Mining: Part 14 Export DMX results with Integration Services

    In this chapter we will explain how to work with Data Mining models and the Integration Services. Specifically, we will talk about the Data Mining Query Task in SSIS. Free ebook "TortoiseSVN and Subversion Cookbook - Oracle Edition"Use these recipes to work better, faster, and do things you never knew you could do with SVN. If you're new to source control, this book provides a concise guide to getting the most out of Subversion. Download it for free.

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  • ODI and OBIEE 11g Integration

    - by David Allan
    Here we will see some of the connectivity options to OBIEE 11g using the JDBC driver. You’ll see based upon some connection properties how the physical or presentation layers can be utilized. In the integrators guide for OBIEE 11g you will find a brief statement indicating that there actually is a JDBC driver for OBIEE. In OBIEE 11g its now possible to connect directly to the physical layer, Venkat has an informative post here on this topic. In ODI 11g the Oracle BI technology is shipped with the product along with KMs for reverse engineering, and using OBIEE models for a data source. When you install OBIEE in 11g a light weight demonstration application is preinstalled in the server, when you open this in the BI Administration tool we see the regular 3 panel view within the administration tool. To interrogate this system via JDBC (just like ODI does using the KMs) need a couple of things; the JDBC driver from OBIEE 11g, a java client program and the credentials. In my java client program I want to connect to the OBIEE system, when I connect I can interrogate what the JDBC driver presents for the metadata. The metadata projected via the JDBC connection’s DatabaseMetadata changes depending on whether the property NQ_SESSION.SELECTPHYSICAL is set when the java client connects. Let’s use the sample app to illustrate. I have a java client program here that will print out the tables in the DatabaseMetadata, it will also output the catalog and schema. For example if I execute without any special JDBC properties as follows; java -classpath .;%BIHOMEDIR%\clients\bijdbc.jar meta_jdbc oracle.bi.jdbc.AnaJdbcDriver jdbc:oraclebi://localhost:9703/ weblogic mypass Then I get the following returned representing the presentation layer, the sample I used is XML, and has no schema; Catalog Schema Table Sample Sales Lite null Base Facts Sample Sales Lite null Calculated Facts …     Sample Targets Lite null Base Facts …     Now if I execute with the only difference being the JDBC property NQ_SESSION.SELECTPHYSICAL with the value Yes, then I see a different set of values representing the physical layer in OBIEE; java -classpath .;%BIHOMEDIR%\clients\bijdbc.jar meta_jdbc oracle.bi.jdbc.AnaJdbcDriver jdbc:oraclebi://localhost:9703/ weblogic mypass NQ_SESSION.SELECTPHYSICAL=Yes The following is returned; Catalog Schema Table Sample App Lite Data null D01 Time Day Grain Sample App Lite Data null F10 Revenue Facts (Order grain) …     System DB (Update me)     …     If this was a database system such as Oracle, the catalog value would be the OBIEE database name and the schema would be the Oracle database schema. Other systems which have real catalog structure such as SQLServer would use its catalog value. Its this ‘Catalog’ and ‘Schema’ value that is important when integration OBIEE with ODI. For the demonstration application in OBIEE 11g, the following illustration shows how the information from OBIEE is related via the JDBC driver through to ODI. In the XML example above, within ODI’s physical schema definition on the right, we leave the schema blank since the XML data source has no schema. When I did this at first, I left the default value that ODI places in the Schema field since which was ‘<Undefined>’ (like image below) but this string is actually used in the RKM so ended up not finding any tables in this schema! Entering an empty string resolved this. Below we see a regular Oracle database example that has the database, schema, physical table structure, and how this is defined in ODI.   Remember back to the physical versus presentation layer usage when we passed the special property, well to do this in ODI, the data server has a panel for properties where you can define key/value pairs. So if you want to select physical objects from the OBIEE server, then you must set this property. An additional changed in ODI 11g is the OBIEE connection pool support, this has been implemented via a ‘Connection Pool’ flex field for the Oracle BI data server. So here you set the connection pool name from the OBIEE system that you specifically want to use and this is used by the Oracle BI to Oracle (DBLINK) LKM, so if you are using this you must set this flex field. Hopefully a useful insight into some of the mechanics of how this hangs together.

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  • Big Data: Size isn’t everything

    - by Simon Elliston Ball
    Big Data has a big problem; it’s the word “Big”. These days, a quick Google search will uncover terabytes of negative opinion about the futility of relying on huge volumes of data to produce magical, meaningful insight. There are also many clichéd but correct assertions about the difficulties of correlation versus causation, in massive data sets. In reading some of these pieces, I begin to understand how climatologists must feel when people complain ironically about “global warming” during snowfall. Big Data has a name problem. There is a lot more to it than size. Shape, Speed, and…err…Veracity are also key elements (now I understand why Gartner and the gang went with V’s instead of S’s). The need to handle data of different shapes (Variety) is not new. Data developers have always had to mold strange-shaped data into our reporting systems, integrating with semi-structured sources, and even straying into full-text searching. However, what we lacked was an easy way to add semi-structured and unstructured data to our arsenal. New “Big Data” tools such as MongoDB, and other NoSQL (Not Only SQL) databases, or a graph database like Neo4J, fill this gap. Still, to many, they simply introduce noise to the clean signal that is their sensibly normalized data structures. What about speed (Velocity)? It’s not just high frequency trading that generates data faster than a single system can handle. Many other applications need to make trade-offs that traditional databases won’t, in order to cope with high data insert speeds, or to extract quickly the required information from data streams. Unfortunately, many people equate Big Data with the Hadoop platform, whose batch driven queries and job processing queues have little to do with “velocity”. StreamInsight, Esper and Tibco BusinessEvents are examples of Big Data tools designed to handle high-velocity data streams. Again, the name doesn’t do the discipline of Big Data any favors. Ultimately, though, does analyzing fast moving data produce insights as useful as the ones we get through a more considered approach, enabled by traditional BI? Finally, we have Veracity and Value. In many ways, these additions to the classic Volume, Velocity and Variety trio acknowledge the criticism that without high-quality data and genuinely valuable outputs then data, big or otherwise, is worthless. As a discipline, Big Data has recognized this, and data quality and cleaning tools are starting to appear to support it. Rather than simply decrying the irrelevance of Volume, we need as a profession to focus how to improve Veracity and Value. Perhaps we should just declare the ‘Big’ silent, embrace these new data tools and help develop better practices for their use, just as we did the good old RDBMS? What does Big Data mean to you? Which V gives your business the most pain, or the most value? Do you see these new tools as a useful addition to the BI toolbox, or are they just enabling a dangerous trend to find ghosts in the noise?

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  • Know your Data Lineage

    - by Simon Elliston Ball
    An academic paper without the footnotes isn’t an academic paper. Journalists wouldn’t base a news article on facts that they can’t verify. So why would anyone publish reports without being able to say where the data has come from and be confident of its quality, in other words, without knowing its lineage. (sometimes referred to as ‘provenance’ or ‘pedigree’) The number and variety of data sources, both traditional and new, increases inexorably. Data comes clean or dirty, processed or raw, unimpeachable or entirely fabricated. On its journey to our report, from its source, the data can travel through a network of interconnected pipes, passing through numerous distinct systems, each managed by different people. At each point along the pipeline, it can be changed, filtered, aggregated and combined. When the data finally emerges, how can we be sure that it is right? How can we be certain that no part of the data collection was based on incorrect assumptions, that key data points haven’t been left out, or that the sources are good? Even when we’re using data science to give us an approximate or probable answer, we cannot have any confidence in the results without confidence in the data from which it came. You need to know what has been done to your data, where it came from, and who is responsible for each stage of the analysis. This information represents your data lineage; it is your stack-trace. If you’re an analyst, suspicious of a number, it tells you why the number is there and how it got there. If you’re a developer, working on a pipeline, it provides the context you need to track down the bug. If you’re a manager, or an auditor, it lets you know the right things are being done. Lineage tracking is part of good data governance. Most audit and lineage systems require you to buy into their whole structure. If you are using Hadoop for your data storage and processing, then tools like Falcon allow you to track lineage, as long as you are using Falcon to write and run the pipeline. It can mean learning a new way of running your jobs (or using some sort of proxy), and even a distinct way of writing your queries. Other Hadoop tools provide a lot of operational and audit information, spread throughout the many logs produced by Hive, Sqoop, MapReduce and all the various moving parts that make up the eco-system. To get a full picture of what’s going on in your Hadoop system you need to capture both Falcon lineage and the data-exhaust of other tools that Falcon can’t orchestrate. However, the problem is bigger even that that. Often, Hadoop is just one piece in a larger processing workflow. The next step of the challenge is how you bind together the lineage metadata describing what happened before and after Hadoop, where ‘after’ could be  a data analysis environment like R, an application, or even directly into an end-user tool such as Tableau or Excel. One possibility is to push as much as you can of your key analytics into Hadoop, but would you give up the power, and familiarity of your existing tools in return for a reliable way of tracking lineage? Lineage and auditing should work consistently, automatically and quietly, allowing users to access their data with any tool they require to use. The real solution, therefore, is to create a consistent method by which to bring lineage data from these data various disparate sources into the data analysis platform that you use, rather than being forced to use the tool that manages the pipeline for the lineage and a different tool for the data analysis. The key is to keep your logs, keep your audit data, from every source, bring them together and use the data analysis tools to trace the paths from raw data to the answer that data analysis provides.

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  • Should integration testing of DAOs be done in an application server?

    - by HDave
    I have a three tier application under development and am creating integration tests for DAOs in the persistence layer. When the application runs in Websphere or JBoss I expect to use the connection pooling and transaction manager of those application servers. When the application runs in Tomcat or Jetty, we'll be using C3P0 for pooling and Atomikos for transactions. Because of these different subsystems, should the DAO's be tested in a fully configured application server environment or should we handle those concerns when integration testing the service layer? Currently we plan on setting up a simple JDBC data source with non-JTA (i.e. resource-local) transactions for DAO integration testing, thus no application server is involved....but this leaves me wondering about environmental problems we won't uncover.

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  • NSURLConnection receives data even if no data was thrown back

    - by Anna Fortuna
    Let me explain my situation. Currently, I am experimenting long-polling using NSURLConnection. I found this and I decided to try it. What I do is send a request to the server with a timeout interval of 300 secs. (or 5 mins.) Here is a code snippet: NSURL *url = [NSURL URLWithString:urlString]; NSURLRequest *request = [NSURLRequest requestWithURL:url cachePolicy:NSURLCacheStorageAllowedInMemoryOnly timeoutInterval:300]; NSData *data = [NSURLConnection sendSynchronousRequest:request returningResponse:&resp error:&err]; Now I want to test if the connection will "hold" the request if no data was thrown back from the server, so what I did was this: if (data != nil) [self performSelectorOnMainThread:@selector(dataReceived:) withObject:data waitUntilDone:YES]; And the function dataReceived: looks like this: - (void)dataReceived:(NSData *)data { NSLog(@"DATA RECEIVED!"); NSString *string = [NSString stringWithUTF8String:[data bytes]]; NSLog(@"THE DATA: %@", string); } Server-side, I created a function that will return a data once it fits the arguments and returns none if nothing fits. Here is a snippet of the PHP function: function retrieveMessages($vardata) { if (!empty($vardata)) { $result = check_data($vardata) //check_data is the function which returns 1 if $vardata //fits the arguments, and 0 if it fails to fit if ($result == 1) { $jsonArray = array('Data' => $vardata); echo json_encode($jsonArray); } } } As you can see, the function will only return data if the $result is equal to 1. However, even if the function returns nothing, NSURLConnection will still perform the function dataReceived: meaning the NSURLConnection still receives data, albeit an empty one. So can anyone help me here? How will I perform long-polling using NSURLConnection? Basically, I want to maintain the connection as long as no data is returned. So how will I do it? NOTE: I am new to PHP, so if my code is wrong, please point it out so I can correct it.

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  • How to maintain an ordered table with Core Data (or SQL) with insertions/deletions?

    - by Jean-Denis Muys
    This question is in the context of Core Data, but if I am not mistaken, it applies equally well to a more general SQL case. I want to maintain an ordered table using Core Data, with the possibility for the user to: reorder rows insert new lines anywhere delete any existing line What's the best data model to do that? I can see two ways: 1) Model it as an array: I add an int position property to my entity 2) Model it as a linked list: I add two one-to-one relations, next and previous from my entity to itself 1) makes it easy to sort, but painful to insert or delete as you then have to update the position of all objects that come after 2) makes it easy to insert or delete, but very difficult to sort. In fact, I don't think I know how to express a Sort Descriptor (SQL ORDER BY clause) for that case. Now I can imagine a variation on 1): 3) add an int ordering property to the entity, but instead of having it count one-by-one, have it count 100 by 100 (for example). Then inserting is as simple as finding any number between the ordering of the previous and next existing objects. The expensive renumbering only has to occur when the 100 holes have been filled. Making that property a float rather than an int makes it even better: it's almost always possible to find a new float midway between two floats. Am I on the right track with solution 3), or is there something smarter?

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  • How can I scrape specific data from a website

    - by Stoney
    I'm trying to scrape data from a website for research. The urls are nicely organized in an example.com/x format, with x as an ascending number and all of the pages are structured in the same way. I just need to grab certain headings and a few numbers which are always in the same locations. I'll then need to get this data into structured form for analysis in Excel. I have used wget before to download pages, but I can't figure out how to grab specific lines of text. Excel has a feature to grab data from the web (Data-From Web) but from what I can see it only allows me to download tables. Unfortunately, the data I need is not in tables.

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  • How should I architect my Model and Data Access layer objects in my website?

    - by Robin Winslow
    I've been tasked with designing Data layer for a website at work, and I am very interested in architecture of code for the best flexibility, maintainability and readability. I am generally acutely aware of the value in completely separating out my actual Models from the Data Access layer, so that the Models are completely naive when it comes to Data Access. And in this case it's particularly useful to do this as the Models may be built from the Database or may be built from a Soap web service. So it seems to me to make sense to have Factories in my data access layer which create Model objects. So here's what I have so far (in my made-up pseudocode): class DataAccess.ProductsFromXml extends DataAccess.ProductFactory {} class DataAccess.ProductsFromDatabase extends DataAccess.ProductFactory {} These then get used in the controller in a fashion similar to the following: var xmlProductCreator = DataAccess.ProductsFromXml(xmlDataProvider); var databaseProductCreator = DataAccess.ProductsFromXml(xmlDataProvider); // Returns array of Product model objects var XmlProducts = databaseProductCreator.Products(); // Returns array of Product model objects var DbProducts = xmlProductCreator.Products(); So my question is, is this a good structure for my Data Access layer? Is it a good idea to use a Factory for building my Model objects from the data? Do you think I've misunderstood something? And are there any general patterns I should read up on for how to write my data access objects to create my Model objects?

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  • OAM OVD integration - Error Encounterd while performance test "LDAP response read timed out, timeout used:2000ms"

    - by siddhartha_sinha
    While working on OAM OVD integration for one of my client, I have been involved in the performance test of the products wherein I encountered OAM authentication failures while talking to OVD during heavy load. OAM logs revealed the following: oracle.security.am.common.policy.common.response.ResponseException: oracle.security.am.engines.common.identity.provider.exceptions.IdentityProviderException: OAMSSA-20012: Exception in getting user attributes for user : dummy_user1, idstore MyIdentityStore with exception javax.naming.NamingException: LDAP response read timed out, timeout used:2000ms.; remaining name 'ou=people,dc=oracle,dc=com' at oracle.security.am.common.policy.common.response.IdentityValueProvider.getUserAttribute(IdentityValueProvider.java:271) ... During the authentication and authorization process, OAM complains that the LDAP repository is taking too long to return user attributes.The default value is 2 seconds as can be seen from the exception, "2000ms". While troubleshooting the issue, it was found that we can increase the ldap read timeout in oam-config.xml.  For reference, the attribute to add in the oam-config.xml file is: <Setting Name="LdapReadTimeout" Type="xsd:string">2000</Setting> However it is not recommended to increase the time out unless it is absolutely necessary and ensure that back-end directory servers are working fine. Rather I took the path of tuning OVD in the following manner: 1) Navigate to ORACLE_INSTANCE/config/OPMN/opmn folder and edit opmn.xml. Search for <data id="java-options" ………> and edit the contents of the file with the highlighted items: <category id="start-options"><data id="java-bin" value="$ORACLE_HOME/jdk/bin/java"/><data id="java-options" value="-server -Xms1024m -Xmx1024m -Dvde.soTimeoutBackend=0 -Didm.oracle.home=$ORACLE_HOME -Dcommon.components.home=$ORACLE_HOME/../oracle_common -XX:+PrintGCDetails -XX:+PrintGCDateStamps -Xloggc:/opt/bea/Middleware/asinst_1/diagnostics/logs/OVD/ovd1/ovdGClog.log -XX:+UseConcMarkSweepGC -Doracle.security.jps.config=$ORACLE_INSTANCE/config/JPS/jps-config-jse.xml"/><data id="java-classpath" value="$ORACLE_HOME/ovd/jlib/vde.jar$:$ORACLE_HOME/jdbc/lib/ojdbc6.jar"/></category></module-data><stop timeout="120"/><ping interval="60"/></process-type> When the system is busy, a ping from the Oracle Process Manager and Notification Server (OPMN) to Oracle Virtual Directory may fail. As a result, OPMN will restart Oracle Virtual Directory after 20 seconds (the default ping interval). To avoid this, consider increasing the ping interval to 60 seconds or more. 2) Navigate to ORACLE_INSTANCE/config/OVD/ovd1 folder.Open listeners.os_xml file and perform the following changes: · Search for <ldap id=”Ldap Endpoint”…….> and point the cursor to that line. · Change threads count to 200. · Change anonymous bind to Deny. · Change workQueueCapacity to 8096. Add a new parameter <useNIO> and set its value to false viz: <useNIO>false</useNio> Snippet: <ldap version="8" id="LDAP Endpoint"> ....... .......  <socketOptions><backlog>128</backlog>         <reuseAddress>false</reuseAddress>         <keepAlive>false</keepAlive>         <tcpNoDelay>true</tcpNoDelay>         <readTimeout>0</readTimeout>      </socketOptions> <useNIO>false</useNIO></ldap> Restart OVD server. For more information on OVD tuneup refer to http://docs.oracle.com/cd/E25054_01/core.1111/e10108/ovd.htm. Please Note: There were few patches released from OAM side for performance tune-up as well. Will provide the updates shortly !!!

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  • Calculating percentiles in Excel with "buckets" data instead of the data list itself

    - by G B
    I have a bunch of data in Excel that I need to get certain percentile information from. The problem is that instead of having the data set made up of each value, I instead have info on the number of or "bucket" data. For example, imagine that my actual data set looks like this: 1,1,2,2,2,2,3,3,4,4,4 The data set that I have is this: Value No. of occurrences 1 2 2 4 3 2 4 3 Is there an easy way for me to calculate percentile information (as well as the median) without having to explode the summary data out to full data set? (Once I did that, I know that I could just use the Percentile(A1:A5, p) function) This is important because my data set is very large. If I exploded the data out, I would have hundreds of thousands of rows and I would have to do it for a couple of hundred data sets. Help!

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  • How do I setup a WCF Data Service with an ADO.NET Entity Entity Model in another assembly?

    - by lsb
    Hi! I have an ASP.NET 4.0 website that has an Entity Data Model hooked up to WCF Data Service. When the Service and Model are in the same assembly everything works. Unfortunately, when I move the Model to another "shared" assembly (and change the namespace) the service compiles but throws a 500 error when launched in a browser. The reason I want to have the Model in a common assembly (lets call it RiaTest.Shared) is that I want share common validation code between the client and service (by checking "Reuse types in referenced assemblies" in the Advanced tab of the Add Service Reference dialog). Anyway, I've spent a couple of hours on this to no avail so any help in the regard would be appreciated...

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  • Open Data, Government and Transparency

    - by Tori Wieldt
    A new track at TDC (The Developer's Conference in Sao Paulo, Brazil) is titled Open Data. It deals with open data, government and transparency. Saturday will be a "transparency hacker day" where developers are invited to create applications using open data from the Brazilian government.  Alexandre Gomes, co-lead of the track, says "I want to inspire developers to become "Civic hackers:" developers who create apps to make society better." It is a chance for developers to do well and do good. There are many opportunities for developers, including monitoring government expenditures and getting citizens involved via social networks. The open data movement is growing worldwide. One initiative, the Open Government Partnership, is working to make government data easier to find and access. Making this data easily available means that with the right applications, it will be easier for people to make decisions and suggestions about government policies based on detailed information. Last April, the Open Government Partnership held its annual meeting in Brasilia, the capitol of Brazil. It was a great success showcasing the innovative work being done in open data by governments, civil societies and individuals around the world. For example, Bulgaria now publishes daily data on budget spending for all public institutions. Alexandre Gomes Explains Open Data At TDC, the Open Data track will include a presentation of examples of successful open data projects, an introduction to the semantic web, how to handle big data sets, techniques of data visualization, and how to design APIs.The other track lead is Christian Moryah Miranda, a systems analyst for the Brazilian Government's Ministry of Planning. "The Brazilian government wholeheartedly supports this effort. In order to make our data available to the public, it forces us to be more consistent with our data across ministries, and that's a good step forward for us," he said. He explained the government knows they cannot achieve everything they would like without help from the public. "It is not the government versus the people, rather citizens are partners with the government, and together we can achieve great things!" Miranda exclaimed. Saturday at TDC will be a "transparency hacker day" where developers will be invited to create applications using open data from the Brazilian government. Attendees are invited to pitch their ideas, work in small groups, and present their project at the end of the conference. "For example," Gomes said, "the Brazilian government just released the salaries of all government employees and I can't wait to see what developers can do with that." Resources Open Government Partnership  U.S. Government Open Data ProjectBrazilian Government Open Data ProjectU.K. Government Open Data Project 2012 International Open Government Data Conference 

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  • Master Data Management and Cloud Computing

    - by david.butler(at)oracle.com
    Cloud Computing is all the rage these days. There are many reasons why this is so. But like its predecessor, Service Oriented Architecture, it can fall on hard times if the underlying data is left unmanaged. Master Data Management is the perfect Cloud companion. It can materially increase the chances for successful Cloud initiatives. In this blog, I'll review the nature of the Cloud and show how MDM fits in.   Here's the National Institute of Standards and Technology Cloud definition: •          Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction.   Cloud architectures have three main layers: applications or Software as a Service (SaaS), Platforms as a Service (PaaS), and Infrastructure as a Service (IaaS). SaaS generally refers to applications that are delivered to end-users over the Internet. Oracle CRM On Demand is an example of a SaaS application. Today there are hundreds of SaaS providers covering a wide variety of applications including Salesforce.com, Workday, and Netsuite. Oracle MDM applications are located in this layer of Oracle's On Demand enterprise Cloud platform. We call it Master Data as a Service (MDaaS). PaaS generally refers to an application deployment platform delivered as a service. They are often built on a grid computing architecture and include database and middleware. Oracle Fusion Middleware is in this category and includes the SOA and Data Integration products used to connect SaaS applications including MDM. Finally, IaaS generally refers to computing hardware (servers, storage and network) delivered as a service.  This typically includes the associated software as well: operating systems, virtualization, clustering, etc.    Cloud Computing benefits are compelling for a large number of organizations. These include significant cost savings, increased flexibility, and fast deployments. Cost advantages include paying for just what you use. This is especially critical for organizations with variable or seasonal usage. Companies don't have to invest to support peak computing periods. Costs are also more predictable and controllable. Increased agility includes access to the latest technology and experts without making significant up front investments.   While Cloud Computing is certainly very alluring with a clear value proposition, it is not without its challenges. An IDC survey of 244 IT executives/CIOs and their line-of-business (LOB) colleagues identified a number of issues:   Security - 74% identified security as an issue involving data privacy and resource access control. Integration - 61% found that it is hard to integrate Cloud Apps with in-house applications. Operational Costs - 50% are worried that On Demand will actually cost more given the impact of poor data quality on the rest of the enterprise. Compliance - 49% felt that compliance with required regulatory, legal and general industry requirements (such as PCI, HIPAA and Sarbanes-Oxley) would be a major issue. When control is lost, the ability of a provider to directly manage how and where data is deployed, used and destroyed is negatively impacted.  There are others, but I singled out these four top issues because Master Data Management, properly incorporated into a Cloud Computing infrastructure, can significantly ameliorate all of these problems. Cloud Computing can literally rain raw data across the enterprise.   According to fellow blogger, Mike Ferguson, "the fracturing of data caused by the adoption of cloud computing raises the importance of MDM in keeping disparate data synchronized."   David Linthicum, CTO Blue Mountain Labs blogs that "the lack of MDM will become more of an issue as cloud computing rises. We're moving from complex federated on-premise systems, to complex federated on-premise and cloud-delivered systems."    Left unmanaged, non-standard, inconsistent, ungoverned data with questionable quality can pollute analytical systems, increase operational costs, and reduce the ROI in Cloud and On-Premise applications. As cloud computing becomes more relevant, and more data, applications, services, and processes are moved out to cloud computing platforms, the need for MDM becomes ever more important. Oracle's MDM suite is designed to deal with all four of the above Cloud issues listed in the IDC survey.   Security - MDM manages all master data attribute privacy and resource access control issues. Integration - MDM pre-integrates Cloud Apps with each other and with On Premise applications at the data level. Operational Costs - MDM significantly reduces operational costs by increasing data quality, thereby improving enterprise business processes efficiency. Compliance - MDM, with its built in Data Governance capabilities, insures that the data is governed according to organizational standards. This facilitates rapid and accurate reporting for compliance purposes. Oracle MDM creates governed high quality master data. A unified cleansed and standardized data view is produced. The Oracle Customer Hub creates a single view of the customer. The Oracle Product Hub creates high quality product data designed to support all go-to-market processes. Oracle Supplier Hub dramatically reduces the chances of 'supplier exceptions'. Oracle Site Hub masters locations. And Oracle Hyperion Data Relationship Management masters financial reference data and manages enterprise hierarchies across operational areas from ERP to EPM and CRM to SCM. Oracle Fusion Middleware connects Cloud and On Premise applications to MDM Hubs and brings high quality master data to your enterprise business processes.   An independent analyst once said "Poor data quality is like dirt on the windshield. You may be able to drive for a long time with slowly degrading vision, but at some point, you either have to stop and clear the windshield or risk everything."  Cloud Computing has the potential to significantly degrade data quality across the enterprise over time. Deploying a Master Data Management solution prior to or in conjunction with a move to the Cloud can insure that the data flowing into the enterprise from the Cloud is clean and governed. This will in turn insure that expected returns on the investment in Cloud Computing will be realized.       Oracle MDM has proven its metal in this area and has the customers to back that up. In fact, I will be hosting a webcast on Tuesday, April 10th at 10 am PT with one of our top Cloud customers, the Church Pension Group. They have moved all mainline applications to a hosted model and use Oracle MDM to insure the master data is managed and cleansed before it is propagated to other cloud and internal systems. I invite you join Martin Hossfeld, VP, IT Operations, and Danette Patterson, Enterprise Data Manager as they review business drivers for MDM and hosted applications, how they did it, the benefits achieved, and lessons learned. You can register for this free webcast here.  Hope to see you there.

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