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  • Oracle Enterprise Data Quality Adds Global Address Verification Capabilities for Greater Accuracy and Broader Location Coverage

    - by Mala Narasimharajan
    Data quality – has many flavors to it.  Product, Customer – you name the data domain and there’s data quality associated with it.  Address verification and data quality are a little different.  in that there is a tremendous amount of variation as well as nuance attached to it.  Specifically, what makes address verification challenging is that more often than not, addresses are incomplete, riddled with misspellings, incorrect postal codes are assigned to locations or non-address items are present.  Almost all data has locations, and accurate locations power a wealth of business processes: Customer Relationship Management, data quality, delivery of materials, goods or services, fraud detection, insurance risk assessment, data analytics, store and territory planning, and much more. Oracle Address Verification Server provides location-based services as well as deeper parsing and analysis capabilities for Oracle Enterprise Data Quality.  Specifically, Pre-integrated with the EDQ platform, Oracle Address Verification Server provides robust parsing, validation, as well as specialized location information for over 240 countries – all populated countries on Earth.  Oracle Enterprise Data Quality (EDQ) is a data quality platform, dedicated to address the distinct challenges of customer and product data quality, and performs advanced data profiling to identify and measure poor quality data and identify rule requirements, as well as semantic and pattern-based recognition to accurately parse and standardize data that is poorly structured.   EDQ is integrated with Oracle Master Data Management, including Oracle Customer Hub and Oracle Product Hub, as well as Oracle Data Integrator Enterprise Edition and Oracle CRM.  Address Verification Server provides key address verification services for Oracle CRM and Oracle Customer Hub.  In addition, Address Verification Server provides greater accuracy when handling address data due to its expanded sources and extensible knowledge repository, solid parsing across locales and countries as well as  adept handling of extraneous data in address fields.  For more information on Oracle Address Verification Server visit:  http://bit.ly/GMUE4H and http://bit.ly/GWf7U6

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  • Making Spring Data JPA work with DataNucleus (GAE) (Spring Boot)

    - by xybrek
    There are several hints that Spring Data works with Google App Engine like: http://tommysiu.blogspot.com/2014/01/spring-data-on-gae-part-1.html http://blog.eisele.net/2009/07/spring-300m3-on-google-appengine-with.html Much of the examples are not "Spring Boot" so I've been trying to retrofit things with it. However, I've been stuck with this error for days and days: [INFO] Caused by: java.lang.NullPointerException [INFO] at org.datanucleus.api.jpa.metamodel.SingularAttributeImpl.isVersion(SingularAttributeImpl.java:79) [INFO] at org.springframework.data.jpa.repository.support.JpaMetamodelEntityInformation.findVersionAttribute(JpaMetamodelEntityInformation.java:102) [INFO] at org.springframework.data.jpa.repository.support.JpaMetamodelEntityInformation.<init>(JpaMetamodelEntityInformation.java:79) [INFO] at org.springframework.data.jpa.repository.support.JpaEntityInformationSupport.getMetadata(JpaEntityInformationSupport.java:65) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getEntityInformation(JpaRepositoryFactory.java:149) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getTargetRepository(JpaRepositoryFactory.java:88) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactory.getTargetRepository(JpaRepositoryFactory.java:68) [INFO] at org.springframework.data.repository.core.support.RepositoryFactorySupport.getRepository(RepositoryFactorySupport.java:158) [INFO] at org.springframework.data.repository.core.support.RepositoryFactoryBeanSupport.initAndReturn(RepositoryFactoryBeanSupport.java:224) [INFO] at org.springframework.data.repository.core.support.RepositoryFactoryBeanSupport.afterPropertiesSet(RepositoryFactoryBeanSupport.java:210) [INFO] at org.springframework.data.jpa.repository.support.JpaRepositoryFactoryBean.afterPropertiesSet(JpaRepositoryFactoryBean.java:92) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory$6.run(AbstractAutowireCapableBeanFactory.java:1602) [INFO] at java.security.AccessController.doPrivileged(Native Method) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.invokeInitMethods(AbstractAutowireCapableBeanFactory.java:1599) [INFO] at org.springframework.beans.factory.support.AbstractAutowireCapableBeanFactory.initializeBean(AbstractAutowireCapableBeanFactory.java:1549) [INFO] ... 40 more Where, I'm trying to use Spring Data JPA with DataNucleus/AppEngine: @Configuration @ComponentScan @EnableJpaRepositories @EnableTransactionManagement class JpaApplicationConfig { private static final Logger logger = Logger .getLogger(JpaApplicationConfig.class.getName()); @Bean public EntityManagerFactory entityManagerFactory() { logger.info("Loading Entity Manager..."); return Persistence .createEntityManagerFactory("transactions-optional"); } @Bean public PlatformTransactionManager transactionManager() { logger.info("Loading Transaction Manager..."); final JpaTransactionManager txManager = new JpaTransactionManager(); txManager.setEntityManagerFactory(entityManagerFactory()); return txManager; } } I've tested Persistence.createEntityManagerFactory("transactions-optional"); to see if the app can persist using this EMF, well, it does, so I am sure that this EMF works fine. The problem is the "wiring" up with the Spring Data JPA, can anybody help?

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  • Parse and read data frame in C?

    - by user253656
    I am writing a program that reads the data from the serial port on Linux. The data are sent by another device with the following frame format: |start | Command | Data | CRC | End | |0x02 | 0x41 | (0-127 octets) | | 0x03| ---------------------------------------------------- The Data field contains 127 octets as shown and octet 1,2 contains one type of data; octet 3,4 contains another data. I need to get these data I know how to write and read data to and from a serial port in Linux, but it is just to write and read a simple string (like "ABD") My issue is that I do not know how to parse the data frame formatted as above so that I can: get the data in octet 1,2 in the Data field get the data in octet 3,4 in the Data field get the value in CRC field to check the consistency of the data Here the sample snip code that read and write a simple string from and to a serial port in Linux: int writeport(int fd, char *chars) { int len = strlen(chars); chars[len] = 0x0d; // stick a <CR> after the command chars[len+1] = 0x00; // terminate the string properly int n = write(fd, chars, strlen(chars)); if (n < 0) { fputs("write failed!\n", stderr); return 0; } return 1; } int readport(int fd, char *result) { int iIn = read(fd, result, 254); result[iIn-1] = 0x00; if (iIn < 0) { if (errno == EAGAIN) { printf("SERIAL EAGAIN ERROR\n"); return 0; } else { printf("SERIAL read error %d %s\n", errno, strerror(errno)); return 0; } } return 1; } Does anyone please have some ideas? Thanks all.

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  • Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 1

    - by rajbk
    The Open Data Protocol, referred to as OData, is a new data-sharing standard that breaks down silos and fosters an interoperative ecosystem for data consumers (clients) and producers (services) that is far more powerful than currently possible. It enables more applications to make sense of a broader set of data, and helps every data service and client add value to the whole ecosystem. WCF Data Services (previously known as ADO.NET Data Services), then, was the first Microsoft technology to support the Open Data Protocol in Visual Studio 2008 SP1. It provides developers with client libraries for .NET, Silverlight, AJAX, PHP and Java. Microsoft now also supports OData in SQL Server 2008 R2, Windows Azure Storage, Excel 2010 (through PowerPivot), and SharePoint 2010. Many other other applications in the works. * This post walks you through how to create an OData feed, define a shape for the data and pre-filter the data using Visual Studio 2010, WCF Data Services and the Entity Framework. A sample project is attached at the bottom of Part 2 of this post. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Create the Web Application File –› New –› Project, Select “ASP.NET Empty Web Application” Add the Entity Data Model Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “ADO.NET Entity Data Model” under "Data”. Name the Model “Northwind” and click “Add”.   In the “Choose Model Contents”, select “Generate Model From Database” and click “Next”   Define a connection to your database containing the Northwind database in the next screen. We are going to expose the Products table through our OData feed. Select “Products” in the “Choose your Database Object” screen.   Click “Finish”. We are done creating our Entity Data Model. Save the Northwind.edmx file created. Add the WCF Data Service Right click on the Web Application in the Solution Explorer and select “Add New Item..” Select “WCF Data Service” from the list and call the service “DataService” (creative, huh?). Click “Add”.   Enable Access to the Data Service Open the DataService.svc.cs class. The class is well commented and instructs us on the next steps. public class DataService : DataService< /* TODO: put your data source class name here */ > { // This method is called only once to initialize service-wide policies. public static void InitializeService(DataServiceConfiguration config) { // TODO: set rules to indicate which entity sets and service operations are visible, updatable, etc. // Examples: // config.SetEntitySetAccessRule("MyEntityset", EntitySetRights.AllRead); // config.SetServiceOperationAccessRule("MyServiceOperation", ServiceOperationRights.All); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } Replace the comment that starts with “/* TODO:” with “NorthwindEntities” (the entity container name of the Model we created earlier).  WCF Data Services is initially locked down by default, FTW! No data is exposed without you explicitly setting it. You have explicitly specify which Entity sets you wish to expose and what rights are allowed by using the SetEntitySetAccessRule. The SetServiceOperationAccessRule on the other hand sets rules for a specified operation. Let us define an access rule to expose the Products Entity we created earlier. We use the EnititySetRights.AllRead since we want to give read only access. Our modified code is shown below. public class DataService : DataService<NorthwindEntities> { public static void InitializeService(DataServiceConfiguration config) { config.SetEntitySetAccessRule("Products", EntitySetRights.AllRead); config.DataServiceBehavior.MaxProtocolVersion = DataServiceProtocolVersion.V2; } } We are done setting up our ODataFeed! Compile your project. Right click on DataService.svc and select “View in Browser” to see the OData feed. To view the feed in IE, you must make sure that "Feed Reading View" is turned off. You set this under Tools -› Internet Options -› Content tab.   If you navigate to “Products”, you should see the Products feed. Note also that URIs are case sensitive. ie. Products work but products doesn’t.   Filtering our data OData has a set of system query operations you can use to perform common operations against data exposed by the model. For example, to see only Products in CategoryID 2, we can use the following request: /DataService.svc/Products?$filter=CategoryID eq 2 At the time of this writing, supported operations are $orderby, $top, $skip, $filter, $expand, $format†, $select, $inlinecount. Pre-filtering our data using Query Interceptors The Product feed currently returns all Products. We want to change that so that it contains only Products that have not been discontinued. WCF introduces the concept of interceptors which allows us to inject custom validation/policy logic into the request/response pipeline of a WCF data service. We will use a QueryInterceptor to pre-filter the data so that it returns only Products that are not discontinued. To create a QueryInterceptor, write a method that returns an Expression<Func<T, bool>> and mark it with the QueryInterceptor attribute as shown below. [QueryInterceptor("Products")] public Expression<Func<Product, bool>> OnReadProducts() { return o => o.Discontinued == false; } Viewing the feed after compilation will only show products that have not been discontinued. We also confirm this by looking at the WHERE clause in the SQL generated by the entity framework. SELECT [Extent1].[ProductID] AS [ProductID], ... ... [Extent1].[Discontinued] AS [Discontinued] FROM [dbo].[Products] AS [Extent1] WHERE 0 = [Extent1].[Discontinued] Other examples of Query/Change interceptors can be seen here including an example to filter data based on the identity of the authenticated user. We are done pre-filtering our data. In the next part of this post, we will see how to shape our data. Pre-filtering and shaping OData feeds using WCF Data Services and the Entity Framework - Part 2 Foot Notes * http://msdn.microsoft.com/en-us/data/aa937697.aspx † $format did not work for me. The way to get a Json response is to include the following in the  request header “Accept: application/json, text/javascript, */*” when making the request. This is easily done with most JavaScript libraries.

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  • Big Data Matters with ODI12c

    - by Madhu Nair
    contributed by Mike Eisterer On October 17th, 2013, Oracle announced the release of Oracle Data Integrator 12c (ODI12c).  This release signifies improvements to Oracle’s Data Integration portfolio of solutions, particularly Big Data integration. Why Big Data = Big Business Organizations are gaining greater insights and actionability through increased storage, processing and analytical benefits offered by Big Data solutions.  New technologies and frameworks like HDFS, NoSQL, Hive and MapReduce support these benefits now. As further data is collected, analytical requirements increase and the complexity of managing transformations and aggregations of data compounds and organizations are in need for scalable Data Integration solutions. ODI12c provides enterprise solutions for the movement, translation and transformation of information and data heterogeneously and in Big Data Environments through: The ability for existing ODI and SQL developers to leverage new Big Data technologies. A metadata focused approach for cataloging, defining and reusing Big Data technologies, mappings and process executions. Integration between many heterogeneous environments and technologies such as HDFS and Hive. Generation of Hive Query Language. Working with Big Data using Knowledge Modules  ODI12c provides developers with the ability to define sources and targets and visually develop mappings to effect the movement and transformation of data.  As the mappings are created, ODI12c leverages a rich library of prebuilt integrations, known as Knowledge Modules (KMs).  These KMs are contextual to the technologies and platforms to be integrated.  Steps and actions needed to manage the data integration are pre-built and configured within the KMs.  The Oracle Data Integrator Application Adapter for Hadoop provides a series of KMs, specifically designed to integrate with Big Data Technologies.  The Big Data KMs include: Check Knowledge Module Reverse Engineer Knowledge Module Hive Transform Knowledge Module Hive Control Append Knowledge Module File to Hive (LOAD DATA) Knowledge Module File-Hive to Oracle (OLH-OSCH) Knowledge Module  Nothing to beat an Example: To demonstrate the use of the KMs which are part of the ODI Application Adapter for Hadoop, a mapping may be defined to move data between files and Hive targets.  The mapping is defined by dragging the source and target into the mapping, performing the attribute (column) mapping (see Figure 1) and then selecting the KM which will govern the process.  In this mapping example, movie data is being moved from an HDFS source into a Hive table.  Some of the attributes, such as “CUSTID to custid”, have been mapped over. Figure 1  Defining the Mapping Before the proper KM can be assigned to define the technology for the mapping, it needs to be added to the ODI project.  The Big Data KMs have been made available to the project through the KM import process.   Generally, this is done prior to defining the mapping. Figure 2  Importing the Big Data Knowledge Modules Following the import, the KMs are available in the Designer Navigator. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Figure 3  The Project View in Designer, Showing Installed IKMs Once the KM is imported, it may be assigned to the mapping target.  This is done by selecting the Physical View of the mapping and examining the Properties of the Target.  In this case MOVIAPP_LOG_STAGE is the target of our mapping. Figure 4  Physical View of the Mapping and Assigning the Big Data Knowledge Module to the Target Alternative KMs may have been selected as well, providing flexibility and abstracting the logical mapping from the physical implementation.  Our mapping may be applied to other technologies as well. The mapping is now complete and is ready to run.  We will see more in a future blog about running a mapping to load Hive. To complete the quick ODI for Big Data Overview, let us take a closer look at what the IKM File to Hive is doing for us.  ODI provides differentiated capabilities by defining the process and steps which normally would have to be manually developed, tested and implemented into the KM.  As shown in figure 5, the KM is preparing the Hive session, managing the Hive tables, performing the initial load from HDFS and then performing the insert into Hive.  HDFS and Hive options are selected graphically, as shown in the properties in Figure 4. Figure 5  Process and Steps Managed by the KM What’s Next Big Data being the shape shifting business challenge it is is fast evolving into the deciding factor between market leaders and others. Now that an introduction to ODI and Big Data has been provided, look for additional blogs coming soon using the Knowledge Modules which make up the Oracle Data Integrator Application Adapter for Hadoop: Importing Big Data Metadata into ODI, Testing Data Stores and Loading Hive Targets Generating Transformations using Hive Query language Loading Oracle from Hadoop Sources For more information now, please visit the Oracle Data Integrator Application Adapter for Hadoop web site, http://www.oracle.com/us/products/middleware/data-integration/hadoop/overview/index.html Do not forget to tune in to the ODI12c Executive Launch webcast on the 12th to hear more about ODI12c and GG12c. Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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  • How can I intercept an exception occurred during serialization in WCF?

    - by bonomo
    I have a legit data object with all data contract / data member attributes. For some reason the WCF service crashes after the operation has completed and the result is passed as a return value. I believe it has something to do with WCF not being able to serialize that result properly. The test client doesn't say anything specific: The underlying connection was closed: The connection was closed unexpectedly. Server stack trace: at System.ServiceModel.Channels.HttpChannelUtilities.ProcessGetResponseWebException(WebException webException, HttpWebRequest request, HttpAbortReason abortReason) at System.ServiceModel.Channels.HttpChannelFactory.HttpRequestChannel.HttpChannelRequest.WaitForReply(TimeSpan timeout) at System.ServiceModel.Channels.RequestChannel.Request(Message message, TimeSpan timeout) at System.ServiceModel.Dispatcher.RequestChannelBinder.Request(Message message, TimeSpan timeout) at System.ServiceModel.Channels.ServiceChannel.Call(String action, Boolean oneway, ProxyOperationRuntime operation, Object[] ins, Object[] outs, TimeSpan timeout) at System.ServiceModel.Channels.ServiceChannelProxy.InvokeService(IMethodCallMessage methodCall, ProxyOperationRuntime operation) at System.ServiceModel.Channels.ServiceChannelProxy.Invoke(IMessage message) Exception rethrown at [0]: at System.Runtime.Remoting.Proxies.RealProxy.HandleReturnMessage(IMessage reqMsg, IMessage retMsg) at System.Runtime.Remoting.Proxies.RealProxy.PrivateInvoke(MessageData& msgData, Int32 type) at IFacade.PickSecurities(String pattern, Int32 atMost) at FacadeClient.PickSecurities(String pattern, Int32 atMost) Inner Exception: The underlying connection was closed: The connection was closed unexpectedly. at System.Net.HttpWebRequest.GetResponse() at System.ServiceModel.Channels.HttpChannelFactory.HttpRequestChannel.HttpChannelRequest.WaitForReply(TimeSpan timeout) I am in control of creating the instance of the service using a customized service host factory. I know I can set up trace listeners and check the logs, but it's a lot of hassle to do. So I would rather handle it explicitly on the server at the time it happens. So I how can I intercept that exception programmatically and return an appropriate fault meassage?

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  • XML Serialization : Has property of type Class1 : Class1 has another property : How to write the property of Class1 into XML?

    - by Wonderlander
    I want to serialize a class. In this class there's a property, type of Class1, while there are other properties in Class1. public abstract class ComponentBase { [ToSerialize]//An attribute defined my me, indicating whether or not to serialize this property. public ComponentArgs Parameters { get; set; } } public class ComponentArgs { public string WorkingPath { get; set; } public IList<Language> Languages { get; set; } public string ComponentOutputPath { get; set; } } The information serialized must be put into a Dictionary, such as ComponentSettings[str_Name]=str_Value. The method used in reading this value is Reflection. pinfo: Property Info got via Type.GetProperties(); componentSettings.Add(pinfo.Name, pinfo.GetValue((object)this, null).ToString()); The information after serialization is: <Parameters>MS.STBIntl.Pippin.Framework.ComponentArgs</Parameters> instead of the value of ComponentArgs.WorkingPath. The solution I thought of is to append to the following line an if judgement: componentSettings.Add(pinfo.Name, pinfo.GetValue((object)this, null).ToString()); if(pinfo is ComponentArgs) componentSettings.Add(pinfo.Name, pinfo.GetValue( (ComponentArgs)this, null).WorkingPath+"\n"+ LanguageList+"\n"+ //Language list is a concatinated string of all elements in the list. (ComponentArgs)this, null).ComponentOutputPath+"\n"+ ); When deserializing, add a judgement of whether the value contains more than 2 "\n", if so, extract each value from the string. But this way seems clumsy and much more like an workaround. I wonder if there's any more professional way of doing it? My reviewer is very particular and he won't accept such a solution. If you know a way, could you please share it with me? Thanks a lot.

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  • JavaScript Data Binding Frameworks

    - by dwahlin
    Data binding is where it’s at now days when it comes to building client-centric Web applications. Developers experienced with desktop frameworks like WPF or web frameworks like ASP.NET, Silverlight, or others are used to being able to take model objects containing data and bind them to UI controls quickly and easily. When moving to client-side Web development the data binding story hasn’t been great since neither HTML nor JavaScript natively support data binding. This means that you have to write code to place data in a control and write code to extract it. Although it’s certainly feasible to do it from scratch (many of us have done it this way for years), it’s definitely tedious and not exactly the best solution when it comes to maintenance and re-use. Over the last few years several different script libraries have been released to simply the process of binding data to HTML controls. In fact, the subject of data binding is becoming so popular that it seems like a new script library is being released nearly every week. Many of the libraries provide MVC/MVVM pattern support in client-side JavaScript apps and some even integrate directly with server frameworks like Node.js. Here’s a quick list of a few of the available libraries that support data binding (if you like any others please add a comment and I’ll try to keep the list updated): AngularJS MVC framework for data binding (although closely follows the MVVM pattern). Backbone.js MVC framework with support for models, key/value binding, custom events, and more. Derby Provides a real-time environment that runs in the browser an in Node.js. The library supports data binding and templates. Ember Provides support for templates that automatically update as data changes. JsViews Data binding framework that provides “interactive data-driven views built on top of JsRender templates”. jQXB Expression Binder Lightweight jQuery plugin that supports bi-directional data binding support. KnockoutJS MVVM framework with robust support for data binding. For an excellent look at using KnockoutJS check out John Papa’s course on Pluralsight. Meteor End to end framework that uses Node.js on the server and provides support for data binding on  the client. Simpli5 JavaScript framework that provides support for two-way data binding. WinRT with HTML5/JavaScript If you’re building Windows 8 applications using HTML5 and JavaScript there’s built-in support for data binding in the WinJS library.   I won’t have time to write about each of these frameworks, but in the next post I’m going to talk about my (current) favorite when it comes to client-side JavaScript data binding libraries which is AngularJS. AngularJS provides an extremely clean way – in my opinion - to extend HTML syntax to support data binding while keeping model objects (the objects that hold the data) free from custom framework method calls or other weirdness. While I’m writing up the next post, feel free to visit the AngularJS developer guide if you’d like additional details about the API and want to get started using it.

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  • Protect Data and Save Money? Learn How Best-in-Class Organizations do Both

    - by roxana.bradescu
    Databases contain nearly two-thirds of the sensitive information that must be protected as part of any organization's overall approach to security, risk management, and compliance. Solutions for protecting data housed in databases vary from encrypting data at the application level to defense-in-depth protection of the database itself. So is there a difference? Absolutely! According to new research from the Aberdeen Group, Best-in-Class organizations experience fewer data breaches and audit deficiencies - at lower cost -- by deploying database security solutions. And the results are dramatic: Aberdeen found that organizations encrypting data within their databases achieved 30% fewer data breaches and 15% greater audit efficiency with 34% less total cost when compared to organizations encrypting data within applications. Join us for a live webcast with Derek Brink, Vice President and Research Fellow at the Aberdeen Group, next week to learn how your organization can become Best-in-Class.

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  • Bad Data is Really the Monster

    - by Dain C. Hansen
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Bad Data is really the monster – is an article written by Bikram Sinha who I borrowed the title and the inspiration for this blog. Sinha writes: “Bad or missing data makes application systems fail when they process order-level data. One of the key items in the supply-chain industry is the product (aka SKU). Therefore, it becomes the most important data element to tie up multiple merchandising processes including purchase order allocation, stock movement, shipping notifications, and inventory details… Bad data can cause huge operational failures and cost millions of dollars in terms of time, resources, and money to clean up and validate data across multiple participating systems. Yes bad data really is the monster, so what do we do about it? Close our eyes and hope it stays in the closet? We’ve tacked this problem for some years now at Oracle, and with our latest introduction of Oracle Enterprise Data Quality along with our integrated Oracle Master Data Management products provides a complete, best-in-class answer to the bad data monster. What’s unique about it? Oracle Enterprise Data Quality also combines powerful data profiling, cleansing, matching, and monitoring capabilities while offering unparalleled ease of use. What makes it unique is that it has dedicated capabilities to address the distinct challenges of both customer and product data quality – [different monsters have different needs of course!]. And the ability to profile data is just as important to identify and measure poor quality data and identify new rules and requirements. Included are semantic and pattern-based recognition to accurately parse and standardize data that is poorly structured. Finally all of the data quality components are integrated with Oracle Master Data Management, including Oracle Customer Hub and Oracle Product Hub, as well as Oracle Data Integrator Enterprise Edition and Oracle CRM. Want to learn more? On Tuesday Nov 15th, I invite you to listen to our webcast on Reduce ERP consolidation risks with Oracle Master Data Management I’ll be joined by our partner iGate Patni and be talking about one specific way to deal with the bad data monster specifically around ERP consolidation. Look forward to seeing you there!

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  • Where can I locate business data to use in my application?

    - by Aaron McIver
    This question talks about any and all free public raw data which appeared to have valuable pieces but nothing that really provides what I am looking for. Instead of using a socially defined listing of businesses (foursquare), I would like a business listing data set of registered businesses and associated addresses that could then be searchable based on location (coordinates). The critical need is that the data set should be filterable based on varying criteria (give me all restaurants, coffee shops, etc...). If the data is free that is great but anywhere that sells this type of data would also suffice. Infochimps looked like a possibility but perhaps something a bit more extensive exists. Where can I find a free or for fee data set of registered business that is filterable based on type of business and location?

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  • Sybase PowerDesigner Change Many (Find/Replace/Convert) Data Item's Data Types

    - by Andy
    Hello, I have a relatively large Conceptual Data Model in PowerDesigner. After generating a Physical Data Model and seeing the DBMS data types, I need to update all of data types(NUMBER/TEXT) for each data item. I'd like to either do a find/replace within the Conceptual Data Model or somehow map to different data types when creating the Physical Data Model. Ex. Change the auto conversion of Text - Clob, to Text - NVARCHAR(20). Thanks!

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  • are there any useful datasets available on the web for data mining?

    - by niko
    Hi, Does anyone know any good resource where example (real) data can be downloaded for experimenting statistics and machine learning techniques such as decision trees etc? Currently I am studying machine learning techniques and it would be very helpful to have real data for evaluating the accuracy of various tools. If anyone knows any good resource (perhaps csv, xls files or any other format) I would be very thankful for a suggestion.

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  • In .NET Xml Serialization, is it possible to serialize a class with an enum property with different

    - by Lasse V. Karlsen
    I have a class, containing a list property, where the list contains objects that has an enum property. When I serialize this, it looks like this: <?xml version="1.0" encoding="ibm850"?> <test> <events> <test-event type="changing" /> <test-event type="changed" /> </events> </test> Is it possible, through attributes, or similar, to get the Xml to look like this? <?xml version="1.0" encoding="ibm850"?> <test> <events> <changing /> <changed /> </events> </test> Basically, use the property value of the enum as a way to determine the tag-name? Is using a class hierarchy (ie. creating subclasses instead of using the property value) the only way? Edit: After testing, it seems even a class-hierarchy won't actually work. If there is a way to structure the classes to get the output I want, even with sub-classes, that is also an acceptable answer. Here's a sample program that will output the above Xml (remember to hit Ctrl+F5 to run in Visual Studio, otherwise the program window will close immediately): using System; using System.Collections.Generic; using System.Xml.Serialization; namespace ConsoleApplication18 { public enum TestEventTypes { [XmlEnum("changing")] Changing, [XmlEnum("changed")] Changed } [XmlType("test-event")] public class TestEvent { [XmlAttribute("type")] public TestEventTypes Type { get; set; } } [XmlType("test")] public class Test { private List<TestEvent> _Events = new List<TestEvent>(); [XmlArray("events")] public List<TestEvent> Events { get { return _Events; } } } class Program { static void Main(string[] args) { Test test = new Test(); test.Events.Add(new TestEvent { Type = TestEventTypes.Changing }); test.Events.Add(new TestEvent { Type = TestEventTypes.Changed }); XmlSerializer serializer = new XmlSerializer(typeof(Test)); XmlSerializerNamespaces ns = new XmlSerializerNamespaces(); ns.Add("", ""); serializer.Serialize(Console.Out, test, ns); } } }

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  • Optimizing a thread safe Java NIO / Serialization / FIFO Queue [migrated]

    - by trialcodr
    I've written a thread safe, persistent FIFO for Serializable items. The reason for reinventing the wheel is that we simply can't afford any third party dependencies in this project and want to keep this really simple. The problem is it isn't fast enough. Most of it is undoubtedly due to reading and writing directly to disk but I think we should be able to squeeze a bit more out of it anyway. Any ideas on how to improve the performance of the 'take'- and 'add'-methods? /** * <code>DiskQueue</code> Persistent, thread safe FIFO queue for * <code>Serializable</code> items. */ public class DiskQueue<ItemT extends Serializable> { public static final int EMPTY_OFFS = -1; public static final int LONG_SIZE = 8; public static final int HEADER_SIZE = LONG_SIZE * 2; private InputStream inputStream; private OutputStream outputStream; private RandomAccessFile file; private FileChannel channel; private long offs = EMPTY_OFFS; private long size = 0; public DiskQueue(String filename) { try { boolean fileExists = new File(filename).exists(); file = new RandomAccessFile(filename, "rwd"); if (fileExists) { size = file.readLong(); offs = file.readLong(); } else { file.writeLong(size); file.writeLong(offs); } } catch (FileNotFoundException e) { throw new RuntimeException(e); } catch (IOException e) { throw new RuntimeException(e); } channel = file.getChannel(); inputStream = Channels.newInputStream(channel); outputStream = Channels.newOutputStream(channel); } /** * Add item to end of queue. */ public void add(ItemT item) { try { synchronized (this) { channel.position(channel.size()); ObjectOutputStream s = new ObjectOutputStream(outputStream); s.writeObject(item); s.flush(); size++; file.seek(0); file.writeLong(size); if (offs == EMPTY_OFFS) { offs = HEADER_SIZE; file.writeLong(offs); } notify(); } } catch (IOException e) { throw new RuntimeException(e); } } /** * Clears overhead by moving the remaining items up and shortening the file. */ public synchronized void defrag() { if (offs > HEADER_SIZE && size > 0) { try { long totalBytes = channel.size() - offs; ByteBuffer buffer = ByteBuffer.allocateDirect((int) totalBytes); channel.position(offs); for (int bytes = 0; bytes < totalBytes;) { int res = channel.read(buffer); if (res == -1) { throw new IOException("Failed to read data into buffer"); } bytes += res; } channel.position(HEADER_SIZE); buffer.flip(); for (int bytes = 0; bytes < totalBytes;) { int res = channel.write(buffer); if (res == -1) { throw new IOException("Failed to write buffer to file"); } bytes += res; } offs = HEADER_SIZE; file.seek(LONG_SIZE); file.writeLong(offs); file.setLength(HEADER_SIZE + totalBytes); } catch (IOException e) { throw new RuntimeException(e); } } } /** * Returns the queue overhead in bytes. */ public synchronized long overhead() { return (offs == EMPTY_OFFS) ? 0 : offs - HEADER_SIZE; } /** * Returns the first item in the queue, blocks if queue is empty. */ public ItemT peek() throws InterruptedException { block(); synchronized (this) { if (offs != EMPTY_OFFS) { return readItem(); } } return peek(); } /** * Returns the number of remaining items in queue. */ public synchronized long size() { return size; } /** * Removes and returns the first item in the queue, blocks if queue is empty. */ public ItemT take() throws InterruptedException { block(); try { synchronized (this) { if (offs != EMPTY_OFFS) { ItemT result = readItem(); size--; offs = channel.position(); file.seek(0); if (offs == channel.size()) { truncate(); } file.writeLong(size); file.writeLong(offs); return result; } } return take(); } catch (IOException e) { throw new RuntimeException(e); } } /** * Throw away all items and reset the file. */ public synchronized void truncate() { try { offs = EMPTY_OFFS; file.setLength(HEADER_SIZE); size = 0; } catch (IOException e) { throw new RuntimeException(e); } } /** * Block until an item is available. */ protected void block() throws InterruptedException { while (offs == EMPTY_OFFS) { try { synchronized (this) { wait(); file.seek(LONG_SIZE); offs = file.readLong(); } } catch (IOException e) { throw new RuntimeException(e); } } } /** * Read and return item. */ @SuppressWarnings("unchecked") protected ItemT readItem() { try { channel.position(offs); return (ItemT) new ObjectInputStream(inputStream).readObject(); } catch (ClassNotFoundException e) { throw new RuntimeException(e); } catch (IOException e) { throw new RuntimeException(e); } } }

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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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  • 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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  • Why do transfer objects need to implement Serializable?

    - by smaye81
    I realized today that I have blindly just followed this requirement for years without ever really asking why. Today, I ran across a NotSerializableException with a model object I created from scratch and I realized enough is enough. I was told this was because of session replication between load-balanced servers, but I know I've seen other objects at session scope that do not implement Serializable. Is this the real reason?

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  • creative way for implementing Data object with it's corespanding buisness logic class in java

    - by ekeren
    I have a class that need to be serialized (for both persistentcy and client-server communication) for simplicity reasons lets call the classes Business a BusinessData and I prefix for their Interfaces. All the getter and setter are delegated from Business class to BusinessData class. I thought about implementing IBusinessData interface that will contain all the getter and setters and IBusiness interface that will extend it. I can either make Business extend BuisnessData so I will not need to implement all getter and setter delegates, or make some abstract class ForwardingBusinessData that will only delegate getter and setters. Any of the above option I loose my hierarchy freedom, does any of you have any creative solution for this problem... I also reviewed DAO pattern: http://java.sun.com/blueprints/patterns/DAO.html

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