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• Achieving decoupling in Model classes

  - by Guven

  I am trying to test-drive (or at least write unit tests) my Model classes but I noticed that my classes end up being too coupled. Since I can't break this coupling, writing unit tests is becoming harder and harder. To be more specific: Model Classes: These are the classes that hold the data in my application. They resemble pretty much the POJO (plain old Java objects), but they also have some methods. The application is not too big so I have around 15 model classes. Coupling: Just to give an example, think of a simple case of Order Header - Order Item. The header knows the item and the item knows the header (needs some information from the header for performing certain operations). Then, let's say there is the relationship between Order Item - Item Report. The item report needs the item as well. At this point, imagine writing tests for Item Report; you need have a Order Header to carry out the tests. This is a simple case with 3 classes; things get more complicated with more classes. I can come up with decoupled classes when I design algorithms, persistence layers, UI interactions, etc... but with model classes, I can't think of a way to separate them. They currently sit as one big chunk of classes that depend on each other. Here are some workarounds that I can think of: Data Generators: I have a package that generates sample data for my model classes. For example, the OrderHeaderGenerator class creates OrderHeaders with some basic data in it. I use the OrderHeaderGenerator from my ItemReport unit-tests so that I get an instance to OrderHeader class. The problem is these generators get complicated pretty fast and then I also need to test these generators; defeating the purpose a little bit. Interfaces instead of dependencies: I can come up with interfaces to get rid of the hard dependencies. For example, the OrderItem class would depend on the IOrderHeader interface. So, in my unit tests, I can easily mock the behaviour of an OrderHeader with a FakeOrderHeader class that implements the IOrderHeader interface. The problem with this approach is the complexity that the Model classes would end up having. Would you have other ideas on how to break this coupling in the model classes? Or, how to make it easier to unit-test the model classes?

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• Model binding & derived model classes

  - by Richard Ev

  Does ASP.NET MVC offer any simple way to get model binding to work when you have model classes that inherit from others? In my scenario I have a View that is strongly typed to List<Person>. I have a couple of classes that inherit from Person, namely PersonTypeOne and PersonTypeTwo. I have three strongly typed partial views with names that match these class names (and render form elements for the properties of their respective models). This means that in my main View I can have the following code: <% for(int i = 0; i < Model.Count; i++) { Html.RenderPartial(Model[i].GetType().Name, Model[i]); } %> This works well, apart from when the user submits the form the relevant controller action method just gets a List<Person>, rather than a list of Person, PersonTypeOne and PersonTypeTwo. This is pretty much as expected as the form submission doesn't contain enough information to tell the default model binder to create any instances of PersonTypeOne and PersonTypeTwo classes. So, is there any way to get such functionality from the default model binder?

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• Custom ASP.Net MVC 2 ModelMetadataProvider for using custom view model attributes

  - by SeanMcAlinden

  There are a number of ways of implementing a pattern for using custom view model attributes, the following is similar to something I’m using at work which works pretty well. The classes I’m going to create are really simple: 1. Abstract base attribute 2. Custom ModelMetadata provider which will derive from the DataAnnotationsModelMetadataProvider   Base Attribute MetadataAttribute using System; using System.Web.Mvc; namespace Mvc2Templates.Attributes {     /// <summary>     /// Base class for custom MetadataAttributes.     /// </summary>     public abstract class MetadataAttribute : Attribute     {         /// <summary>         /// Method for processing custom attribute data.         /// </summary>         /// <param name="modelMetaData">A ModelMetaData instance.</param>         public abstract void Process(ModelMetadata modelMetaData);     } } As you can see, the class simple has one method – Process. Process accepts the ModelMetaData which will allow any derived custom attributes to set properties on the model meta data and add items to its AdditionalValues collection.   Custom Model Metadata Provider For a quick explanation of the Model Metadata and how it fits in to the MVC 2 framework, it is basically a set of properties that are usually set via attributes placed above properties on a view model, for example the ReadOnly and HiddenInput attributes. When EditorForModel, DisplayForModel or any of the other EditorFor/DisplayFor methods are called, the ModelMetadata information is used to determine how to display the properties. All of the information available within the model metadata is also available through ViewData.ModelMetadata. The following class derives from the DataAnnotationsModelMetadataProvider built into the mvc 2 framework. I’ve overridden the CreateMetadata method in order to process any custom attributes that may have been placed above a property in a view model.   CustomModelMetadataProvider using System; using System.Collections.Generic; using System.Linq; using System.Web.Mvc; using Mvc2Templates.Attributes; namespace Mvc2Templates.Providers {     public class CustomModelMetadataProvider : DataAnnotationsModelMetadataProvider     {         protected override ModelMetadata CreateMetadata(             IEnumerable<Attribute> attributes,             Type containerType,             Func<object> modelAccessor,             Type modelType,             string propertyName)         {             var modelMetadata = base.CreateMetadata(attributes, containerType, modelAccessor, modelType, propertyName);               attributes.OfType<MetadataAttribute>().ToList().ForEach(x => x.Process(modelMetadata));               return modelMetadata;         }     } } As you can see, once the model metadata is created through the base method, a check for any attributes deriving from our new abstract base attribute MetadataAttribute is made, the Process method is then called on any existing custom attributes with the model meta data for the property passed in.   Hooking it up The last thing you need to do to hook it up is set the new CustomModelMetadataProvider as the current ModelMetadataProvider, this is done within the Global.asax Application_Start method. Global.asax protected void Application_Start()         {             AreaRegistration.RegisterAllAreas();               RegisterRoutes(RouteTable.Routes);               ModelMetadataProviders.Current = new CustomModelMetadataProvider();         }   In my next post, I’m going to demonstrate a cool custom attribute that turns a textbox into an ajax driven AutoComplete text box. Hope this is useful. Kind Regards, Sean McAlinden.

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• Data Structures usage and motivational aspects

  - by Aubergine

  For long student life I was always wondering why there are so many of them yet there seems to be lack of usage at all in many of them. The opinion didn't really change when I got a job. We have brilliant books on what they are and their complexities, but I never encounter resources which would actually give a good hint of practical usage. I perfectly understand that I have to look at problem , analyse required operations, look for data structure that does them efficiently. However in practice I never do that, not because of human laziness syndrome, but because when it comes to work I acknowledge time priority over self-development. Over time I thought that when I would be better developer I will automatically use more of them - that didn't happen at all or maybe I just didn't. Then I found that the colleagues usually in the same plate as me - knowing more or less some three of data structures and being totally happy about it and refusing to discuss this matter further with me, coming back to conversations about 'cool new languages' 'libraries that do jobs for you' and the joy to work under scrumban etc. I am stuck with ArrayLists, Arrays and SortedMap , which no matter what I do always suffice or either I tweak them to be capable of fulfilling my task. Yes, it might be inefficient but do we really have to care if Intel increases performance over years no matter if we improve our skills? Does new Xeon or IBM machines really care what we use? What if I like build things, but I am not particularly excited whether it is n log(n) or just n? Over twenty years the processing power increased enormously, which gives us freedom of not being critical about which one to use? On top of that new more optimized languages appear which support multiple cores more efficiently. To be more specific: I would like to find motivational material on complex real areas/cases of possible effective usages of data structures. I would be really grateful if you would provide relevant resources. There is similar question ,but in the end the links again mostly describe or do dumb example(vehicles, students or holy grail quest - yes, very relevant) them and people keep referring to the "scenario decides the data structure to use". I want to know these complex scenarios to be able to identify similarities to my scenario and then use them. The complex scenarios where it really matters and not necessarily of quantitive nature. It seems that data structures only concern is efficiency and nothing else? There seems to be no particular convenience for developer in use one over another. (only when I found scientific resources on why exactly simple carbohydrates are evil I stopped eating sugar and candies completely replacing it with less harmful fruits - I hope you can see the analogy)

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• Backbone.js (model instanceof Model) via Chrome Extension

  - by Leoncelot

  Hey guys, This is my first time ever posting on this site and the problem I'm about to pose is difficult to articulate due to the set of variables required to arrive at it. Let me just quickly explain the framework I'm working with. I'm building a Chrome Extension using jQuery, jQuery-ui, and Backbone The entire JS suite for the extension is written in CoffeeScript and I'm utilizing Rails and the asset pipeline to manage it all. This means that when I want to deploy my extension code I run rake assets:precompile and copy the resulting compressed JS to my extensions Directory. The nice thing about this approach is that I can actually run the extension js from inside my Rails app by including the library. This is basically the same as my extensions background.js file which injects the js as a content script. Anyway, the problem I've recently encountered was when I tried testing my extension on my buddy's site, whiskeynotes.com. What I was noticing is that my backbone models were being mangled upon adding them to their respective collections. So something like this.collection.add(new SomeModel) created some nonsense version of my model. This code eventually runs into Backbone's prepareModel code _prepareModel: function(model, options) { options || (options = {}); if (!(model instanceof Model)) { var attrs = model; options.collection = this; model = new this.model(attrs, options); if (!model._validate(model.attributes, options)) model = false; } else if (!model.collection) { model.collection = this; } return model; }, Now, in most of the sites on which I've tested the extension, the result is normal, however on my buddy's site the !(model instance Model) evaluates to true even though it is actually an instance of the correct class. The consequence is a super messed up version of the model where the model's attributes is a reference to the models collection (strange right?). Needless to say, all kinds of crazy things were happening afterward. Why this is occurring is beyond me. However changing this line (!(model instanceof Model)) to (!(model instanceof Backbone.Model)) seems to fix the problem. I thought maybe it had something to do with the Flot library (jQuery graph library) creating their own version of 'Model' but looking through the source yielded no instances of it. I'm just curious as to why this would happen. And does it make sense to add this little change to the Backbone source? Update: I just realized that the "fix" doesn't actually work. I can also add that my backbone Models are namespaced in a wrapping object so that declaration looks something like class SomeNamespace.SomeModel extends Backbone.Model

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• Unleash AutoVue on Your Unmanaged Data

  - by [email protected]

  Over the years, I've spoken to hundreds of customers who use AutoVue to collaborate on their "managed" data stored in content management systems, product lifecycle management systems, etc. via our many integrations. Through these conversations I've also learned a harsh reality - we will never fully move away from unmanaged data (desktops, file servers, emails, etc). If you use AutoVue today you already know that even if your primary use is viewing content stored in a content management system, you can still open files stored locally on your computer. But did you know that AutoVue actually has - built-in - a great solution for viewing, printing and redlining your data stored on file servers? Using the 'Server protocol' you can point AutoVue directly to a top-level location on any networked file server and provide your users with a link or shortcut to access an interface similar to the sample page shown below. Many customers link to pages just like this one from their internal company intranets. Through this webpage, users can easily search and browse through file server data with a 'click-and-view' interface to find the specific image, document, drawing or model they're looking for. Any markups created on a document will be accessible to everyone else viewing that document and of course real-time collaboration is supported as well. Customers on maintenance can consult the AutoVue Admin guide or My Oracle Support Doc ID 753018.1 for an introduction to the server protocol. Contact your local AutoVue Solutions Consultant for help setting up the sample shown above.

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• SQL SERVER – Step by Step Guide to Beginning Data Quality Services in SQL Server 2012 – Introduction to DQS

  - by pinaldave

  Data Quality Services is a very important concept of SQL Server. I have recently started to explore the same and I am really learning some good concepts. Here are two very important blog posts which one should go over before continuing this blog post. Installing Data Quality Services (DQS) on SQL Server 2012 Connecting Error to Data Quality Services (DQS) on SQL Server 2012 This article is introduction to Data Quality Services for beginners. We will be using an Excel file Click on the image to enlarge the it. In the first article we learned to install DQS. In this article we will see how we can learn about building Knowledge Base and using it to help us identify the quality of the data as well help correct the bad quality of the data. Here are the two very important steps we will be learning in this tutorial. Building a New Knowledge Base  Creating a New Data Quality Project Let us start the building the Knowledge Base. Click on New Knowledge Base. In our project we will be using the Excel as a knowledge base. Here is the Excel which we will be using. There are two columns. One is Colors and another is Shade. They are independent columns and not related to each other. The point which I am trying to show is that in Column A there are unique data and in Column B there are duplicate records. Clicking on New Knowledge Base will bring up the following screen. Enter the name of the new knowledge base. Clicking NEXT will bring up following screen where it will allow to select the EXCE file and it will also let users select the source column. I have selected Colors and Shade both as a source column. Creating a domain is very important. Here you can create a unique domain or domain which is compositely build from Colors and Shade. As this is the first example, I will create unique domain – for Colors I will create domain Colors and for Shade I will create domain Shade. Here is the screen which will demonstrate how the screen will look after creating domains. Clicking NEXT it will bring you to following screen where you can do the data discovery. Clicking on the START will start the processing of the source data provided. Pre-processed data will show various information related to the source data. In our case it shows that Colors column have unique data whereas Shade have non-unique data and unique data rows are only two. In the next screen you can actually add more rows as well see the frequency of the data as the values are listed unique. Clicking next will publish the knowledge base which is just created. Now the knowledge base is created. We will try to take any random data and attempt to do DQS implementation over it. I am using another excel sheet here for simplicity purpose. In reality you can easily use SQL Server table for the same. Click on New Data Quality Project to see start DQS Project. In the next screen it will ask which knowledge base to use. We will be using our Colors knowledge base which we have recently created. In the Colors knowledge base we had two columns – 1) Colors and 2) Shade. In our case we will be using both of the mappings here. User can select one or multiple column mapping over here. Now the most important phase of the complete project. Click on Start and it will make the cleaning process and shows various results. In our case there were two columns to be processed and it completed the task with necessary information. It demonstrated that in Colors columns it has not corrected any value by itself but in Shade value there is a suggestion it has. We can train the DQS to correct values but let us keep that subject for future blog posts. Now click next and keep the domain Colors selected left side. It will demonstrate that there are two incorrect columns which it needs to be corrected. Here is the place where once corrected value will be auto-corrected in future. I manually corrected the value here and clicked on Approve radio buttons. As soon as I click on Approve buttons the rows will be disappeared from this tab and will move to Corrected Tab. If I had rejected tab it would have moved the rows to Invalid tab as well. In this screen you can see how the corrected 2 rows are demonstrated. You can click on Correct tab and see previously validated 6 rows which passed the DQS process. Now let us click on the Shade domain on the left side of the screen. This domain shows very interesting details as there DQS system guessed the correct answer as Dark with the confidence level of 77%. It is quite a high confidence level and manual observation also demonstrate that Dark is the correct answer. I clicked on Approve and the row moved to corrected tab. On the next screen DQS shows the summary of all the activities. It also demonstrates how the correction of the quality of the data was performed. The user can explore their data to a SQL Server Table, CSV file or Excel. The user also has an option to either explore data and all the associated cleansing info or data only. I will select Data only for demonstration purpose. Clicking explore will generate the files. Let us open the generated file. It will look as following and it looks pretty complete and corrected. Well, we have successfully completed DQS Process. The process is indeed very easy. I suggest you try this out yourself and you will find it very easy to learn. In future we will go over advanced concepts. Are you using this feature on your production server? If yes, would you please leave a comment with your environment and business need. It will be indeed interesting to see where it is implemented. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Business Intelligence, Data Warehousing, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: Data Quality Services, DQS

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• Consolidate Data in Private Clouds, But Consider Security and Regulatory Issues

  - by Troy Kitch

  The January 13 webcast Security and Compliance for Private Cloud Consolidation will provide attendees with an overview of private cloud computing based on Oracle's Maximum Availability Architecture and how security and regulatory compliance affects implementations. Many organizations are taking advantage of Oracle's Maximum Availability Architecture to drive down the cost of IT by deploying private cloud computing environments that can support downtime and utilization spikes without idle redundancy. With two-thirds of sensitive and regulated data in organizations' databases private cloud database consolidation means organizations must be more concerned than ever about protecting their information and addressing new regulatory challenges. Join us for this webcast to learn about greater risks and increased threats to private cloud data and how Oracle Database Security Solutions can assist in securely consolidating data and meet compliance requirements. Register Now.

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• Web application / Domain model integration using JSON capable DTOs [on hold]

  - by g-makulik

  I'm a bit confused about architectural choices for the web-applications/java/python world. For c/c++ world the available (open source) choices to implement web applications is pretty limited to zero, involving java or python the choices explode to a,- hard to sort out -, mess of available 'frameworks' and application approaches. I want to sort out a clean MVC model, where the M stands for a fully blown (POCO, POJO driven) domain model (according M.Fowler's EAA pattern) using a mature OO language (Java,C++) for implementation. The background is: I have a system with certain hardware components (that introduce system immanent active behavior) and a configuration database for system meta and HW-components configuration data (these are even usually self contained, since the HW-components are capable to persist their configuration data anyway). For realization of the configuration/status data exchange protocol with the HW-components we have chosen the Google Protobuf format, which works well for the directly wired communication with these components. This protocol is already used successfully with a Java based GUI application via TCP/IP connection to the main system controlling HW-component. This application has some drawbacks and design flaws for historical reasons. Now we want to develop an abstract model (domain model) for configuration and monitoring those HW-components, that represents a more use case oriented view to the overall system behavior. I have the feeling that a plain Java class model would fit best for this (c++ implementation seems to have too much implementation/integration overhead with viable language-bridge interfaces). Google Protobuf message definitions could still serve well to describe DTO objects used to interact with a domain model API. But integrating Google Protobuf messages client side for e.g. data binding in the current view doesn't seem to be a good choice. I'm thinking about some extra serialization features, e.g. for JSON based data exchange with the views/controllers. Most lightweight solutions seem to involve a python based presentation layer using JSON based data transfer (I'm at least not sure to be fully informed about this). Is there some lightweight (applicable for a limited ARM Linux platform) framework available, supporting such architecture to realize a web-application? UPDATE: According to my recent research and comments of colleagues I've noticed that using Java (and some JVM) might not be the preferable choice for integration with python on a limited linux system as we have (running on ARM9 with hard to discuss memory and MCU costs), but C/C++ modules would do well for this (since this forms the native interface to python extensions, doesn't it?). I can imagine to provide a domain model from an appropriate C/C++ API (though I still think it's more efforts and higher skill requirements for the involved developers to do with these languages). Still I'm searching for a good approach that supports such architecture. I'll appreciate any pointers!

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• More Value From Data Using Data Mining Presentation

  Here is a presentation I gave at the SQLBits conference in September which was recorded by Microsoft.  Usually I speak about SSIS but on this particular event I thought people would like to hear something different from me. Microsoft are making a big play for making Data Mining more accessible to everyone and not just boffins.  In this presentation I give an overview of data mining and then do some demonstrations using the excellent Excel Add-Ins available from Microsoft SQL Server 2008 SQL Server 2005 I hope you enjoy this presentation http://go.microsoft.com/?linkid=9633764

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• Camera not staying behind model while moving in circle

  - by ChocoMan

  I have a camera behind a model (3rd Person) and I'm having problems KEEPING it behind the model. When I first start my game, you see the back of the model. If the model moves forward, backward or strafe left or right, the camera moves along accordingly. When the model rotates (stationary), the camera rotates accordingly with the model still pointing at the model's back. So far, so good. The problem comes when the player is BOTH moving and rotating at the same time. Take for example a model moving in a circular pattern like running around a track. As the model moves in this motion, the model rotates slightly more with each complete rotation. Eventually, instead of looking at the model's back, eventually you will see the model in a profile view and before you know it, the model's front is facing the camera. And when you stop moving the model, the model stays in that position. So, as long as my model is stationary and rotating in one place, the camera rotates correctly. But as soon as there is any sort movement while rotating, the model is offset by a mysterious increasing amount. How can I keep the camera maintaining the same view no matter how I move AND rotate at the same time? // Rotates model and pitches camera on its own axis public void modelRotMovement(GamePadState pController) { /* For rotating the model left or right. * Camera maintains distance from model * throughout rotation and if model moves * to a new position. */ Yaw = pController.ThumbSticks.Right.X * MathHelper.ToRadians(speedAngleMAX); AddRotation = Quaternion.CreateFromAxisAngle(Vector3.Up, yaw); //AddRotation = Quaternion.CreateFromYawPitchRoll(Yaw, 0, 0); ModelLoad.MRotation *= AddRotation; MOrientation = Matrix.CreateFromQuaternion(ModelLoad.MRotation); Pitch = pController.ThumbSticks.Right.Y * MathHelper.ToRadians(speedAngleMAX); AddPitch = Quaternion.CreateFromAxisAngle(Vector3.Up, pitch); ModelLoad.CRotation *= AddPitch; COrientation = Matrix.CreateFromQuaternion(ModelLoad.CRotation); } // Orbit (yaw) Camera around model public void cameraYaw(float yaw) { Vector3 yawAngle = ModelLoad.CameraPos - ModelLoad.camTarget; Vector3 axisYaw = Vector3.Up; ModelLoad.CameraPos = Vector3.Transform(yawAngle, Matrix.CreateFromAxisAngle(axisYaw, yaw)) + ModelLoad.camTarget; }

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• Move model forward base on model orientation

  - by ChocoMan

  My model rotates on it's own Y-axis regardless of where it is in the world. Here are the controls for the left ThumbStick: UP (move model forward on Z-Axis) DOWN (move model backward on Z-Axis) LEFT & RIGHT (strafe to either side) The problem is adjusting the direction the model's orientation UP and DOWN if the player should also rotate the player while moving forward or backwards. An example what Im trying to achieve would be a car doing donuts. The car is always facing the current direction that it interprets as forward (or rear as backwards) in relation to it's local rotation. Here is how Im calling the movement: // Rotate model with Right Thumbstick along X-Axis modelRotation -= pController.ThumbSticks.Right.X * mRotSpeed; // Move Forward if (pController.IsButtonDown(Buttons.LeftThumbstickUp)) { modelPosition.Z -= -pController.ThumbSticks.Left.Y * speed; } // Move Backward if (pController.IsButtonDown(Buttons.LeftThumbstickDown)) { modelPosition.Z += pController.ThumbSticks.Left.Y * speed; } // Strafe Left if (pController.IsButtonDown(Buttons.LeftThumbstickLeft)) { modelPosition.X += -pController.ThumbSticks.Left.X * speed; } // Strafe Right if (pController.IsButtonDown(Buttons.LeftThumbstickRight)) { modelPosition.X -= pController.ThumbSticks.Left.X * speed; } // DeadZone if (!pController.IsButtonDown(Buttons.LeftThumbstickUp) && !pController.IsButtonDown(Buttons.LeftThumbstickDown) && !pController.IsButtonDown(Buttons.LeftThumbstickLeft) && !pController.IsButtonDown(Buttons.LeftThumbstickRight)) { }

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• Move data from others user accounts in my user account

  - by user118136

  I had problems with compiz setting and I make multiple accounts, now I want to transfer my information from all deleted users in my current account, some data I can not copy because I am not right to read, I type in terminal "sudo nautilus" and I get the permission for read, but the copied data is available only for superusers and I must charge the permissions for each file and each folder. How I can copy the information with out the superuser rights OR how I can charge the permissions for selected folder and all files and folders included in it?

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• How do you keep track of what the industry is up to?

  - by BlairHippo

  A discussion elsewhere made me realize that I don't do a particularly good job of following the software industry. My exposure to new trends or technologies is haphazard at best, often limited to a "Hey, that sounds interesting" when I see people discussing something I'm not familiar with on SO. To abuse a metaphor, I'm quite familiar with the tree where I work, but I know too bloody little about the rest of the forest. How do other folks keep abreast of what's going on in the software industry? Are there any sites/blogs/podcasts/whatever that you find particularly valuable for keeping you informed of potentially useful new technologies or industry-wide trends? (My apologies in advance if this is a duplicate; this feels like something that ought to have been asked before, but alas, my search-fu has failed me.)

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• How to remove a model object from an EMF model and its GEF Editor via Adapter

  - by s.d

  This question is principally a follow-up to my question about EMF listening mechanisms. So, I have a third-party EMF model (uneditable) which is based on a generic graph model. The structure is as follows: Project | ItemGraph | Item | Document | DocumentGraph / | \ Tokens Nodes Relations(Edges) I have a GEF editor which works on the DocumentGraph (i.e., not the root object, perhaps this is a problem?): getGraphicalViewer().setContents(documentGraph). THe editor has the following edit part structure: DocumentGraphEP / \ Primary Connection LayerEP LayerEP / \ | TokenEP NodeEP RelationEP PrimaryLayerEP and ConnectionLayerEP both have simple Strings as model, which are not represented in the EMF (domain) model. They are simply used to add a primary (i.e., node) layer, and a connection layer (with ShortestPathConnectionRouter) to the editor. Problem: I am trying to get myself into the workings of EMF adapters, and have tried to make use of the available tutorials, mainly the EMF-GEF Eclipse tutorial, vainolo's blog, and vogella's tutorial. I thought I'd start with an easy thing, so tried to remove a node from the graph and see if I get it to work. Which I didn't, and I don't see where the problem is. I can select a node, and have the generic delete Action in my toolbar, but when I click it, nothing happens. Here is the respective source code for the different responsible parts. Please be so kind to point me to any errors (of thinking, coding errors, whathaveyou) you can find. NodeEditPart public class NodeEditPart extends AbstractGraphicalEditPart implements Adapter { protected IFigure createFigure() { return new NodeFigure(); } protected void createEditPolicies() { .... installEditPolicy(EditPolicy.COMPONENT_ROLE, new NodeComponentEditPolicy()); } protected void refreshVisuals() { NodeFigure figure = (NodeFigure) getFigure(); SNode model = (SNode) getModel(); PrimaryLayerEditPart parent = (PrimaryLayerEditPart) getParent(); // Set text figure.getLabel().setText(model.getSName()); .... } public void activate() { if (isActive()) return; // start listening for changes in the model ((Notifier)getModel()).eAdapters().add(this); super.activate(); } public void deactivate() { if (!isActive()) return; // stop listening for changes in the model ((Notifier)getModel()).eAdapters().remove(this); super.deactivate(); } private Notifier getSDocumentGraph() { return ((SNode)getModel()).getSDocumentGraph(); } @Override public void notifyChanged(Notification notification) { int type = notification.getEventType(); switch( type ) { case Notification.ADD: case Notification.ADD_MANY: case Notification.REMOVE: case Notification.REMOVE_MANY: refreshChildren(); break; case Notification.SET: refreshVisuals(); break; } } @Override public Notifier getTarget() { return target; } @Override public void setTarget(Notifier newTarget) { this.target = newTarget; } @Override public boolean isAdapterForType(Object type) { return type.equals(getModel().getClass()); } } NodeComponentEditPolicy public class NodeComponentEditPolicy extends ComponentEditPolicy { public NodeComponentEditPolicy() { super(); } protected Command createDeleteCommand(GroupRequest deleteRequest) { DeleteNodeCommand cmd = new DeleteNodeCommand(); cmd.setSNode((SNode) getHost().getModel()); return cmd; } } DeleteNodeCommand public class DeleteNodeCommand extends Command { private SNode node; private SDocumentGraph graph; @Override public void execute() { node.setSDocumentGraph(null); } @Override public void undo() { node.setSDocumentGraph(graph); } public void setSNode(SNode node) { this.node = node; this.graph = node.getSDocumentGraph(); } } All seems to work fine: When a node is selected in the editor, the delete symbol is activated in the toolbar, but when it is clicked, nothing happens in the editor. I'd be very thankful for any pointers :).

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• SQL SERVER – Guest Post – Architecting Data Warehouse – Niraj Bhatt

  - by pinaldave

  Niraj Bhatt works as an Enterprise Architect for a Fortune 500 company and has an innate passion for building / studying software systems. He is a top rated speaker at various technical forums including Tech·Ed, MCT Summit, Developer Summit, and Virtual Tech Days, among others. Having run a successful startup for four years Niraj enjoys working on – IT innovations that can impact an enterprise bottom line, streamlining IT budgets through IT consolidation, architecture and integration of systems, performance tuning, and review of enterprise applications. He has received Microsoft MVP award for ASP.NET, Connected Systems and most recently on Windows Azure. When he is away from his laptop, you will find him taking deep dives in automobiles, pottery, rafting, photography, cooking and financial statements though not necessarily in that order. He is also a manager/speaker at BDOTNET, Asia’s largest .NET user group. Here is the guest post by Niraj Bhatt. As data in your applications grows it’s the database that usually becomes a bottleneck. It’s hard to scale a relational DB and the preferred approach for large scale applications is to create separate databases for writes and reads. These databases are referred as transactional database and reporting database. Though there are tools / techniques which can allow you to create snapshot of your transactional database for reporting purpose, sometimes they don’t quite fit the reporting requirements of an enterprise. These requirements typically are data analytics, effective schema (for an Information worker to self-service herself), historical data, better performance (flat data, no joins) etc. This is where a need for data warehouse or an OLAP system arises. A Key point to remember is a data warehouse is mostly a relational database. It’s built on top of same concepts like Tables, Rows, Columns, Primary keys, Foreign Keys, etc. Before we talk about how data warehouses are typically structured let’s understand key components that can create a data flow between OLTP systems and OLAP systems. There are 3 major areas to it: a) OLTP system should be capable of tracking its changes as all these changes should go back to data warehouse for historical recording. For e.g. if an OLTP transaction moves a customer from silver to gold category, OLTP system needs to ensure that this change is tracked and send to data warehouse for reporting purpose. A report in context could be how many customers divided by geographies moved from sliver to gold category. In data warehouse terminology this process is called Change Data Capture. There are quite a few systems that leverage database triggers to move these changes to corresponding tracking tables. There are also out of box features provided by some databases e.g. SQL Server 2008 offers Change Data Capture and Change Tracking for addressing such requirements. b) After we make the OLTP system capable of tracking its changes we need to provision a batch process that can run periodically and takes these changes from OLTP system and dump them into data warehouse. There are many tools out there that can help you fill this gap – SQL Server Integration Services happens to be one of them. c) So we have an OLTP system that knows how to track its changes, we have jobs that run periodically to move these changes to warehouse. The question though remains is how warehouse will record these changes? This structural change in data warehouse arena is often covered under something called Slowly Changing Dimension (SCD). While we will talk about dimensions in a while, SCD can be applied to pure relational tables too. SCD enables a database structure to capture historical data. This would create multiple records for a given entity in relational database and data warehouses prefer having their own primary key, often known as surrogate key. As I mentioned a data warehouse is just a relational database but industry often attributes a specific schema style to data warehouses. These styles are Star Schema or Snowflake Schema. The motivation behind these styles is to create a flat database structure (as opposed to normalized one), which is easy to understand / use, easy to query and easy to slice / dice. Star schema is a database structure made up of dimensions and facts. Facts are generally the numbers (sales, quantity, etc.) that you want to slice and dice. Fact tables have these numbers and have references (foreign keys) to set of tables that provide context around those facts. E.g. if you have recorded 10,000 USD as sales that number would go in a sales fact table and could have foreign keys attached to it that refers to the sales agent responsible for sale and to time table which contains the dates between which that sale was made. These agent and time tables are called dimensions which provide context to the numbers stored in fact tables. This schema structure of fact being at center surrounded by dimensions is called Star schema. A similar structure with difference of dimension tables being normalized is called a Snowflake schema. This relational structure of facts and dimensions serves as an input for another analysis structure called Cube. Though physically Cube is a special structure supported by commercial databases like SQL Server Analysis Services, logically it’s a multidimensional structure where dimensions define the sides of cube and facts define the content. Facts are often called as Measures inside a cube. Dimensions often tend to form a hierarchy. E.g. Product may be broken into categories and categories in turn to individual items. Category and Items are often referred as Levels and their constituents as Members with their overall structure called as Hierarchy. Measures are rolled up as per dimensional hierarchy. These rolled up measures are called Aggregates. Now this may seem like an overwhelming vocabulary to deal with but don’t worry it will sink in as you start working with Cubes and others. Let’s see few other terms that we would run into while talking about data warehouses. ODS or an Operational Data Store is a frequently misused term. There would be few users in your organization that want to report on most current data and can’t afford to miss a single transaction for their report. Then there is another set of users that typically don’t care how current the data is. Mostly senior level executives who are interesting in trending, mining, forecasting, strategizing, etc. don’t care for that one specific transaction. This is where an ODS can come in handy. ODS can use the same star schema and the OLAP cubes we saw earlier. The only difference is that the data inside an ODS would be short lived, i.e. for few months and ODS would sync with OLTP system every few minutes. Data warehouse can periodically sync with ODS either daily or weekly depending on business drivers. Data marts are another frequently talked about topic in data warehousing. They are subject-specific data warehouse. Data warehouses that try to span over an enterprise are normally too big to scope, build, manage, track, etc. Hence they are often scaled down to something called Data mart that supports a specific segment of business like sales, marketing, or support. Data marts too, are often designed using star schema model discussed earlier. Industry is divided when it comes to use of data marts. Some experts prefer having data marts along with a central data warehouse. Data warehouse here acts as information staging and distribution hub with spokes being data marts connected via data feeds serving summarized data. Others eliminate the need for a centralized data warehouse citing that most users want to report on detailed data. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Business Intelligence, Data Warehousing, Database, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Camera wont stay behind model after pitch, then rotation

  - by ChocoMan

  I have a camera position behind a model. Currently, if I push the left thumbstick making my model move forward, backward, or strafe, the camera stays with the model. If I push the right thumbstick left or right, the model rotates in those directions fine along with the camera rotating while maintaining its position relatively behind the model. But when I pitch the model up or down, then rotate the model afterwards, the camera moves slightly rotates in a clock-like fashion behind the model. If I do a few rotations of the model and try to pitch the camera, the camera will eventually be looking at the side, then eventually the front of the model while also rotating in a clock-like fashion. My question is, how do I keep the camera to pitch up and down behind the model no matter how much the model has rotated? Here is what I got: // Rotates model and pitches camera on its own axis public void modelRotMovement(GamePadState pController) { // Rotates Camera with model Yaw = pController.ThumbSticks.Right.X * MathHelper.ToRadians(angularSpeed); // Pitches Camera around model Pitch = pController.ThumbSticks.Right.Y * MathHelper.ToRadians(angularSpeed); AddRotation = Quaternion.CreateFromYawPitchRoll(Yaw, 0, 0); ModelLoad.MRotation *= AddRotation; MOrientation = Matrix.CreateFromQuaternion(ModelLoad.MRotation); } // Orbit (yaw) Camera around with model (only seeing back of model) public void cameraYaw(Vector3 axisYaw, float yaw) { ModelLoad.CameraPos = Vector3.Transform(ModelLoad.CameraPos - ModelLoad.camTarget, Matrix.CreateFromAxisAngle(axisYaw, yaw)) + ModelLoad.camTarget; } // Raise camera above or below model's shoulders public void cameraPitch(Vector3 axisPitch, float pitch) { ModelLoad.CameraPos = Vector3.Transform(ModelLoad.CameraPos - ModelLoad.camTarget, Matrix.CreateFromAxisAngle(axisPitch, pitch)) + ModelLoad.camTarget; } // Call in update method public void updateCamera() { cameraYaw(Vector3.Up, Yaw); cameraPitch(Vector3.Right, Pitch); } NOTE: I tried to use addPitch just like addRotation but it didn't work...

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• How to Assure an Effective Data Model

  As a general rule in my opinion the effectiveness of a data model can be directly related to the accuracy and complexity of a project’s requirements. For example there is no need to work on very detailed data models when the details surrounding a specific data model have not been defined or even clarified. Developing data models when the clarity of project requirements is limited tends to introduce designed issues because the proper details to create an effective data model are not even known. One way to avoid this issue is to create data models that correspond to the complexity of the existing project requirements so that when requirements are updated then new data models can be created based any new discoveries regarding requirements on a fine grain level.  This allows for data models to be composed of general entities to be created initially when a project’s requirements are very vague and then the entities are refined as new and more substantial requirements are defined or redefined. This promotes communication amongst all stakeholders within a project as they go through the process of defining and finalizing project requirements.In addition, here are some general tips that can be applied to projects in regards to data modeling.Initially model all data generally and slowly reactor the data model as new requirements and business constraints are applied to a project.Ensure that data modelers have the proper tools and training they need to design a data model accurately.Create a common location for all project documents so that everyone will be able to review a project’s data models along with any other project documentation.All data models should follow a clear naming schema that tells readers the intended purpose for the data and how it is going to be applied within a project.

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• Data Mining Resources

  - by Dejan Sarka

  There are many different types of analyses, each one with its own pros and cons. Relational reports have a predefined structure, and end users cannot change it. They are simple to use for end users. Reports can use real-time data and snapshots of data to show the state of a report at specific points in time. One of the drawbacks is that report authoring is limited to IT pros and advanced users. Any kind of dynamic restructuring is very limited. If real-time data is used for a report, the report has a negative impact on the performance of the source system. Processing of the reports might be slow because the data comes from relational database management systems, which are not optimized for reporting only. If you create a semantic model of your data, your end users can create ad-hoc report structures. However, the development is more complex because a developer is needed to create these semantic models. For OLAP, you typically use specialized database management systems. You get lightning speed of analyses. End users can use rich and thin clients to interactively change the structure of the report. Typically, they do it graphically. However, the development of an OLAP system is many times quite complex. It involves the preparation and maintenance of an enterprise data warehouse and OLAP cubes. In order to exploit the possibility of real-time restructuring of reports, the users must be both active and educated. The data is usually stale, as it is loaded into data warehouses and OLAP cubes with a scheduled process. With data mining, a structure is not selected in advance; it searches for the structure. As a result, data mining can give you the most valuable results because you can discover patterns you did not expect. A data mining model structure is limited only by the attributes that you use to train the model. One of the drawbacks is that a lot of knowledge is needed for a successful data mining project. End users have to understand the results. Subject matter experts and IT professionals need to understand business problem thoroughly. The development might be sometimes even more complex than the development of OLAP cubes. Each type of analysis has its own place in an enterprise system. SQL Server has tools for all kinds of analyses. However, data mining is the most advanced way of analyzing the data; this is the “I” in BI. In order to get the most out of it, you need to learn quite a lot. In this blog post, I am gathering together resources for learning, including forthcoming events. Books Multiple authors: SQL Server MVP Deep Dives – I wrote an introductory data mining chapter there. Erik Veerman, Teo Lachev and Dejan Sarka: MCTS Self-Paced Training Kit (Exam 70-448): Microsoft SQL Server 2008 - Business Intelligence Development and Maintenance – you can find a good overview of a complete BI solution, including data mining, in this book. Jamie MacLennan, ZhaoHui Tang, and Bogdan Crivat: Data Mining with Microsoft SQL Server 2008 – can’t miss this book if you want to mine your data with SQL Server tools. Michael Berry, Gordon Linoff: Mastering Data Mining: The Art and Science of Customer Relationship Management – data mining from both, business and technical perspective. Dorian Pyle: Data Preparation for Data Mining – an in-depth book about data preparation. Thomas and Ronald Wonnacott: Introductory Statistics – if you thought that you could get away without statistics, then you are not serious about data mining. Jiawei Han and Micheline Kamber: Data Mining Concepts and Techniques – in-depth explanation of the most popular data mining algorithms. Michael Berry and Gordon Linoff: Data Mining Techniques – another book that explains data mining algorithms, more fro a business perspective. Paolo Guidici: Applied Data Mining – very mathematical book, only if you enjoy statistics and mathematics in general. Forthcoming presentations I am presenting two data mining related sessions during the PASS Summit in Charlotte, NC: Wednesday, October 16th, 2013 - Fraud Detection: Notes from the Field – I am showing how to use data mining for a specific business problem. The presentation is based on real-life projects. Friday, October 18th: Excel 2013 Advanced Analytics – I am focusing on Excel Data Mining Add-ins, and how to use them together with Power Pivot and other add-ins. This is the most you can get out of Excel. Sinergija 2013, Belgrade, Serbia Tuesday, October 22nd: Excel 2013 Analytics to the Max – another presentation focusing on the most advanced analytics you can get in Excel. SQL Rally Amsterdam, Netherlands Thursday, November 7th: Advanced Analytics in Excel 2013 – and again I am presenting about data mining in Excel. Why three different titles for the same presentation? I don’t know, I guess I forgot the name I proposed every time right after I sent the proposal. Courses Data Mining with SQL Server 2012 – I wrote a 3-day course for SolidQ. If you are interested in this course, which I could also deliver in a shorter seminar way, you can contact your closes SolidQ subsidiary, or, of course, me directly on addresses [email protected] or [email protected]. This course could also complement the existing courseware portfolio of training providers, which are welcome to contact me as well. OK, now you know: no more excuses, start learning data mining, get the most out of your data

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• Looking for Cutting-Edge Data Integration: 2010 Innovation Awards

  - by dain.hansen

  This year's Oracle Fusion Middleware Innovation Awards will honor customers and partners who are creatively using to various products across Oracle Fusion Middleware. Brand new to this year's awards is a category for Data Integration. Think you have something unique and innovative with one of our Oracle Data Integration products? We'd love to hear from you! Please submit today The deadline for the nomination is 5 p.m. PT Friday, August 6th 2010, and winning organizations will be notified by late August 2010. What you win! FREE pass to Oracle OpenWorld 2010 in San Francisco for select winners in each category. Honored by Oracle executives at awards ceremony held during Oracle OpenWorld 2010 in San Francisco. Oracle Middleware Innovation Award Winner Plaque 1-3 meetings with Oracle Executives during Oracle OpenWorld 2010 Feature article placement in Oracle Magazine and placement in Oracle Press Release Customer snapshot and video testimonial opportunity, to be hosted on oracle.com Podcast interview opportunity with Senior Oracle Executive

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• Data Integration 12c Raising the Big Data Roof at Oracle OpenWorld

  - by Tanu Sood

  Normal 0 false false false EN-US X-NONE X-NONE /* 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-family:"Times New Roman","serif"; mso-fareast-font-family:"MS Mincho";} Author: Dain Hansen, Director, Oracle It was an exciting OpenWorld 2013 for us in the Data Integration track. Our theme this year was all about ‘being future ready’ - previewing one of our biggest releases this year: Oracle Data Integration 12c. Just this week we followed up with this preview by announcing the general availability of 12c release for Oracle’s key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. Normal 0 false false false EN-US X-NONE X-NONE /* 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-family:"Times New Roman","serif"; mso-fareast-font-family:"MS Mincho";} Mark Hurd's keynote on day one set the tone for the Data Integration sessions. Mark focused on big data analytics and the changing consumer expectations. Especially real-time insight is a key theme for Oracle overall and data integration products. In Mark Hurd's keynote we heard from key customers, such as Airbus and Thomson Reuters, how real-time analysis of operational data including machine data creates value, in some cases even saves lives. Thomas Kurian gave a deeper look into Oracle's big data and fast data solutions. In the initial lead Data Integration track session - Brad Adelberg, VP of Development, presented Oracle’s Data Integration 12c product strategy based on key trends from the initial OpenWorld keynotes. Brad talked about how Oracle's data integration products address the new data integration requirements that evolved with cloud computing, big data, and changing consumer expectations and how they set the key themes in our products’ road map. Brad explained why and how fast-time to value, high-performance and future-ready solutions is the top focus areas for product development. If you were not able to attend OpenWorld or this session I recommend reading the white paper: Five New Data Integration Requirements and How to Meet them with Oracle Data Integration, which provides an in-depth look into how Oracle addresses the new trends in the DI market. Following Brad’s session, Nick Wagner provided in depth review of Oracle GoldenGate’s latest features and roadmap. Nick discussed how Oracle GoldenGate’s tight integration with Oracle Database sets the product apart from the competition. We also heard that heterogeneity of the product is still a major focus for GoldenGate’s development and there will be more news on that front when there is a major release. Normal 0 false false false EN-US X-NONE X-NONE /* 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-family:"Times New Roman","serif"; mso-fareast-font-family:"MS Mincho";} After GoldenGate’s product strategy session, Denis Gray from the PM team presented Oracle Data Integrator’s product strategy session, talking about the latest and greatest on ODI. Another good session was delivered by long-time GoldenGate users, Comcast.  Jason Hurd and Amit Patel of Comcast talked about the various use cases they deploy Oracle GoldenGate throughout their enterprise, from database upgrades, feeding reporting systems, to active-active database synchronization.  The Comcast team shared many good tips on how to use GoldenGate for both zero downtime upgrades and active-active replication with conflict management requirement. One of our other important goals we had this year for the Data Integration track at OpenWorld was hearing from our customers. We ended day 1 on just that, with a wonderful award ceremony for Oracle Excellence Awards for Oracle Fusion Middleware Innovation. The ceremony was held in the Yerba Buena Center for the Arts. Congratulations to Royal Bank of Scotland and Yalumba Wine Company, the winners in the Data Integration category. You can find more information on the award and the winners in our previous blog post: 2013 Oracle Excellence Awards for Fusion Middleware Innovation… Selected for their innovation use of Oracle’s Data Integration products; the winners for the Data Integration Category are Royal Bank of Scotland and The Yalumba Wine Company. Congratulations!!! Royal Bank of Scotland’s Market and International Banking division provides clients across the globe with seamless trading and competitive pricing, underpinned by a deep knowledge of risk management across the full spectrum of financial products. They handle millions of transactions daily to keep the lifeblood of their clients’ businesses flowing – whether through payment management solutions or through bespoke trade finance solutions. Royal Bank of Scotland is leveraging Oracle GoldenGate and Oracle Data Integrator along with Oracle Business Intelligence Enterprise Edition and the Oracle Database for a variety of solutions. Mainly, Oracle GoldenGate and Oracle Data Integrator are used to feed their data warehouse – providing a real-time data integration solution that feeds transactional data to their analytics system in minutes to enable improved decision making with timely, accurate data for their business users. Oracle Data Integrator’s in-database transformation capabilities and its ability to integrate with Oracle GoldenGate for real-time data capture is the foundation of this implementation. This solution makes it such that changes happening in the analytics systems are available the same day they are deployed on the operational system with 100% data quality guaranteed. Additionally, the solution has helped to reduce their operational database size from 150GB to 10GB. Impressive! Now what if I told you this solution was built in 3 months and had a less than 6 month return on investment? That’s outstanding! The Yalumba Wine Company is situated in the Barossa Valley of Australia. It is the oldest family owned winery in Australia with a unique way of aging their wines in specially crafted 100 liter barrels. Did you know that “Yalumba” is Aboriginal for “all the land around”? The Yalumba Wine Company is growing rapidly, and was in need of introducing a more modern standard to the existing manufacturing processes to meet globalization demands, overall time-to-market, and better operational efficiency objectives of product development. The Yalumba Wine Company worked with a partner, Bristlecone to develop a unique solution whereby Oracle Data Integrator is leveraged to pull data from Salesforce.com and JD Edwards, in addition to their other pre-existing source systems, for consumption into their data warehouse. They have emphasized the overall ease of developing integration workflows with Oracle Data Integrator. The solution has brought better visibility for the business users, shorter data loading and transformation performance to their data warehouse with rapid incorporation of new data sources, and a solid future-proof foundation for their organization. Moving forward, they plan on leveraging more from Oracle’s Data Integration portfolio. Terrific! In addition to these two customers on Tuesday we featured many other important Oracle Data Integrator and Oracle GoldenGate customers. On Tuesday the GoldenGate panel included: Land O’Lakes, Smuckers, and Veolia Water. Besides giving us yummy nutrition and healthy water, these companies have another aspect in common. They all use GoldenGate to boost their ERP application. Please read the recap by Irem Radzik. On Wednesday, the ODI Panel included: Barry Ralston and Ryan Weber of Infinity Insurance, Paul Stracke of Paychex Inc., and Ian Wall of Vertex Pharmaceuticals for a session filled with interesting projects, use cases and approaches to leveraging Oracle Data Integrator. Please read the recap by Sandrine Riley for more. Thanks to everyone who joined with us and we hope to stay connected! To hear more about our Data Integration12c products join us in an upcoming webcast to learn more. Follow us www.twitter.com/ORCLGoldenGate or goto our website at www.oracle.com/goto/dataintegration

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• Core Data Model Design Question - Changing "Live" Objects also Changes Saved Objects

  - by mwt

  I'm working on my first Core Data project (on iPhone) and am really liking it. Core Data is cool stuff. I am, however, running into a design difficulty that I'm not sure how to solve, although I imagine it's a fairly common situation. It concerns the data model. For the sake of clarity, I'll use an imaginary football game app as an example to illustrate my question. Say that there are NSMO's called Downs and Plays. Plays function like templates to be used by Downs. The user creates Plays (for example, Bootleg, Button Hook, Slant Route, Sweep, etc.) and fills in the various properties. Plays have a to-many relationship with Downs. For each Down, the user decides which Play to use. When the Down is executed, it uses the Play as its template. After each down is run, it is stored in history. The program remembers all the Downs ever played. So far, so good. This is all working fine. The question I have concerns what happens when the user wants to change the details of a Play. Let's say it originally involved a pass to the left, but the user now wants it to be a pass to the right. Making that change, however, not only affects all the future executions of that Play, but also changes the details of the Plays stored in history. The record of Downs gets "polluted," in effect, because the Play template has been changed. I have been rolling around several possible fixes to this situation, but I imagine the geniuses of SO know much more about how to handle this than I do. Still, the potential fixes I've come up with are: 1) "Versioning" of Plays. Each change to a Play template actually creates a new, separate Play object with the same name (as far as the user can tell). Underneath the hood, however, it is actually a different Play. This would work, AFAICT, but seems like it could potentially lead to a wild proliferation of Play objects, esp. if the user keeps switching back and forth between several versions of the same Play (creating object after object each time the user switches). Yes, the app could check for pre-existing, identical Plays, but... it just seems like a mess. 2) Have Downs, upon saving, record the details of the Play they used, but not as a Play object. This just seems ridiculous, given that the Play object is there to hold those just those details. 3) Recognize that Play objects are actually fulfilling 2 functions: one to be a template for a Down, and the other to record what template was used. These 2 functions have a different relationship with a Down. The first (template) has a to-many relationship. But the second (record) has a one-to-one relationship. This would mean creating a second object, something like "Play-Template" which would retain the to-many relationship with Downs. Play objects would get reconfigured to have a one-to-one relationship with Downs. A Down would use a Play-Template object for execution, but use the new kind of Play object to store what template was used. It is this change from a to-many relationship to a one-to-one relationship that represents the crux of the problem. Even writing this question out has helped me get clearer. I think something like solution 3 is the answer. However if anyone has a better idea or even just a confirmation that I'm on the right track, that would be helpful. (Remember, I'm not really making a football game, it's just faster/easier to use a metaphor everyone understands.) Thanks.

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• Fast Data - Big Data's achilles heel

  - by thegreeneman

  At OOW 2013 in Mark Hurd and Thomas Kurian's keynote, they discussed Oracle's Fast Data software solution stack and discussed a number of customers deploying Oracle's Big Data / Fast Data solutions and in particular Oracle's NoSQL Database.  Since that time, there have been a large number of request seeking clarification on how the Fast Data software stack works together to deliver on the promise of real-time Big Data solutions.   Fast Data is a software solution stack that deals with one aspect of Big Data, high velocity.   The software in the Fast Data solution stack involves 3 key pieces and their integration:  Oracle Event Processing, Oracle Coherence, Oracle NoSQL Database.   All three of these technologies address a high throughput, low latency data management requirement.   Oracle Event Processing enables continuous query to filter the Big Data fire hose, enable intelligent chained events to real-time service invocation and augments the data stream to provide Big Data enrichment. Extended SQL syntax allows the definition of sliding windows of time to allow SQL statements to look for triggers on events like breach of weighted moving average on a real-time data stream.    Oracle Coherence is a distributed, grid caching solution which is used to provide very low latency access to cached data when the data is too big to fit into a single process, so it is spread around in a grid architecture to provide memory latency speed access.  It also has some special capabilities to deploy remote behavioral execution for "near data" processing.   The Oracle NoSQL Database is designed to ingest simple key-value data at a controlled throughput rate while providing data redundancy in a cluster to facilitate highly concurrent low latency reads.  For example, when large sensor networks are generating data that need to be captured while analysts are simultaneously extracting the data using range based queries for upstream analytics.  Another example might be storing cookies from user web sessions for ultra low latency user profile management, also leveraging that data using holistic MapReduce operations with your Hadoop cluster to do segmented site analysis.  Understand how NoSQL plays a critical role in Big Data capture and enrichment while simultaneously providing a low latency and scalable data management infrastructure thru clustered, always on, parallel processing in a shared nothing architecture. Learn how easily a NoSQL cluster can be deployed to provide essential services in industry specific Fast Data solutions. See these technologies work together in a demonstration highlighting the salient features of these Fast Data enabling technologies in a location based personalization service. The question then becomes how do these things work together to deliver an end to end Fast Data solution.  The answer is that while different applications will exhibit unique requirements that may drive the need for one or the other of these technologies, often when it comes to Big Data you may need to use them together.   You may have the need for the memory latencies of the Coherence cache, but just have too much data to cache, so you use a combination of Coherence and Oracle NoSQL to handle extreme speed cache overflow and retrieval.   Here is a great reference to how these two technologies are integrated and work together.  Coherence & Oracle NoSQL Database.   On the stream processing side, it is similar as with the Coherence case.  As your sliding windows get larger, holding all the data in the stream can become difficult and out of band data may need to be offloaded into persistent storage.  OEP needs an extreme speed database like Oracle NoSQL Database to help it continue to perform for the real time loop while dealing with persistent spill in the data stream.  Here is a great resource to learn more about how OEP and Oracle NoSQL Database are integrated and work together.  OEP & Oracle NoSQL Database.

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• Oracle Announces Oracle Big Data Appliance X3-2 and Enhanced Oracle Big Data Connectors

  - by jgelhaus

  Enables Customers to Easily Harness the Business Value of Big Data at Lower Cost Engineered System Simplifies Big Data for the Enterprise Oracle Big Data Appliance X3-2 hardware features the latest 8-core Intel® Xeon E5-2600 series of processors, and compared with previous generation, the 18 compute and storage servers with 648 TB raw storage now offer: 33 percent more processing power with 288 CPU cores; 33 percent more memory per node with 1.1 TB of main memory; and up to a 30 percent reduction in power and cooling Oracle Big Data Appliance X3-2 further simplifies implementation and management of big data by integrating all the hardware and software required to acquire, organize and analyze big data. It includes: Support for CDH4.1 including software upgrades developed collaboratively with Cloudera to simplify NameNode High Availability in Hadoop, eliminating the single point of failure in a Hadoop cluster; Oracle NoSQL Database Community Edition 2.0, the latest version that brings better Hadoop integration, elastic scaling and new APIs, including JSON and C support; The Oracle Enterprise Manager plug-in for Big Data Appliance that complements Cloudera Manager to enable users to more easily manage a Hadoop cluster; Updated distributions of Oracle Linux and Oracle Java Development Kit; An updated distribution of open source R, optimized to work with high performance multi-threaded math libraries Read More   Data sheet: Oracle Big Data Appliance X3-2 Oracle Big Data Appliance: Datacenter Network Integration Big Data and Natural Language: Extracting Insight From Text Thomson Reuters Discusses Oracle's Big Data Platform Connectors Integrate Hadoop with Oracle Big Data Ecosystem Oracle Big Data Connectors is a suite of software built by Oracle to integrate Apache Hadoop with Oracle Database, Oracle Data Integrator, and Oracle R Distribution. Enhancements to Oracle Big Data Connectors extend these data integration capabilities. With updates to every connector, this release includes: Oracle SQL Connector for Hadoop Distributed File System, for high performance SQL queries on Hadoop data from Oracle Database, enhanced with increased automation and querying of Hive tables and now supported within the Oracle Data Integrator Application Adapter for Hadoop; Transparent access to the Hive Query language from R and introduction of new analytic techniques executing natively in Hadoop, enabling R developers to be more productive by increasing access to Hadoop in the R environment. Read More Data sheet: Oracle Big Data Connectors High Performance Connectors for Load and Access of Data from Hadoop to Oracle Database

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• Best approach to accessing multiple data source in a web application

  - by ced

  I've a base web application developed with .net technologies (asp.net) used into our LAN by 30 users simultanousley. From this web application I've developed two verticalization used from online users. In future i expect hundreds users simultanousley. Our company has different locations. Each site use its own database. The web application needs to retrieve information from all existing databases. Currently there are 3 database, but it's not excluded in the future expansion of new offices. My question then is: What is the best strategy for a web application to retrieve information from different databases (which have the same schema) whereas the main objective performance data access and high fault tolerance? There are case studies in the literature that I can take as an example? Do you know some good documents to study? Do you have any tips to implement this task so efficient? Intuitively I would say that two possible strategy are: perform queries from different sources in real time and aggregate data on the fly; create a repository that contains the union of the entities of interest and perform queries directly on repository;

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