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• Design Time Attribute For CSS Class in ASP.net Custom Server Control

  - by Jon P

  Hopefully some Custom Control Designers/Builders can help I'm attempting to build my first custom control that is essential a client detail collection form. There are to be a series of elements to this form that require various styles applied to them. Ideally I'd like the VS 2005/2008 properties interface to be able to apply the CSSClass as it does at the control level, i.e. with a dropdown list of available CSS Clases. Take for example the Class to be applied to the legend tag /// <summary>Css Class for Legend</summary> [Category("Appearance")] [Browsable(true)] [DefaultValue("")] //I am at a loss as to what goes in [Editor] [Editor(System.Web.UI.CssStyleCollection), typeof(System.Drawing.Design.UITypeEditor))] public string LegendCSSClass { get { return _LegendCSSClass; } set { _LegendCSSClass = value; } } I have tried a couple of options, as you can see from above, without much luck. Hopefully there is something simple I am missing. I'd also be happy for references pertaining to the [Editor] attribute

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• Importing Multiple Schemas to a Model in Oracle SQL Developer Data Modeler

  - by thatjeffsmith

  Your physical data model might stretch across multiple Oracle schemas. Or maybe you just want a single diagram containing tables, views, etc. spanning more than a single user in the database. The process for importing a data dictionary is the same, regardless if you want to suck in objects from one schema, or many schemas. Let’s take a quick look at how to get started with a data dictionary import. I’m using Oracle SQL Developer in this example. The process is nearly identical in Oracle SQL Developer Data Modeler – the only difference being you’ll use the ‘File’ menu to get started versus the ‘File – Data Modeler’ menu in SQL Developer. Remember, the functionality is exactly the same whether you use SQL Developer or SQL Developer Data Modeler when it comes to the data modeling features – you’ll just have a cleaner user interface in SQL Developer Data Modeler. Importing a Data Dictionary to a Model You’ll want to open or create your model first. You can import objects to an existing or new model. The easiest way to get started is to simply open the ‘Browser’ under the View menu. The Browser allows you to navigate your open designs/models You’ll see an ‘Untitled_1′ model by default. I’ve renamed mine to ‘hr_sh_scott_demo.’ Now go back to the File menu, and expand the ‘Data Modeler’ section, and select ‘Import – Data Dictionary.’ This is a fancy way of saying, ‘suck objects out of the database into my model’ Connect! If you haven’t already defined a connection to the database you want to reverse engineer, you’ll need to do that now. I’m going to assume you already have that connection – so select it, and hit the ‘Next’ button. Select the Schema(s) to be imported Select one or more schemas you want to import The schemas selected on this page of the wizard will dictate the lists of tables, views, synonyms, and everything else you can choose from in the next wizard step to import. For brevity, I have selected ALL tables, views, and synonyms from 3 different schemas: HR SCOTT SH Once I hit the ‘Finish’ button in the wizard, SQL Developer will interrogate the database and add the objects to our model. The Big Model and the 3 Little Models I can now see ALL of the objects I just imported in the ‘hr_sh_scott_demo’ relational model in my design tree, and in my relational diagram. Quick Tip: Oracle SQL Developer calls what most folks think of as a ‘Physical Model’ the ‘Relational Model.’ Same difference, mostly. In SQL Developer, a Physical model allows you to define partitioning schemes, advanced storage parameters, and add your PL/SQL code. You can have multiple physical models per relational models. For example I might have a 4 Node RAC in Production that uses partitioning, but in test/dev, only have a single instance with no partitioning. I can have models for both of those physical implementations. The list of tables in my relational model Wouldn’t it be nice if I could segregate the objects based on their schema? Good news, you can! And it’s done by default Several of you might already know where I’m going with this – SUBVIEWS. You can easily create a ‘SubView’ by selecting one or more objects in your model or diagram and add them to a new SubView. SubViews are just mini-models. They contain a subset of objects from the main model. This is very handy when you want to break your model into smaller, more digestible parts. The model information is identical across the model and subviews, so you don’t have to worry about making a change in one place and not having it propagate across your design. SubViews can be used as filters when you create reports and exports as well. So instead of generating a PDF for everything, just show me what’s in my ‘ABC’ subview. But, I don’t want to do any work! Remember, I’m really lazy. More good news – it’s already done by default! The schemas are automatically used to create default SubViews Auto-Navigate to the Object in the Diagram In the subview tree node, right-click on the object you want to navigate to. You can ask to be taken to the main model view or to the SubView location. If you haven’t already opened the SubView in the diagram, it will be automatically opened for you. The SubView diagram only contains the objects from that SubView Your SubView might still be pretty big, many dozens of objects, so don’t forget about the ‘Navigator‘ either! In summary, use the ‘Import’ feature to add existing database objects to your model. If you import from multiple schemas, take advantage of the default schema based SubViews to help you manage your models! Sometimes less is more!

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• Deploying Data Mining Models using Model Export and Import, Part 2

  - by [email protected]

  In my last post, Deploying Data Mining Models using Model Export and Import, we explored using DBMS_DATA_MINING.EXPORT_MODEL and DBMS_DATA_MINING.IMPORT_MODEL to enable moving a model from one system to another. In this post, we'll look at two distributed scenarios that make use of this capability and a tip for easily moving models from one machine to another using only Oracle Database, not an external file transport mechanism, such as FTP. The first scenario, consider a company with geographically distributed business units, each collecting and managing their data locally for the products they sell. Each business unit has in-house data analysts that build models to predict which products to recommend to customers in their space. A central telemarketing business unit also uses these models to score new customers locally using data collected over the phone. Since the models recommend different products, each customer is scored using each model. This is depicted in Figure 1.Figure 1: Target instance importing multiple remote models for local scoring In the second scenario, consider multiple hospitals that collect data on patients with certain types of cancer. The data collection is standardized, so each hospital collects the same patient demographic and other health / tumor data, along with the clinical diagnosis. Instead of each hospital building it's own models, the data is pooled at a central data analysis lab where a predictive model is built. Once completed, the model is distributed to hospitals, clinics, and doctor offices who can score patient data locally.Figure 2: Multiple target instances importing the same model from a source instance for local scoring Since this blog focuses on model export and import, we'll only discuss what is necessary to move a model from one database to another. Here, we use the package DBMS_FILE_TRANSFER, which can move files between Oracle databases. The script is fairly straightforward, but requires setting up a database link and directory objects. We saw how to create directory objects in the previous post. To create a database link to the source database from the target, we can use, for example: create database link SOURCE1_LINK connect to <schema> identified by <password> using 'SOURCE1'; Note that 'SOURCE1' refers to the service name of the remote database entry in your tnsnames.ora file. From SQL*Plus, first connect to the remote database and export the model. Note that the model_file_name does not include the .dmp extension. This is because export_model appends "01" to this name.  Next, connect to the local database and invoke DBMS_FILE_TRANSFER.GET_FILE and import the model. Note that "01" is eliminated in the target system file name.  connect <source_schema>/<password>@SOURCE1_LINK; BEGIN  DBMS_DATA_MINING.EXPORT_MODEL ('EXPORT_FILE_NAME' || '.dmp',                                 'MY_SOURCE_DIR_OBJECT',                                 'name =''MY_MINING_MODEL'''); END; connect <target_schema>/<password>; BEGIN  DBMS_FILE_TRANSFER.GET_FILE ('MY_SOURCE_DIR_OBJECT',                               'EXPORT_FILE_NAME' || '01.dmp',                               'SOURCE1_LINK',                               'MY_TARGET_DIR_OBJECT',                               'EXPORT_FILE_NAME' || '.dmp' );  DBMS_DATA_MINING.IMPORT_MODEL ('EXPORT_FILE_NAME' || '.dmp',                                 'MY_TARGET_DIR_OBJECT'); END; To clean up afterward, you may want to drop the exported .dmp file at the source and the transferred file at the target. For example, utl_file.fremove('&directory_name', '&model_file_name' || '.dmp');

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• Abstract Data Type and Data Structure

  - by mark075

  It's quite difficult for me to understand these terms. I searched on google and read a little on Wikipedia but I'm still not sure. I've determined so far that: Abstract Data Type is a definition of new type, describes its properties and operations. Data Structure is an implementation of ADT. Many ADT can be implemented as the same Data Structure. If I think right, array as ADT means a collection of elements and as Data Structure, how it's stored in a memory. Stack is ADT with push, pop operations, but can we say about stack data structure if I mean I used stack implemented as an array in my algorithm? And why heap isn't ADT? It can be implemented as tree or an array.

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• Difference between generator expression and generator function

  - by Neil G

  Is there any difference — performance or otherwise — between generator expressions and generator functions? In [1]: def f(): ...: yield from range(4) ...: In [2]: def g(): ...: return (i for i in range(4)) ...: In [3]: f() Out[3]: <generator object f at 0x109902550> In [4]: list(f()) Out[4]: [0, 1, 2, 3] In [5]: list(g()) Out[5]: [0, 1, 2, 3] In [6]: g() Out[6]: <generator object <genexpr> at 0x1099056e0>

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• ASP.Net How to enforce the HTTP get URL format?

  - by Hamish Grubijan

  [Sorry about a messy question. I believe I am targeting .Net 2.0 (for now)] Hi, I am an ASP.NET noob. For starters I am building a page that parses a URL string and populates a table in a database. I want that string to be strictly of the form: http://<server>:<port>/PageName.aspx?A=1&B=2&C=3&D=4&E=5 The order of the arguments do not matter, I just do not want any of them missing, or any extras. Here is what I tried (yes, it is ugly; I just want to get it to work first): #if (DEBUG) // Maps parameter names to their human readable names. // Used for error checking. private static Dictionary<string, string> paramNameToDisplayName = new Dictionary<string, string> { { A, "a"}, { B, "b"}, { C, "c"}, { D, "d"}, { E, "e"}, { F, "f"}, }; [Conditional("DEBUG")] private void validateRequestParameters(HttpRequest request) { bool endResponse = false; // Use foreach var foreach (string expectedParameterName in paramNameToDisplayName.Keys) { if (request[expectedParameterName] == null) { Response.Write(String.Format("No parameter \"{0}\", aka {1} was passed to the configuration generator. Check your URL string / cookie.", expectedParameterName, paramNameToDisplayName[expectedParameterName])); endResponse = true; } } // Use foreach var foreach (string actualParameterName in request.Params) { if (!paramNameToDisplayName.ContainsKey(actualParameterName)) { Response.Write(String.Format("The parameter \"{0}\", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.", actualParameterName)); endResponse = true; } } if (endResponse) { Response.End(); } } #endif and it works ok, except that it complains about all sorts of other stuff: http://localhost:1796/AddStatusUpdate.aspx?X=0 No parameter "A", aka a was passed to the configuration generator. Check your URL string / cookie.No parameter "B", aka b was passed to the configuration generator. Check your URL string / cookie.No parameter "C", aka c was passed to the configuration generator. Check your URL string / cookie.No parameter "D", aka d was passed to the configuration generator. Check your URL string / cookie.No parameter "E", aka e was passed to the configuration generator. Check your URL string / cookie.No parameter "F", aka f was passed to the configuration generator. Check your URL string / cookie.The parameter "X", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "ASP.NET_SessionId", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "ALL_HTTP", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "ALL_RAW", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "APPL_MD_PATH", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "APPL_PHYSICAL_PATH", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "AUTH_TYPE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "AUTH_USER", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "AUTH_PASSWORD", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "LOGON_USER", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "REMOTE_USER", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_COOKIE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_FLAGS", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_ISSUER", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_KEYSIZE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_SECRETKEYSIZE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_SERIALNUMBER", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_SERVER_ISSUER", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_SERVER_SUBJECT", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CERT_SUBJECT", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CONTENT_LENGTH", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "CONTENT_TYPE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "GATEWAY_INTERFACE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTPS", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTPS_KEYSIZE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTPS_SECRETKEYSIZE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTPS_SERVER_ISSUER", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTPS_SERVER_SUBJECT", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "INSTANCE_ID", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "INSTANCE_META_PATH", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "LOCAL_ADDR", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "PATH_INFO", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "PATH_TRANSLATED", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "QUERY_STRING", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "REMOTE_ADDR", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "REMOTE_HOST", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "REMOTE_PORT", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "REQUEST_METHOD", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "SCRIPT_NAME", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "SERVER_NAME", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "SERVER_PORT", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "SERVER_PORT_SECURE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "SERVER_PROTOCOL", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "SERVER_SOFTWARE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "URL", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_CACHE_CONTROL", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_CONNECTION", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_ACCEPT", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_ACCEPT_CHARSET", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_ACCEPT_ENCODING", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_ACCEPT_LANGUAGE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_COOKIE", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_HOST", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.The parameter "HTTP_USER_AGENT", was passed to the configuration generator, but it was not expected. Check your URL string / cookie.Thread was being aborted. Is there some way for me to separate the implicit and the explicit parameters, or is it not doable? Should I even bother? Perhaps the philosophy of get is to just throw away that what is not needed. Thanks!

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• Big Data – Various Learning Resources – How to Start with Big Data? – Day 20 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned how to become a Data Scientist for Big Data. In this article we will go over various learning resources related to Big Data. In this series we have covered many of the most essential details about Big Data. At the beginning of this series, I have encouraged readers to send me questions. One of the most popular questions is - “I want to learn more about Big Data. Where can I learn it?” This is indeed a great question as there are plenty of resources out to learn about Big Data and it is indeed difficult to select on one resource to learn Big Data. Hence I decided to write here a few of the very important resources which are related to Big Data. Learn from Pluralsight Pluralsight is a global leader in high-quality online training for hardcore developers.  It has fantastic Big Data Courses and I started to learn about Big Data with the help of Pluralsight. Here are few of the courses which are directly related to Big Data. Big Data: The Big Picture Big Data Analytics with Tableau NoSQL: The Big Picture Understanding NoSQL Data Analysis Fundamentals with Tableau I encourage all of you start with this video course as they are fantastic fundamentals to learn Big Data. Learn from Apache Resources at Apache are single point the most authentic learning resources. If you want to learn fundamentals and go deep about every aspect of the Big Data, I believe you must understand various concepts in Apache’s library. I am pretty impressed with the documentation and I am personally referencing it every single day when I work with Big Data. I strongly encourage all of you to bookmark following all the links for authentic big data learning. Haddop - The Apache Hadoop® project develops open-source software for reliable, scalable, distributed computing. Ambari: A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which include support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heat maps and ability to view MapReduce, Pig and Hive applications visually along with features to diagnose their performance characteristics in a user-friendly manner. Avro: A data serialization system. Cassandra: A scalable multi-master database with no single points of failure. Chukwa: A data collection system for managing large distributed systems. HBase: A scalable, distributed database that supports structured data storage for large tables. Hive: A data warehouse infrastructure that provides data summarization and ad hoc querying. Mahout: A Scalable machine learning and data mining library. Pig: A high-level data-flow language and execution framework for parallel computation. ZooKeeper: A high-performance coordination service for distributed applications. Learn from Vendors One of the biggest issues with about learning Big Data is setting up the environment. Every Big Data vendor has different environment request and there are lots of things require to set up Big Data framework. Many of the users do not start with Big Data as they are afraid about the resources required to set up framework as well as a time commitment. Here Hortonworks have created fantastic learning environment. They have created Sandbox with everything one person needs to learn Big Data and also have provided excellent tutoring along with it. Sandbox comes with a dozen hands-on tutorial that will guide you through the basics of Hadoop as well it contains the Hortonworks Data Platform. I think Hortonworks did a fantastic job building this Sandbox and Tutorial. Though there are plenty of different Big Data Vendors I have decided to list only Hortonworks due to their unique setup. Please leave a comment if there are any other such platform to learn Big Data. I will include them over here as well. Learn from Books There are indeed few good books out there which one can refer to learn Big Data. Here are few good books which I have read. I will update the list as I will learn more. Ethics of Big Data Balancing Risk and Innovation Big Data for Dummies Head First Data Analysis: A Learner’s Guide to Big Numbers, Statistics, and Good Decisions If you search on Amazon there are millions of the books but I think above three books are a great set of books and it will give you great ideas about Big Data. Once you go through above books, you will have a clear idea about what is the next step you should follow in this series. You will be capable enough to make the right decision for yourself. Tomorrow In tomorrow’s blog post we will wrap up this series of Big Data. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Data Storage Options

  - by Kenneth

  When I was working as a website designer/engineer I primarily used databases for storage of much of my dynamic data. It was very easy and convenient to use this method and seemed like a standard practice from my research on the matter. I'm now working on shifting away from websites and into desktop applications. What are the best practices for data storage for desktop applications? I ask because I have noticed that most programs I use on a personal level don't appear to use a database for data storage unless its embedded in the program. (I'm not thinking of an application like a word processor where it makes sense to have data stored in individual files as defined by the user. Rather I'm thinking of something more along the lines of a calendar application which would need to store dates and event info and such where accessing that information would be much easier if stored in a database... at least as far as my experience would indicate.) Thanks for the input!

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• What is a Data Warehouse?

  Typically Data Warehouses are considered to be non-volatile in comparison to traditional databasesdue to the fact that data within the warehouse does not change that often.  In addition, Data Warehouses typically represent data through the use of Multidimensional Conceptual Views that allow data to be extracted based on the view and the current position within the view. Common Data Warehouse Traits Relatively Non-volatile Data Supports Data Extraction and Analysis Optimized for Data Retrieval and Analysis Multidimensional Views of Data Flexible Reporting Multi User Support Generic Dimensionality Transparent Accessible Unlimited Dimensions of Data Unlimited Aggregation levels of Data Normally, Data Warehouses are much larger then there traditional database counterparts due to the fact that they store the basis data along with derived data via Multidimensional Conceptual Views. As companies store larger and larger amounts of data, they will need a way to effectively and accurately extract analysis information that can be used to aide in formulating current and future business decisions. This process can be done currently through data mining within a Data Warehouse. Data Warehouses provide access to data derived through complex analysis, knowledge discovery and decision making. Secondly, they support the demands for high performance in regards to analyzing an organization’s existing and current data. Data Warehouses provide support for an organization’s data and acquired business knowledge.  Within a Data Warehouse multiple types of operations/sub systems are supported. Common Data Warehouse Sub Systems Online Analytical Processing (OLAP) Decision –Support Systems (DSS) Online Transaction Processing (OLTP)

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• How Do You Actually Model Data?

  Since the 1970’s Developers, Analysts and DBAs have been able to represent concepts and relations in the form of data through the use of generic symbols.  But what is data modeling?  The first time I actually heard this term I could not understand why anyone would want to display a computer on a fashion show runway. Hey, what do you expect? At that time I was a freshman in community college, and obviously this was a long time ago.  I have since had the chance to learn what data modeling truly is through using it. Data modeling is a process of breaking down information and/or requirements in to common categories called objects. Once objects start being defined then relationships start to form based on dependencies found amongst other existing objects.  Currently, there are several tools on the market that help data designer actually map out objects and their relationships through the use of symbols and lines.  These diagrams allow for designs to be review from several perspectives so that designers can ensure that they have the optimal data design for their project and that the design is flexible enough to allow for potential changes and/or extension in the future. Additionally these basic models can always be further refined to show different levels of details depending on the target audience through the use of three different types of models. Conceptual Data Model(CDM)Conceptual Data Models include all key entities and relationships giving a viewer a high level understanding of attributes. Conceptual data model are created by gathering and analyzing information from various sources pertaining to a project during the typical planning phase of a project. Logical Data Model (LDM)Logical Data Models are conceptual data models that have been expanded to include implementation details pertaining to the data that it will store. Additionally, this model typically represents an origination’s business requirements and business rules by defining various attribute data types and relationships regarding each entity. This additional information can be directly translated to the Physical Data Model which reduces the actual time need to implement it. Physical Data Model(PDMs)Physical Data Model are transformed Logical Data Models that include the necessary tables, columns, relationships, database properties for the creation of a database. This model also allows for considerations regarding performance, indexing and denormalization that are applied through database rules, data integrity. Further expanding on why we actually use models in modern application/database development can be seen in the benefits that data modeling provides for data modelers and projects themselves, Benefits of Data Modeling according to Applied Information Science Abstraction that allows data designers remove concepts and ideas form hard facts in the form of data. This gives the data designers the ability to express general concepts and/or ideas in a generic form through the use of symbols to represent data items and the relationships between the items. Transparency through the use of data models allows complex ideas to be translated in to simple symbols so that the concept can be understood by all viewpoints and limits the amount of confusion and misunderstanding. Effectiveness in regards to tuning a model for acceptable performance while maintaining affordable operational costs. In addition it allows systems to be built on a solid foundation in terms of data. I shudder at the thought of a world without data modeling, think about it? Data is everywhere in our lives. Data modeling allows for optimizing a design for performance and the reduction of duplication. If one was to design a database without data modeling then I would think that the first things to get impacted would be database performance due to poorly designed database and there would be greater chances of unnecessary data duplication that would also play in to the excessive query times because unneeded records would need to be processed. You could say that a data designer designing a database is like a box of chocolates. You will never know what kind of database you will get until after it is built.

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• Open Source/ Free alternatives to Redgate Test Data Generator

  - by Perpetualcoder

  I was wondering if there are any free / open source alternatives to RedGate's Data Generator. I do not care if the tool is script based, GUI based, written in anly language/platform. I should be able to target a SQL Server or MySQL schema and have test data generated for me which gets inserted into db directly or generate scripts for insertion.

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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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• 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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• Validating Data Using Data Annotation Attributes in ASP.NET MVC

  - by bipinjoshi

  The data entered by the end user in various form fields must be validated before it is saved in the database. Developers often use validation HTML helpers provided by ASP.NET MVC to perform the input validations. Additionally, you can also use data annotation attributes from the System.ComponentModel.DataAnnotations namespace to perform validations at the model level. Data annotation attributes are attached to the properties of the model class and enforce some validation criteria. They are capable of performing validation on the server side as well as on the client side. This article discusses the basics of using these attributes in an ASP.NET MVC application.http://www.bipinjoshi.net/articles/0a53f05f-b58c-47b1-a544-f032f5cfca58.aspx       

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• BizTalk 2009 - Creating a Custom Functoid Library

  - by StuartBrierley

  If you find that you have a need to created multiple Custom Functoids you may also choose to create a Custom Functoid Library - a single project containing many custom functoids.  As previsouly discussed, the Custom Functoid Wizard can be used to create a project with a new custom functoid inside.  But what if you want to extend this project to include more custom functoids and create your Custom Functoid Library?  First create a Custom Functoid Library project and your first Custom Functoid using the Custom Functoid Wizard. When you open your Custom Functoid Library project in Visual Studio you will see that it contains your custom functoid class file along with its resource file.  One of the items this resource file contains is the ID of the the custom functoid.  Each custom functoid needs a unique ID that is over 6000.  When creating a Custom Functoid Library I would first suggest that you delete the ID from this resource file and instead create a _FunctoidIDs class containing constants for each of your custom functoids.  In this way you can easily see which custom functoid IDs are assigned to which custom functoid and which ID is next in the sequence of availability: namespace MyCompany.BizTalk.Functoids.TestFunctoids {     class _FunctoidIDs     {         public const int TestFunctoid                       = 6001;     } } You will then need to update the base() function in your existing functoid class to reference these constant values rather than the current resource file. From:    int functoidID;    // This has to be a number greater than 6000    functoidID = System.Convert.ToInt32(resmgr.GetString("FunctoidId"));    this.ID = functoidID; To: this.ID = _FunctoidIDs.TestFunctoid; To create a new custom functoid you can copy the existing custom functoid, renaming the resultant class file as appropriate.  Once it is renamed you will need to change the Class name, ResourceName reference and Base function name in the class code to those of your new custom functoid.  You will also need to create a new constant value in the _FunctoidIDs class and update the ID reference in your code to match this.  Assuming that you need some different functionalty from your new  customfunctoid you will need to check or amend the following in your functoid class file: Min and Max connections Functoid Category Input and Output connection types The parameters and functionality of the Execute function To change the appearance of you new custom functoid you will need to check or amend the following in the functoid resource file: Name Description Tooltip Exception Icon You can change the String values by double clicking the resource file and amending the value fields in the string table. To amend the functoid icon you will need to create a 16x16 bitmap image.  Once you have saved this you are then ready to import it into the functoid resource file.  In Visual Studio change the resource view to images, right click the icon and choose import from file. You have now completed your new custom functoid and created a Custom Functoid Library.  You can test your new library of functoids by building the project, copying the resultant DLL to C:\Program Files\Microsoft BizTalk Server 2009\Developer Tools\Mapper Extensions and then resetting the toolbox in Visual Studio.

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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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• 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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• 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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• 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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• Master Data Services Employees Sample Model

  - by Davide Mauri

  I’ve been playing with Master Data Services quite a lot in those last days and I’m also monitoring the web for all available resources on it. Today I’ve found this freshly released sample available on MSDN Code Gallery: SQL Server Master Data Services Employee Sample Model http://code.msdn.microsoft.com/SSMDSEmployeeSample This sample shows how Recursive Hierarchies can be modeled in order to represent a typical organizational chart scenario where a self-relationship exists on the Employee entity. Share this post: email it! | bookmark it! | digg it! | reddit! | kick it! | live it!

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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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• Coherence - How to develop a custom push replication publisher

  - by cosmin.tudor(at)oracle.com

  CoherencePushReplicationDB.zipIn the example bellow I'm describing a way of developing a custom push replication publisher that publishes data to a database via JDBC. This example can be easily changed to publish data to other receivers (JMS,...) by performing changes to step 2 and small changes to step 3, steps that are presented bellow. I've used Eclipse as the development tool. To develop a custom push replication publishers we will need to go through 6 steps: Step 1: Create a custom publisher scheme class Step 2: Create a custom publisher class that should define what the publisher is doing. Step 3: Create a class data is performing the actions (publish to JMS, DB, etc ) for the custom publisher. Step 4: Register the new publisher against a ContentHandler. Step 5: Add the new custom publisher in the cache configuration file. Step 6: Add the custom publisher scheme class to the POF configuration file. All these steps are detailed bellow. The coherence project is attached and conclusions are presented at the end. Step 1: In the Coherence Eclipse project create a class called CustomPublisherScheme that should implement com.oracle.coherence.patterns.pushreplication.publishers.AbstractPublisherScheme. In this class define the elements of the custom-publisher-scheme element. For instance for a CustomPublisherScheme that looks like that: <sync:publisher> <sync:publisher-name>Active2-JDBC-Publisher</sync:publisher-name> <sync:publisher-scheme> <sync:custom-publisher-scheme> <sync:jdbc-string>jdbc:oracle:thin:@machine-name:1521:XE</sync:jdbc-string> <sync:username>hr</sync:username> <sync:password>hr</sync:password> </sync:custom-publisher-scheme> </sync:publisher-scheme> </sync:publisher> the code is: package com.oracle.coherence; import java.io.DataInput; import java.io.DataOutput; import java.io.IOException; import com.oracle.coherence.patterns.pushreplication.Publisher; import com.oracle.coherence.configuration.Configurable; import com.oracle.coherence.configuration.Mandatory; import com.oracle.coherence.configuration.Property; import com.oracle.coherence.configuration.parameters.ParameterScope; import com.oracle.coherence.environment.Environment; import com.tangosol.io.pof.PofReader; import com.tangosol.io.pof.PofWriter; import com.tangosol.util.ExternalizableHelper; @Configurable public class CustomPublisherScheme extends com.oracle.coherence.patterns.pushreplication.publishers.AbstractPublisherScheme { /** * */ private static final long serialVersionUID = 1L; private String jdbcString; private String username; private String password; public String getJdbcString() { return this.jdbcString; } @Property("jdbc-string") @Mandatory public void setJdbcString(String jdbcString) { this.jdbcString = jdbcString; } public String getUsername() { return username; } @Property("username") @Mandatory public void setUsername(String username) { this.username = username; } public String getPassword() { return password; } @Property("password") @Mandatory public void setPassword(String password) { this.password = password; } public Publisher realize(Environment environment, ClassLoader classLoader, ParameterScope parameterScope) { return new CustomPublisher(getJdbcString(), getUsername(), getPassword()); } public void readExternal(DataInput in) throws IOException { super.readExternal(in); this.jdbcString = ExternalizableHelper.readSafeUTF(in); this.username = ExternalizableHelper.readSafeUTF(in); this.password = ExternalizableHelper.readSafeUTF(in); } public void writeExternal(DataOutput out) throws IOException { super.writeExternal(out); ExternalizableHelper.writeSafeUTF(out, this.jdbcString); ExternalizableHelper.writeSafeUTF(out, this.username); ExternalizableHelper.writeSafeUTF(out, this.password); } public void readExternal(PofReader reader) throws IOException { super.readExternal(reader); this.jdbcString = reader.readString(100); this.username = reader.readString(101); this.password = reader.readString(102); } public void writeExternal(PofWriter writer) throws IOException { super.writeExternal(writer); writer.writeString(100, this.jdbcString); writer.writeString(101, this.username); writer.writeString(102, this.password); } } Step 2: Define what the CustomPublisher should basically do by creating a new java class called CustomPublisher that implements com.oracle.coherence.patterns.pushreplication.Publisher package com.oracle.coherence; import com.oracle.coherence.patterns.pushreplication.EntryOperation; import com.oracle.coherence.patterns.pushreplication.Publisher; import com.oracle.coherence.patterns.pushreplication.exceptions.PublisherNotReadyException; import java.io.BufferedWriter; import java.util.Iterator; public class CustomPublisher implements Publisher { private String jdbcString; private String username; private String password; private transient BufferedWriter bufferedWriter; public CustomPublisher() { } public CustomPublisher(String jdbcString, String username, String password) { this.jdbcString = jdbcString; this.username = username; this.password = password; this.bufferedWriter = null; } public String getJdbcString() { return this.jdbcString; } public String getUsername() { return username; } public String getPassword() { return password; } public void publishBatch(String cacheName, String publisherName, Iterator<EntryOperation> entryOperations) { DatabasePersistence databasePersistence = new DatabasePersistence( jdbcString, username, password); while (entryOperations.hasNext()) { EntryOperation entryOperation = (EntryOperation) entryOperations .next(); databasePersistence.databasePersist(entryOperation); } } public void start(String cacheName, String publisherName) throws PublisherNotReadyException { System.err .printf("Started: Custom JDBC Publisher for Cache %s with Publisher %s\n", new Object[] { cacheName, publisherName }); } public void stop(String cacheName, String publisherName) { System.err .printf("Stopped: Custom JDBC Publisher for Cache %s with Publisher %s\n", new Object[] { cacheName, publisherName }); } } In the publishBatch method from above we inform the publisher that he is supposed to persist data to a database: DatabasePersistence databasePersistence = new DatabasePersistence( jdbcString, username, password); while (entryOperations.hasNext()) { EntryOperation entryOperation = (EntryOperation) entryOperations .next(); databasePersistence.databasePersist(entryOperation); } Step 3: The class that deals with the persistence is a very basic one that uses JDBC to perform inserts/updates against a database. package com.oracle.coherence; import com.oracle.coherence.patterns.pushreplication.EntryOperation; import java.sql.*; import java.text.SimpleDateFormat; import com.oracle.coherence.Order; public class DatabasePersistence { public static String INSERT_OPERATION = "INSERT"; public static String UPDATE_OPERATION = "UPDATE"; public Connection dbConnection; public DatabasePersistence(String jdbcString, String username, String password) { this.dbConnection = createConnection(jdbcString, username, password); } public Connection createConnection(String jdbcString, String username, String password) { Connection connection = null; System.err.println("Connecting to: " + jdbcString + " Username: " + username + " Password: " + password); try { // Load the JDBC driver String driverName = "oracle.jdbc.driver.OracleDriver"; Class.forName(driverName); // Create a connection to the database connection = DriverManager.getConnection(jdbcString, username, password); System.err.println("Connected to:" + jdbcString + " Username: " + username + " Password: " + password); } catch (ClassNotFoundException e) { e.printStackTrace(); } // driver catch (SQLException e) { e.printStackTrace(); } return connection; } public void databasePersist(EntryOperation entryOperation) { if (entryOperation.getOperation().toString() .equalsIgnoreCase(INSERT_OPERATION)) { insert(((Order) entryOperation.getPublishableEntry().getValue())); } else if (entryOperation.getOperation().toString() .equalsIgnoreCase(UPDATE_OPERATION)) { update(((Order) entryOperation.getPublishableEntry().getValue())); } } public void update(Order order) { String update = "UPDATE Orders set QUANTITY= '" + order.getQuantity() + "', AMOUNT='" + order.getAmount() + "', ORD_DATE= '" + (new SimpleDateFormat("dd-MMM-yyyy")).format(order .getOrdDate()) + "' WHERE SYMBOL='" + order.getSymbol() + "'"; System.err.println("UPDATE = " + update); try { Statement stmt = getDbConnection().createStatement(); stmt.execute(update); stmt.close(); } catch (SQLException ex) { System.err.println("SQLException: " + ex.getMessage()); } } public void insert(Order order) { String insert = "insert into Orders values('" + order.getSymbol() + "'," + order.getQuantity() + "," + order.getAmount() + ",'" + (new SimpleDateFormat("dd-MMM-yyyy")).format(order .getOrdDate()) + "')"; System.err.println("INSERT = " + insert); try { Statement stmt = getDbConnection().createStatement(); stmt.execute(insert); stmt.close(); } catch (SQLException ex) { System.err.println("SQLException: " + ex.getMessage()); } } public Connection getDbConnection() { return dbConnection; } public void setDbConnection(Connection dbConnection) { this.dbConnection = dbConnection; } } Step 4: Now we need to register our publisher against a ContentHandler. In order to achieve that we need to create in our eclipse project a new class called CustomPushReplicationNamespaceContentHandler that should extend the com.oracle.coherence.patterns.pushreplication.configuration.PushReplicationNamespaceContentHandler. In the constructor of the new class we define a new handler for our custom publisher. package com.oracle.coherence; import com.oracle.coherence.configuration.Configurator; import com.oracle.coherence.environment.extensible.ConfigurationContext; import com.oracle.coherence.environment.extensible.ConfigurationException; import com.oracle.coherence.environment.extensible.ElementContentHandler; import com.oracle.coherence.patterns.pushreplication.PublisherScheme; import com.oracle.coherence.environment.extensible.QualifiedName; import com.oracle.coherence.patterns.pushreplication.configuration.PushReplicationNamespaceContentHandler; import com.tangosol.run.xml.XmlElement; public class CustomPushReplicationNamespaceContentHandler extends PushReplicationNamespaceContentHandler { public CustomPushReplicationNamespaceContentHandler() { super(); registerContentHandler("custom-publisher-scheme", new ElementContentHandler() { public Object onElement(ConfigurationContext context, QualifiedName qualifiedName, XmlElement xmlElement) throws ConfigurationException { PublisherScheme publisherScheme = new CustomPublisherScheme(); Configurator.configure(publisherScheme, context, qualifiedName, xmlElement); return publisherScheme; } }); } } Step 5: Now we should define our CustomPublisher in the cache configuration file according to the following documentation. <cache-config xmlns:sync="class:com.oracle.coherence.CustomPushReplicationNamespaceContentHandler" xmlns:cr="class:com.oracle.coherence.environment.extensible.namespaces.InstanceNamespaceContentHandler"> <caching-schemes> <sync:provider pof-enabled="false"> <sync:coherence-provider /> </sync:provider> <caching-scheme-mapping> <cache-mapping> <cache-name>publishing-cache</cache-name> <scheme-name>distributed-scheme-with-publishing-cachestore</scheme-name> <autostart>true</autostart> <sync:publisher> <sync:publisher-name>Active2 Publisher</sync:publisher-name> <sync:publisher-scheme> <sync:remote-cluster-publisher-scheme> <sync:remote-invocation-service-name>remote-site1</sync:remote-invocation-service-name> <sync:remote-publisher-scheme> <sync:local-cache-publisher-scheme> <sync:target-cache-name>publishing-cache</sync:target-cache-name> </sync:local-cache-publisher-scheme> </sync:remote-publisher-scheme> <sync:autostart>true</sync:autostart> </sync:remote-cluster-publisher-scheme> </sync:publisher-scheme> </sync:publisher> <sync:publisher> <sync:publisher-name>Active2-Output-Publisher</sync:publisher-name> <sync:publisher-scheme> <sync:stderr-publisher-scheme> <sync:autostart>true</sync:autostart> <sync:publish-original-value>true</sync:publish-original-value> </sync:stderr-publisher-scheme> </sync:publisher-scheme> </sync:publisher> <sync:publisher> <sync:publisher-name>Active2-JDBC-Publisher</sync:publisher-name> <sync:publisher-scheme> <sync:custom-publisher-scheme> <sync:jdbc-string>jdbc:oracle:thin:@machine_name:1521:XE</sync:jdbc-string> <sync:username>hr</sync:username> <sync:password>hr</sync:password> </sync:custom-publisher-scheme> </sync:publisher-scheme> </sync:publisher> </cache-mapping> </caching-scheme-mapping> <!-- The following scheme is required for each remote-site when using a RemoteInvocationPublisher --> <remote-invocation-scheme> <service-name>remote-site1</service-name> <initiator-config> <tcp-initiator> <remote-addresses> <socket-address> <address>localhost</address> <port>20001</port> </socket-address> </remote-addresses> <connect-timeout>2s</connect-timeout> </tcp-initiator> <outgoing-message-handler> <request-timeout>5s</request-timeout> </outgoing-message-handler> </initiator-config> </remote-invocation-scheme> <!-- END: com.oracle.coherence.patterns.pushreplication --> <proxy-scheme> <service-name>ExtendTcpProxyService</service-name> <acceptor-config> <tcp-acceptor> <local-address> <address>localhost</address> <port>20002</port> </local-address> </tcp-acceptor> </acceptor-config> <autostart>true</autostart> </proxy-scheme> </caching-schemes> </cache-config> As you can see in the red-marked text from above I've:       - set new Namespace Content Handler       - define the new custom publisher that should work together with other publishers like: stderr and remote publishers in our case. Step 6: Add the com.oracle.coherence.CustomPublisherScheme to your custom-pof-config file: <pof-config> <user-type-list> <!-- Built in types --> <include>coherence-pof-config.xml</include> <include>coherence-common-pof-config.xml</include> <include>coherence-messagingpattern-pof-config.xml</include> <include>coherence-pushreplicationpattern-pof-config.xml</include> <!-- Application types --> <user-type> <type-id>1901</type-id> <class-name>com.oracle.coherence.Order</class-name> <serializer> <class-name>com.oracle.coherence.OrderSerializer</class-name> </serializer> </user-type> <user-type> <type-id>1902</type-id> <class-name>com.oracle.coherence.CustomPublisherScheme</class-name> </user-type> </user-type-list> </pof-config> CONCLUSIONSThis approach allows for publishers to publish data to almost any other receiver (database, JMS, MQ, ...). The only thing that needs to be changed is the DatabasePersistence.java class that should be adapted to the chosen receiver. Only minor changes are needed for the rest of the code (to publishBatch method from CustomPublisher class).

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