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  • How to Secure a Data Role by Multiple Business Units

    - by Elie Wazen
    In this post we will see how a Role can be data secured by multiple Business Units (BUs).  Separate Data Roles are generally created for each BU if a corresponding data template generates roles on the basis of the BU dimension. The advantage of creating a policy with a rule that includes multiple BUs is that while mapping these roles in HCM Role Provisioning Rules, fewer number of entires need to be made. This could facilitate maintenance for enterprises with a large number of Business Units. Note: The example below applies as well if the securing entity is Inventory Organization. Let us take for example the case of a user provisioned with the "Accounts Payable Manager - Vision Operations" Data Role in Fusion Applications. This user will be able to access Invoices in Vision Operations but will not be able to see Invoices in Vision Germany. Figure 1. A User with a Data Role restricting them to Data from BU: Vision Operations With the role granted above, this is what the user will see when they attempt to select Business Units while searching for AP Invoices. Figure 2.The List Of Values of Business Units is limited to single one. This is the effect of the Data Role granted to that user as can be seen in Figure 1 In order to create a data role that secures by multiple BUs,  we need to start by creating a condition that groups those Business Units we want to include in that data role. This is accomplished by creating a new condition against the BU View .  That Condition will later be used to create a data policy for our newly created Role.  The BU View is a Database resource and  is accessed from APM as seen in the search below Figure 3.Viewing a Database Resource in APM The next step is create a new condition,  in which we define a sql predicate that includes 2 BUs ( The ids below refer to Vision Operations and Vision Germany).  At this point we have simply created a standalone condition.  We have not used this condition yet, and security is therefore not affected. Figure 4. Custom Role that inherits the Purchase Order Overview Duty We are now ready to create our Data Policy.  in APM, we search for our newly Created Role and Navigate to “Find Global Policies”.  we query the Role we want to secure and navigate to view its global policies. Figure 5. The Job Role we plan on securing We can see that the role was not defined with a Data Policy . So will create one that uses the condition we created earlier.   Figure 6. Creating a New Data Policy In the General Information tab, we have to specify the DB Resource that the Security Policy applies to:  In our case this is the BU View Figure 7. Data Policy Definition - Selection of the DB Resource we will secure by In the Rules Tab, we  make the rule applicable to multiple values of the DB Resource we selected in the previous tab.  This is where we associate the condition we created against the BU view to this data policy by entering the Condition name in the Condition field Figure 8. Data Policy Rule The last step of Defining the Data Policy, consists of  explicitly selecting  the Actions that are goverened by this Data Policy.  In this case for example we select the Actions displayed below in the right pane. Once the record is saved , we are ready to use our newly secured Data Role. Figure 9. Data Policy Actions We can now see a new Data Policy associated with our Role.  Figure 10. Role is now secured by a Data Policy We now Assign that new Role to the User.  Of course this does not have to be done in OIM and can be done using a Provisioning Rule in HCM. Figure 11. Role assigned to the User who previously was granted the Vision Ops secured role. Once that user accesses the Invoices Workarea this is what they see: In the image below the LOV of Business Unit returns the two values defined in our data policy namely: Vision Operations and Vision Germany Figure 12. The List Of Values of Business Units now includes the two we included in our data policy. This is the effect of the data role granted to that user as can be seen in Figure 11

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  • First Day of Data Integration Track at Oracle OpenWorld 2012

    - by Irem Radzik
    OpenWorld started full speed for us today with a great set of sessions in the Data Integration track. After the exciting keynote session on Oracle Database 12c in the morning; Brad Adelberg, VP of Development for Data Integration products, presented Oracle’s data integration product strategy. His session highlighted the new requirements for data integration to achieve pervasive and continuous access to trusted data. The new requirements and product focus areas presented in this session are: Provide access to any data at any source On premise or on cloud Enable zero downtime operations and maximum performance Leverage real-time data for accurate business insights And ensure high quality data is used across the enterprise During the session Brad walked over how Oracle’s data integration products, Oracle Data Integrator, Oracle GoldenGate, Oracle Enterprise Data Quality, and Oracle Data Service Integrator, deliver on these requirements and how recent product releases build on this strategy. Soon after Brad’s session we heard from a panel of Oracle GoldenGate customers, St. Jude Medical, Equifax, and Bank of America, how they achieved zero downtime operations using Oracle GoldenGate. The panel presented different use cases of GoldenGate, from Active-Active replication to offloading reporting. Especially St. Jude Medical’s implementation, which involves the alert management system for patients that use their pacemakers, reminded me in some cases downtime of mission-critical systems can be a matter of life or death. It is very comforting to hear that GoldenGate delivers highly-reliable continuous availability for life-saving medical systems. In the afternoon, Nick Wagner from the Product Management team and I followed the customer panel with the review of Oracle GoldenGate 11gR2’s New Features.  Many questions we received from audience were about GoldenGate’s new Integrated Capture for Oracle Database and the enhanced Conflict Management features, as well as how GoldenGate compares to Oracle Streams. In addition to giving details on GoldenGate’s unique capability to capture changed data with a direct integration to the Oracle DBMS engine, we reminded the audience that enhancements to Oracle GoldenGate will continue, while Streams will be primarily maintained. Last but not least, Tim Garrod and Ryan Fonnett from Raymond James presented a unified real-time data integration solution using Oracle Data Integrator and GoldenGate for their operational data store (ODS). The ODS supports application services across the enterprise and providing timely data is a critical requirement. In this solution, Oracle GoldenGate does the log-based change data capture for Oracle Data Integrator’s near real-time data integration between heterogeneous systems. As Raymond James’ ODS supports mission-critical services for their advisors, the project team had to set up this integration environment to be highly available. During the session, Ryan and Tim explained how they use ODI to enable automated process execution and “always-on” integration processes. Their presentation included 2 demonstrations that focused on CDC patterns deployed with ODI and the automated multi-instance execution and monitoring. We are very grateful to Tim and Ryan for their very-well prepared presentation at OpenWorld this year. Day 2 (Tuesday) will be also a busy day in our track. In addition to the Fusion Middleware Innovation Awards ceremony at 11:45am at Moscone West 3001, we have the following DI sessions Real-World Operational Reporting Customer Panel 11:45am Moscone West- 3005 Oracle Data Integrator Product Update and Future Strategy 1:15pm Moscone West- 3005 High-volume OLTP with Oracle GoldenGate: Best Practices from Comcast 1:15pm Moscone West- 3005 Everything You need to Know about Monitoring Oracle GoldenGate 5pm Moscone West-3005 If you are at OpenWorld please join us in these sessions. For a full review of data integration track at OpenWorld please see our Focus-On document.

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  • ADO.NET Data Services Entity Framework request error when property setter is internal

    - by Jim Straatman
    I receive an error message when exposing an ADO.NET Data Service using an Entity Framework data model that contains an entity (called "Case") with an internal setter on a property. If I modify the setter to be public (using the entity designer), the data services works fine. I don’t need the entity "Case" exposed in the data service, so I tried to limit which entities are exposed using SetEntitySetAccessRule. This didn’t work, and service end point fails with the same error. public static void InitializeService(IDataServiceConfiguration config) { config.SetEntitySetAccessRule("User", EntitySetRights.AllRead); } The error message is reported in a browser when the .svc endpoint is called. It is very generic, and reads “Request Error. The server encountered an error processing the request. See server logs for more details.” Unfortunately, there are no entries in the System and Application event logs. I found this stackoverflow question that shows how to configure tracing on the service. After doing so, the following NullReferenceExceptoin error was reported in the trace log. Does anyone know how to avoid this exception when including an entity with an internal setter? Blockquote 131076 3 0 2 MOTOJIM http://msdn.microsoft.com/en-US/library/System.ServiceModel.Diagnostics.TraceHandledException.aspx Handling an exception. 685a2910-19-128703978432492675 System.NullReferenceException, mscorlib, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 Object reference not set to an instance of an object. at System.Data.Services.Providers.ObjectContextServiceProvider.PopulateMemberMetadata(ResourceType resourceType, MetadataWorkspace workspace, IDictionary2 entitySets, IDictionary2 knownTypes) at System.Data.Services.Providers.ObjectContextServiceProvider.PopulateMetadata(IDictionary2 knownTypes, IDictionary2 entitySets) at System.Data.Services.Providers.BaseServiceProvider.PopulateMetadata() at System.Data.Services.DataService1.CreateProvider(Type dataServiceType, Object dataSourceInstance, DataServiceConfiguration&amp; configuration) at System.Data.Services.DataService1.EnsureProviderAndConfigForRequest() at System.Data.Services.DataService1.ProcessRequestForMessage(Stream messageBody) at SyncInvokeProcessRequestForMessage(Object , Object[] , Object[] ) at System.ServiceModel.Dispatcher.SyncMethodInvoker.Invoke(Object instance, Object[] inputs, Object[]&amp; outputs) at System.ServiceModel.Dispatcher.DispatchOperationRuntime.InvokeBegin(MessageRpc&amp; rpc) at System.ServiceModel.Dispatcher.ImmutableDispatchRuntime.ProcessMessage5(MessageRpc&amp; rpc) at System.ServiceModel.Dispatcher.ImmutableDispatchRuntime.ProcessMessage4(MessageRpc&amp; rpc) at System.ServiceModel.Dispatcher.ImmutableDispatchRuntime.ProcessMessage3(MessageRpc&amp; rpc) at System.ServiceModel.Dispatcher.ImmutableDispatchRuntime.ProcessMessage2(MessageRpc&amp; rpc) at System.ServiceModel.Dispatcher.ImmutableDispatchRuntime.ProcessMessage1(MessageRpc&amp; rpc) at System.ServiceModel.Dispatcher.MessageRpc.Process(Boolean isOperationContextSet) </StackTrace> <ExceptionString>System.NullReferenceException: Object reference not set to an instance of an object. at System.Data.Services.Providers.ObjectContextServiceProvider.PopulateMemberMetadata(ResourceType resourceType, MetadataWorkspace workspace, IDictionary2 entitySets, IDictionary2 knownTypes) at System.Data.Services.Providers.ObjectContextServiceProvider.PopulateMetadata(IDictionary2 knownTypes, IDictionary2 entitySets) at System.Data.Services.Providers.BaseServiceProvider.P

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  • Import exponetial fixed width format data into Excel

    - by Tom Daniel
    I've received a bunch of text data files consiting of Lots of records (30K/file) of 3 fields each of 5-place numbers in exponential format: s0.nnnnnEsee (where s is +/-, n is a digit and ee is the exponent (always 2 digit). When I open the file in Notepad, the format is perfectly uniform throughout each file, but when I import it to Excel using Data|Import|Fixed Width, many of the data values get messed up, no matter what format (text, exponential, various custom tries) I assign to the cells. Looking at the Notepad version, it appears that leading + signs were replaced with a space in the data file, but the sign of the exponential is always there. This means that some fields begin with a space, and this appears to confuse the Excel import routine. I get the same result in Excel 2003 and 2007. I'm sure there's a straightforward solution (hopefully without a messy VBA routine), but I can't figure out what to try next. :-) To clarify (hopefully), here are some input records and the corresponding text input to Excel: Notepad Excel -0.11311E+01 0.10431E-04 0.27018E-03 -0.11311E 1.0431E-05 2.7018E-04 0.19608E+00-0.81414E-02-0.89553E-02 0.19608E -8.1414E-03 8.9553E-03 etc. Whoopee! Solved my own problem - in the spirit of Jeopardy, now that I've begun the question, here's the answer - Use a different "File Origin" - several other than the default "Unicode UTF..." work fine! What a pain. Hope this helps somebody else avoid a few unpleasant hours! Aloha from Kona, Tom

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  • Recover data from quick formatted DVD-R

    - by Andrii Kalytiiuk
    I need to recover data from quick-formatted DVD-R. Please advise a free of charge option (cheap commercial tools will be ok either). Disk was partially recorded with Windows built in disk recorder and recording most likely was not complete. Afterwards I have inserted partially recorded DVD again and on Windows recorder's message box 'How to use this disk?' selected - 'use for CD/DVD player' and data was completely lost - as new recording session was started. Files of photos were recorded on disk. What I have tried so far: DiskInternals CD-DVD recovery - sees 5 jpg files but can't show preview. Tool is commercial - trial version does not allow to recover files. CDCheck - doesn't see any files and reports errors at attempt to scand DVD CD Recovery Toolbox Free - does not even recognize DVD drive ISO Buster - recognizes two files - one MP3 file for 99% of recorded size and one ARC file for about 100 KB MiniTool Power Data Recovery - Free Edition - does not see any files on DVD Stellar Phoenix CD DVD Data Recovery - does not see any files BinaryBiz Virtual Lab - sees DVD disk but needs license to browse content Please advise how is it possible to recover files from DVD.

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  • Oracle SQL Developer Data Modeler: What Tables Aren’t In At Least One SubView?

    - by thatjeffsmith
    Organizing your data model makes the information easier to consume. One of the organizational tools provided by Oracle SQL Developer Data Modeler is the ‘SubView.’ In a nutshell, a SubView is a subset of your model. The Challenge: I’ve just created a model which represents my entire ____________ application. We’ll call it ‘residential lending.’ Instead of having all 100+ tables in a single model diagram, I want to break out the tables by module, e.g. appraisals, credit reports, work histories, customers, etc. I’ve spent several hours breaking out the tables to one or more SubViews, but I think i may have missed a few. Is there an easy way to see what tables aren’t in at least ONE subview? The Answer Yes, mostly. The mostly comes about from the way I’m going to accomplish this task. It involves querying the SQL Developer Data Modeler Reporting Schema. So if you don’t have the Reporting Schema setup, you’ll need to do so. Got it? Good, let’s proceed. Before you start querying your Reporting Schema, you might need a data model for the actual reporting schema…meta-meta data! You could reverse engineer the data modeler reporting schema to a new data model, or you could just reference the PDFs in \datamodeler\reports\Reporting Schema diagrams directory. Here’s a hint, it’s THIS one The Query Well, it’s actually going to be at least 2 queries. We need to get a list of distinct designs stored in your repository. For giggles, I’m going to get a listing including each version of the model. So I can query based on design and version, or in this case, timestamp of when it was added to the repository. We’ll get that from the DMRS_DESIGNS table: SELECT DISTINCT design_name, design_ovid, date_published FROM DMRS_designs Then I’m going to feed the design_ovid, down to a subquery for my child report. select name, count(distinct diagram_id) from DMRS_DIAGRAM_ELEMENTS where design_ovid = :dESIGN_OVID and type = 'Table' group by name having count(distinct diagram_id) < 2 order by count(distinct diagram_id) desc Each diagram element has an entry in this table, so I need to filter on type=’Table.’ Each design has AT LEAST one diagram, the master diagram. So any relational table in this table, only having one listing means it’s not in any SubViews. If you have overloaded object names, which is VERY possible, you’ll want to do the report off of ‘OBJECT_ID’, but then you’ll need to correlate that to the NAME, as I doubt you’re so intimate with your designs that you recognize the GUIDs So I’m going to cheat and just stick with names, but I think you get the gist. My Model Of my almost 90 tables, how many of those have I not added to at least one SubView? Now let’s run my report! Voila! My ‘BEER2′ table isn’t in any SubView! It says ’1′ because the main model diagram counts as a view. So if the count came back as ’2′, that would mean the table was in the main model diagram and in 1 SubView diagram. And I know what you’re thinking, what kind of residential lending program would have a table called ‘BEER2?’ Let’s just say, that my business model has some kinks to work out!

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  • Refreshing imported MySQL data with MySQL for Excel

    - by Javier Rivera
    Welcome to another blog post from the MySQL for Excel Team. Today we're going to talk about a new feature included since MySQL for Excel 1.3.0, you can install the latest GA or maintenance version using the MySQL Installer or optionally you can download directly any GA or non-GA version from the MySQL Developer Zone.As some users suggested in our forums we should be maintaining the link between tables and Excel not only when editing data through the Edit MySQL Data option, but also when importing data via Import MySQL Data. Before 1.3.0 this process only provided you with an offline copy of the Table's data into Excel and you had no way to refresh that information from the DB later on. Now, with this new feature we'll show you how easy is to work with the latest available information at all times. This feature is transparent to you (it doesn't require additional steps to work as long as the users had the Create an Excel Table for the imported MySQL table data option enabled. To ensure you have this option checked, click over Advanced Options... after the Import Data dialog is displayed). The current blog post assumes you already know how to import data into excel, you could always take a look at our previous post How To - Guide to Importing Data from a MySQL Database to Excel using MySQL for Excel if you need further reference on that topic. After importing Data from a MySQL Table into Excel, you can refresh the data in 3 ways.1. Simply right click over the range of the imported data, to show the pop-up menu: Click over the Refresh button to obtain the latest copy of the data in the table. 2. Click the Refresh button on the Data ribbon: 3. Click the Refresh All button in the Data ribbon (beware this will refresh all Excel tables in the Workbook): Please take a note of a couple of details here, the first one is about the size of the table. If by the time you refresh the table new columns had been added to it, and you originally have imported all columns, the table will grow to the right. The same applies to rows, if the table has new rows and you did not limit the results , the table will grow to to the bottom of the sheet in Excel. The second detail you should take into account is this operation will overwrite any changes done to the cells after the table was originally imported or previously refreshed: Now with this new feature, imported data remains linked to the data source and is available to be updated at all times. It empowers the user to always be able to work with the latest version of the imported MySQL data. We hope you like this this new feature and give it a try! Remember that your feedback is very important for us, so drop us a message with your comments, suggestions for this or other features and follow us at our social media channels: MySQL on Windows (this) Blog: https://blogs.oracle.com/MySqlOnWindows/ MySQL for Excel forum: http://forums.mysql.com/list.php?172 Facebook: http://www.facebook.com/mysql YouTube channel: https://www.youtube.com/user/MySQLChannel Thanks!

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  • Extract wrong data from a frame in C?

    - by ipkiss
    I am writing a program that reads the data from the serial port on Linux. The data are sent by another device with the following frame format: |start | Command | Data | CRC | End | |0x02 | 0x41 | (0-127 octets) | | 0x03| ---------------------------------------------------- The Data field contains 127 octets as shown and octet 1,2 contains one type of data; octet 3,4 contains another data. I need to get these data. Because in C, one byte can only holds one character and in the start field of the frame, it is 0x02 which means STX which is 3 characters. So, in order to test my program, On the sender side, I construct an array as the frame formatted above like: char frame[254]; frame[0] = 0x02; // starting field frame[1] = 0x41; // command field which is character 'A' ..so on.. And, then On the receiver side, I take out the fields like: char result[254]; // read data read(result); printf("command = %c", result[1]); // get the command field of the frame // get other field's values the command field value (result[1]) is not character 'A'. I think, this because the first field value of the frame is 0x02 (STX) occupying 3 first places in the array frame and leading to the wrong results on the receiver side. How can I correct the issue or am I doing something wrong at the sender side? Thanks all. related questions: http://stackoverflow.com/questions/2500567/parse-and-read-data-frame-in-c http://stackoverflow.com/questions/2531779/clear-data-at-serial-port-in-linux-in-c

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  • Fraud Detection with the SQL Server Suite Part 1

    - by Dejan Sarka
    While working on different fraud detection projects, I developed my own approach to the solution for this problem. In my PASS Summit 2013 session I am introducing this approach. I also wrote a whitepaper on the same topic, which was generously reviewed by my friend Matija Lah. In order to spread this knowledge faster, I am starting a series of blog posts which will at the end make the whole whitepaper. Abstract With the massive usage of credit cards and web applications for banking and payment processing, the number of fraudulent transactions is growing rapidly and on a global scale. Several fraud detection algorithms are available within a variety of different products. In this paper, we focus on using the Microsoft SQL Server suite for this purpose. In addition, we will explain our original approach to solving the problem by introducing a continuous learning procedure. Our preferred type of service is mentoring; it allows us to perform the work and consulting together with transferring the knowledge onto the customer, thus making it possible for a customer to continue to learn independently. This paper is based on practical experience with different projects covering online banking and credit card usage. Introduction A fraud is a criminal or deceptive activity with the intention of achieving financial or some other gain. Fraud can appear in multiple business areas. You can find a detailed overview of the business domains where fraud can take place in Sahin Y., & Duman E. (2011), Detecting Credit Card Fraud by Decision Trees and Support Vector Machines, Proceedings of the International MultiConference of Engineers and Computer Scientists 2011 Vol 1. Hong Kong: IMECS. Dealing with frauds includes fraud prevention and fraud detection. Fraud prevention is a proactive mechanism, which tries to disable frauds by using previous knowledge. Fraud detection is a reactive mechanism with the goal of detecting suspicious behavior when a fraudster surpasses the fraud prevention mechanism. A fraud detection mechanism checks every transaction and assigns a weight in terms of probability between 0 and 1 that represents a score for evaluating whether a transaction is fraudulent or not. A fraud detection mechanism cannot detect frauds with a probability of 100%; therefore, manual transaction checking must also be available. With fraud detection, this manual part can focus on the most suspicious transactions. This way, an unchanged number of supervisors can detect significantly more frauds than could be achieved with traditional methods of selecting which transactions to check, for example with random sampling. There are two principal data mining techniques available both in general data mining as well as in specific fraud detection techniques: supervised or directed and unsupervised or undirected. Supervised techniques or data mining models use previous knowledge. Typically, existing transactions are marked with a flag denoting whether a particular transaction is fraudulent or not. Customers at some point in time do report frauds, and the transactional system should be capable of accepting such a flag. Supervised data mining algorithms try to explain the value of this flag by using different input variables. When the patterns and rules that lead to frauds are learned through the model training process, they can be used for prediction of the fraud flag on new incoming transactions. Unsupervised techniques analyze data without prior knowledge, without the fraud flag; they try to find transactions which do not resemble other transactions, i.e. outliers. In both cases, there should be more frauds in the data set selected for checking by using the data mining knowledge compared to selecting the data set with simpler methods; this is known as the lift of a model. Typically, we compare the lift with random sampling. The supervised methods typically give a much better lift than the unsupervised ones. However, we must use the unsupervised ones when we do not have any previous knowledge. Furthermore, unsupervised methods are useful for controlling whether the supervised models are still efficient. Accuracy of the predictions drops over time. Patterns of credit card usage, for example, change over time. In addition, fraudsters continuously learn as well. Therefore, it is important to check the efficiency of the predictive models with the undirected ones. When the difference between the lift of the supervised models and the lift of the unsupervised models drops, it is time to refine the supervised models. However, the unsupervised models can become obsolete as well. It is also important to measure the overall efficiency of both, supervised and unsupervised models, over time. We can compare the number of predicted frauds with the total number of frauds that include predicted and reported occurrences. For measuring behavior across time, specific analytical databases called data warehouses (DW) and on-line analytical processing (OLAP) systems can be employed. By controlling the supervised models with unsupervised ones and by using an OLAP system or DW reports to control both, a continuous learning infrastructure can be established. There are many difficulties in developing a fraud detection system. As has already been mentioned, fraudsters continuously learn, and the patterns change. The exchange of experiences and ideas can be very limited due to privacy concerns. In addition, both data sets and results might be censored, as the companies generally do not want to publically expose actual fraudulent behaviors. Therefore it can be quite difficult if not impossible to cross-evaluate the models using data from different companies and different business areas. This fact stresses the importance of continuous learning even more. Finally, the number of frauds in the total number of transactions is small, typically much less than 1% of transactions is fraudulent. Some predictive data mining algorithms do not give good results when the target state is represented with a very low frequency. Data preparation techniques like oversampling and undersampling can help overcome the shortcomings of many algorithms. SQL Server suite includes all of the software required to create, deploy any maintain a fraud detection infrastructure. The Database Engine is the relational database management system (RDBMS), which supports all activity needed for data preparation and for data warehouses. SQL Server Analysis Services (SSAS) supports OLAP and data mining (in version 2012, you need to install SSAS in multidimensional and data mining mode; this was the only mode in previous versions of SSAS, while SSAS 2012 also supports the tabular mode, which does not include data mining). Additional products from the suite can be useful as well. SQL Server Integration Services (SSIS) is a tool for developing extract transform–load (ETL) applications. SSIS is typically used for loading a DW, and in addition, it can use SSAS data mining models for building intelligent data flows. SQL Server Reporting Services (SSRS) is useful for presenting the results in a variety of reports. Data Quality Services (DQS) mitigate the occasional data cleansing process by maintaining a knowledge base. Master Data Services is an application that helps companies maintaining a central, authoritative source of their master data, i.e. the most important data to any organization. For an overview of the SQL Server business intelligence (BI) part of the suite that includes Database Engine, SSAS and SSRS, please refer to Veerman E., Lachev T., & Sarka D. (2009). MCTS Self-Paced Training Kit (Exam 70-448): Microsoft® SQL Server® 2008 Business Intelligence Development and Maintenance. MS Press. For an overview of the enterprise information management (EIM) part that includes SSIS, DQS and MDS, please refer to Sarka D., Lah M., & Jerkic G. (2012). Training Kit (Exam 70-463): Implementing a Data Warehouse with Microsoft® SQL Server® 2012. O'Reilly. For details about SSAS data mining, please refer to MacLennan J., Tang Z., & Crivat B. (2009). Data Mining with Microsoft SQL Server 2008. Wiley. SQL Server Data Mining Add-ins for Office, a free download for Office versions 2007, 2010 and 2013, bring the power of data mining to Excel, enabling advanced analytics in Excel. Together with PowerPivot for Excel, which is also freely downloadable and can be used in Excel 2010, is already included in Excel 2013. It brings OLAP functionalities directly into Excel, making it possible for an advanced analyst to build a complete learning infrastructure using a familiar tool. This way, many more people, including employees in subsidiaries, can contribute to the learning process by examining local transactions and quickly identifying new patterns.

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  • Oracle Data Integrator at Oracle OpenWorld 2012: Demonstrations

    - by Irem Radzik
    By Mike Eisterer Oracle OpenWorld is just a few days away and  we look forward to showing Oracle Data Integrator' comprehensive data integration platform, which delivers critical data integration requirements: from high-volume, high-performance batch loads, to event-driven, trickle-feed integration processes, to SOA-enabled data services.  Several Oracle Data Integrator demonstrations will be available October 1st through the3rd : Oracle Data Integrator and Oracle GoldenGate for Oracle Applications, in Moscone South, Right - S-240 Oracle Data Integrator and Service Integration, in Moscone South, Right - S-235 Oracle Data Integrator for Big Data, in Moscone South, Right - S-236 Oracle Data Integrator for Enterprise Data Warehousing, in Moscone South, Right - S-238 Additional information about OOW 2012 may be found for the following demonstrations. If you are not able to attend OpenWorld, please check out our latest resources for Data Integration.  

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  • Which algorithms/data structures should I "recognize" and know by name?

    - by Earlz
    I'd like to consider myself a fairly experienced programmer. I've been programming for over 5 years now. My weak point though is terminology. I'm self-taught, so while I know how to program, I don't know some of the more formal aspects of computer science. So, what are practical algorithms/data structures that I could recognize and know by name? Note, I'm not asking for a book recommendation about implementing algorithms. I don't care about implementing them, I just want to be able to recognize when an algorithm/data structure would be a good solution to a problem. I'm asking more for a list of algorithms/data structures that I should "recognize". For instance, I know the solution to a problem like this: You manage a set of lockers labeled 0-999. People come to you to rent the locker and then come back to return the locker key. How would you build a piece of software to manage knowing which lockers are free and which are in used? The solution, would be a queue or stack. What I'm looking for are things like "in what situation should a B-Tree be used -- What search algorithm should be used here" etc. And maybe a quick introduction of how the more complex(but commonly used) data structures/algorithms work. I tried looking at Wikipedia's list of data structures and algorithms but I think that's a bit overkill. So I'm looking more for what are the essential things I should recognize?

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  • Understanding Data Science: Recent Studies

    - by Joe Lamantia
    If you need such a deeper understanding of data science than Drew Conway's popular venn diagram model, or Josh Wills' tongue in cheek characterization, "Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician." two relatively recent studies are worth reading.   'Analyzing the Analyzers,' an O'Reilly e-book by Harlan Harris, Sean Patrick Murphy, and Marck Vaisman, suggests four distinct types of data scientists -- effectively personas, in a design sense -- based on analysis of self-identified skills among practitioners.  The scenario format dramatizes the different personas, making what could be a dry statistical readout of survey data more engaging.  The survey-only nature of the data,  the restriction of scope to just skills, and the suggested models of skill-profiles makes this feel like the sort of exercise that data scientists undertake as an every day task; collecting data, analyzing it using a mix of statistical techniques, and sharing the model that emerges from the data mining exercise.  That's not an indictment, simply an observation about the consistent feel of the effort as a product of data scientists, about data science.  And the paper 'Enterprise Data Analysis and Visualization: An Interview Study' by researchers Sean Kandel, Andreas Paepcke, Joseph Hellerstein, and Jeffery Heer considers data science within the larger context of industrial data analysis, examining analytical workflows, skills, and the challenges common to enterprise analysis efforts, and identifying three archetypes of data scientist.  As an interview-based study, the data the researchers collected is richer, and there's correspondingly greater depth in the synthesis.  The scope of the study included a broader set of roles than data scientist (enterprise analysts) and involved questions of workflow and organizational context for analytical efforts in general.  I'd suggest this is useful as a primer on analytical work and workers in enterprise settings for those who need a baseline understanding; it also offers some genuinely interesting nuggets for those already familiar with discovery work. We've undertaken a considerable amount of research into discovery, analytical work/ers, and data science over the past three years -- part of our programmatic approach to laying a foundation for product strategy and highlighting innovation opportunities -- and both studies complement and confirm much of the direct research into data science that we conducted. There were a few important differences in our findings, which I'll share and discuss in upcoming posts.

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  • Branching strategy for frequent releases

    - by Technext
    We have very frequent releases and we use Git for version control. When i am mentioning about frequency, please assume it to include bug-fixes and feature release too. All releases are eventually merged into ‘mainline’. When a release is deployed on production and if a bug is identified, people start fixing the bug on the same branch from which the latest release was deployed on production. They do not create a new bug-fix branch for the same. I feel that’s not the right way to go for. There are several components and each component has a different owner, and thus, different perspective. Though I have not initiated talks with them, I am sure there will be a lot of resistance. Main issue that they might cite would be, “There’s a lot of work involved in creating and tracking branches especially when there are so frequent deployments on production. This will consume a lot of dev effort.” Do you think that fixing bug on the same branch from which release was done, a good idea? If yes, how do you manage it? Using tags? I know that best practices may not always be applicable due to several factors but still I would like to know what might be a good approach for branching in a scenario where releases/bug-fixes happen almost on a daily basis.

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  • IOMEGA 500GB hard disk data reccovery

    - by Vineeth
    Last year by November I bought an IOMEGA 500GB Prestige hard disk. Yesterday, unfortunately the hard disk fell down from my table. After that incident, when I connect my disk, Windows asks me to format the disk to use, but I didn't format it yet. Actually, on that hard disk I have about 320GB of data. I tried all my possible ways to access my disk. I tried using DOS. It shows "data error (Cyclic redundancy check)". I have a 3 year warranty. Will I be covered under warranty if I report this issue to IOMEGA? Can I get my data back?

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  • how to find a good data center?

    - by drewda
    At my start-up, we're getting to the point where we should be hosting our servers at a data center. I'd appreciate any tips and tricks y'all can offer on finding a reputable place to colocate our racks. Are there any Web sites with customer reviews of data centers or should I just be asking around at techie events? Are unlimited bandwidth plans a gimmick or becoming the norm? Is it worth establishing a redundant set of machines at a second data center from Day One? Or just do offsite back-ups? Thanks for your suggestions.

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  • Appending column to a data frame - R

    - by darkie15
    Is it possible to append a column to data frame in the following scenario? dfWithData <- data.frame(start=c(1,2,3), end=c(11,22,33)) dfBlank <- data.frame() ..how to append column start from dfWithData to dfBlank? It looks like the data should be added when data frame is being initialized. I can do this: dfBlank <- data.frame(dfWithData[1]) but I am more interested if it is possible to append columns to an empty (but inti)

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  • Protecting Consolidated Data on Engineered Systems

    - by Steve Enevold
    In this time of reduced budgets and cost cutting measures in Federal, State and Local governments, the requirement to provide services continues to grow. Many agencies are looking at consolidating their infrastructure to reduce cost and meet budget goals. Oracle's engineered systems are ideal platforms for accomplishing these goals. These systems provide unparalleled performance that is ideal for running applications and databases that traditionally run on separate dedicated environments. However, putting multiple critical applications and databases in a single architecture makes security more critical. You are putting a concentrated set of sensitive data on a single system, making it a more tempting target.  The environments were previously separated by iron so now you need to provide assurance that one group, department, or application's information is not visible to other personnel or applications resident in the Exadata system. Administration of the environments requires formal separation of duties so an administrator of one application environment cannot view or negatively impact others. Also, these systems need to be in protected environments just like other critical production servers. They should be in a data center protected by physical controls, network firewalls, intrusion detection and prevention, etc Exadata also provides unique security benefits, including a reducing attack surface by minimizing packages and services to only those required. In addition to reducing the possible system areas someone may attempt to infiltrate, Exadata has the following features: 1.    Infiniband, which functions as a secure private backplane 2.    IPTables  to perform stateful packet inspection for all nodes               Cellwall implements firewall services on each cell using IPTables 3.    Hardware accelerated encryption for data at rest on storage cells Oracle is uniquely positioned to provide the security necessary for implementing Exadata because security has been a core focus since the company's beginning. In addition to the security capabilities inherent in Exadata, Oracle security products are all certified to run in an Exadata environment. Database Vault Oracle Database Vault helps organizations increase the security of existing applications and address regulatory mandates that call for separation-of-duties, least privilege and other preventive controls to ensure data integrity and data privacy. Oracle Database Vault proactively protects application data stored in the Oracle database from being accessed by privileged database users. A unique feature of Database Vault is the ability to segregate administrative tasks including when a command can be executed, or that the DBA can manage the health of the database and objects, but may not see the data Advanced Security  helps organizations comply with privacy and regulatory mandates by transparently encrypting all application data or specific sensitive columns, such as credit cards, social security numbers, or personally identifiable information (PII). By encrypting data at rest and whenever it leaves the database over the network or via backups, Oracle Advanced Security provides the most cost-effective solution for comprehensive data protection. Label Security  is a powerful and easy-to-use tool for classifying data and mediating access to data based on its classification. Designed to meet public-sector requirements for multi-level security and mandatory access control, Oracle Label Security provides a flexible framework that both government and commercial entities worldwide can use to manage access to data on a "need to know" basis in order to protect data privacy and achieve regulatory compliance  Data Masking reduces the threat of someone in the development org taking data that has been copied from production to the development environment for testing, upgrades, etc by irreversibly replacing the original sensitive data with fictitious data so that production data can be shared safely with IT developers or offshore business partners  Audit Vault and Database Firewall Oracle Audit Vault and Database Firewall serves as a critical detective and preventive control across multiple operating systems and database platforms to protect against the abuse of legitimate access to databases responsible for almost all data breaches and cyber attacks.  Consolidation, cost-savings, and performance can now be achieved without sacrificing security. The combination of built in protection and Oracle’s industry-leading data protection solutions make Exadata an ideal platform for Federal, State, and local governments and agencies.

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  • Finish feature reverted commits from develop

    - by marco-fiset
    I am using git as a version control system, and using git-flow as the branching model. I started a feature branch some weeks ago in order to maintain the system in a clean state while developping that feature. The main development continued on the develop branch, and changes from develop were merged periodically into the feature, to keep it up to date as much as possible. However came the time where the feature was finished, and I used git-flow's finish feature to merge the feature back into develop. The merge was successfully done, but then I found out that some of the commits I made in develop were reverted by the merge commit! Nowhere in develop or in the feature branch were these changes reverted, I can't see any commit that overwrote them. I just can't find anything. The only theory I have for the moment is that git is failing on me, but that would be extremely unlikely. Maybe I did some kind of wrong manipulation that made this situation come true? I can trace back in the history when the commit was made. I can see that the changes from that commit were reverted by the merge commit. Nowhere in the branch I see a commit that reverts those changes. Yet they were reverted. How is this even possible?

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  • using core data with web services

    - by Jayshree
    Hi. i am a noob in xcode. I am developing an iphone app where i need to send and receive data from a web service. And i need to store them temporarily in my app. i dont want to use sqlite. so i was wondering if i should use core data for this purpose. I read some articles but i still dont have a clear picture of how to do it, coz i have used core data only with sqlite. I want to do the following things : Will receive table data from a web service. Have to perform certain calculations on those fields. Will send the data back in xml format to the server. How do i convert the xml data into int, date or any other data type? and how do i store it in managed data objects? Can anyone please help me with this??? thnx for your time.

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  • Why CFOs Should Care About Big Data

    - by jmorourke
    The topic of “big data” clearly has reached a tipping point in 2012.  With plenty of coverage over the past few years in the IT press, we are now starting to see the topic of “big data” covered in mainstream business press, including a cover story in the October 2012 issue of the Harvard Business Review.  To help customers understand the challenges of managing “big data” as well as the opportunities that can be created by leveraging “big data”, Oracle has recently run and published the results of a customer survey, as well as white papers and articles on this topic.  Most recently, we commissioned a white paper titled “Mastering Big Data: CFO Strategies to Transform Insight into Opportunity”. The premise here is that “big data” is not just a topic that CIOs should pay attention to, but one that CFOs should understand and take advantage of as well.  Clearly, whoever masters the art and science of big data will be positioned for competitive advantage in their industries or markets.  That’s why smart CFOs are taking control of big data and business analytics projects, not just to uncover new ways to drive growth in a slowing global economy, but also to be a catalyst for change in the enterprise.  With an increasing number of CFOs now responsible for overseeing IT investments and providing strategic insight to the board, CFOs will be increasingly called upon to take a leadership role in assessing the value of “big data” initiatives, building on their traditional skills in reporting and helping managers analyze data to support decision making. Here’s a link to the white paper referenced above, which is posted on the Oracle C-Central/CFO web site, as well as some other resources that can help CFOs master the topic of “big data”: White Paper “Mastering Big Data:  CFO Strategies to Transform Insight into Opportunity CFO Market Watch article:  “Does Big Data Affect the CFO?” Oracle Survey Report:  “From Overload to Impact – An Industry Scorecard on Big Data Industry Challenges” Upcoming Big Data Webcast with Andrew McAfee Here’s a general link to Oracle C-Central/CFO in case you want to start there: www.oracle.com/c-central/cfo Feel free to contact me if you have any questions or need additional information:  [email protected]

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  • Presenting Loading Data Warehouse Partitions with SSIS 2012 at SQL Saturday DC!

    - by andyleonard
    Join Darryll Petrancuri and me as we present Loading Data Warehouse Partitions with SSIS 2012 Saturday 8 Dec 2012 at SQL Saturday 173 in DC ! SQL Server 2012 table partitions offer powerful Big Data solutions to the Data Warehouse ETL Developer. In this presentation, Darryll Petrancuri and Andy Leonard demonstrate one approach to loading partitioned tables and managing the partitions using SSIS 2012, and reporting partition metrics using SSRS 2012. Objectives A practical solution for loading Big...(read more)

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  • data recovery from unallocated harddisk partition

    - by user42151
    Hi I accidentally deleted a partition which mainly served as space I put my data, labeled D: drive. The partition wasn't subsequently formatted though, following the delete incident. Obviously the D: drive doesn't show up as it usually does when I run Windows 7. In the "Computer Management", on clicking the Disk Management I clearly see the space is now labled as unallocated. question: How do I go about recovering my data. Perhaps what the effective data recovery software I can use to resolve this issue. Thanks

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  • data recovery from unallocated harddisk partition

    - by user36007
    Hi, I accidentally deleted a partition which mainly served as space I put my data, labeled D: drive. The partition wasn't subsequently formatted though, following the delete incident. Obviously the D: drive doesn't show up as it usually does when I run Windows 7. In the "Computer Management", on clicking the Disk Management I clearly see the space is now labled as unallocated. question: How do I go about recovering my data. Perhaps what the effective data recovery software I can use to resolve this issue. Thanks

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  • data recovery from unallocated harddisk partition

    - by user36007
    Hi, I accidentally deleted a partition which mainly served as space I put my data, labeled D: drive. The partition wasn't subsequently formatted though, following the delete incident. Obviously the D: drive doesn't show up as it usually does when I run Windows 7. In the "Computer Management", on clicking the Disk Management I clearly see the space is now labled as unallocated. question: How do I go about recovering my data. Perhaps what the effective data recovery software I can use to resolve this issue. Thanks

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