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• Access-based Enumeration (December 04, 2009)

  - by user12612012

  Access-based Enumeration (ABE) is another recent addition to the Solaris CIFS Service - delivered into snv_124.  Designed to be compatible with Windows ABE, which was introduced in Windows Server 2003 SP1, this feature filters directory content based on the user browsing the directory.  Each user can only see the files and directories to which they have access.  This can be useful to implement an out-of-sight, out-of-mind policy or simply to reduce the number of files presented to each user - to make it easier to find files in directories containing a large number of files. ABE is managed on a per share basis by a new boolean share property called, as you might imagine, abe, which is described insharemgr(1M).  When set to true, ABE filtering is enabled on the share and directory entries to which the user has no access will be omitted from directory listings returned to the client.  When set to false or not defined, ABE filtering will not be performed on the share.  The abe property is not defined by default.Administration is straightforward, for example: # zfs sharesmb=abe=true,name=jane tank/home/jane# sharemgr show -vp    zfs       zfs/tank/home/jane nfs=() smb=()          jane=/export/home/jane     smb=(abe="true") ABE is also supported via sharemgr(1M) and on smbautohome(4) shares. Note that even though a file is visible in a share, with ABE enabled, it doesn't automatically mean that the user will always be able to open the file.  If a user has read attribute access to a file ABE will show the it but access will be denied if this user tries to open the file for reading or writing. We considered supporting ABE on NFS shares, as suggested by the name of PSARC/2009/375, but we ran into problems due to NFS client readdir caching.  NFS clients maintain a common directory entry cache for all users, which not only defeats the intent of ABE but can lead to very confusing results.  If multiple users are looking at the content of a directory with ABE enabled, the entries that get cached will depend on who looks at the directory first.  Subsequent users may see files that ABE on the server would have filtered out or files may be missing because they were filtered out for the original user. Although this issue can be resolved by disabling the NFS client readdir cache, this was deemed to be an unsuitable solution because it would create a dependency between a server share property and the configuration on all NFS clients, and there was the potential for differences in behavior across the various NFS clients.  It just seemed to add unnecessary administration complexity so we pulled it out. References for more information PSARC/2009/246 ZFS support for Access Based Enumeration PSARC/2009/375 ABE share property for NFS and SMB 6802734 Support for Access Based Enumeration 6802736 SMB share support for Access Based Enumeration Windows Access-based Enumeration

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• Creating Custom validation rule and register it

  - by FormsEleven

  What is Validation Rule? A validation rule is a piece of code that performs some check ensuring that data meets given constraints.In an enterprise application development environment, often it might require developers to have validation be performed based on some logic at several places across projects. Instead of redundant validation creation, a custom validation rule provides a library with a validation rules that can be registered and used across applications.A custom Validation is encapsulated in a reusable component so that you do not have to write it every time when you need to do input validation. Here is how we can easily implement a custom validation that checks for name of an employee to be "KING" For creating a custom Validation , 1.         Create Generic Application Workspace "CustomValidator" with the project "Model" 2.         Create an BC4J based on emp table. 3.         Create a custom validation rule.In EmpNamerule class, update the validateValue(..) method as follows:  public boolean validateValue(Object value) { EntityImpl emp = (EntityImpl)value; if(emp.getAttribute("Ename").toString().equals("KING")){ return false; } return true; } Create ADF Library: Next step would be to create ADF library. Create ADF library with name lets say testADFLibrary1.jarRegister ADF Library Next step is to register the ADF library , so that its available across the applications. Invoke the menu "Tools -> Preferences"Select the option "Business Components -> Registered Rules" from left paneClick on button "Pick Library". The dialog "Select Library" comes up with  the user library addedAdd new library' that points to the above jarCheck the checkbox "Register" and set the name for the rule Sample UsageHere is how we can easily implement a validation rule that restrict the name of the employee not to be "KING".Create new Application with BC4J based on EMP table.Create new validation under Business rule tab for Ename & select the above custom validation rule.Run the AppModule tester.

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• Analytics in an Omni-Channel World

  - by David Dorf

  Retail has been around ever since mankind started bartering.  The earliest transactions were very specific to the individuals buying and selling, then someone had the bright idea to open a store.  Those transactions were a little more generic, but the store owner still knew his customers and what they wanted.  As the chains rolled out, customer intimacy was sacrificed for scale, and retailers began to rely on segments and clusters.  But thanks to the widespread availability of data and the technology to convert said data into information, retailers are getting back to details. The retail industry is following a maturity model for analytics that is has progressed through five stages, each delivering more value than the previous. Store Analytics Brick-and-mortar retailers (and pure-play catalogers as well) that collect anonymous basket-level data are able to get some sense of demand to help with allocation decisions.  Promotions and foot-traffic can be measured to understand marketing effectiveness and perhaps focus groups can help test ideas.  But decisions are influenced by the majority, using faceless customer segments and aggregated industry data points.  Loyalty programs help a little, but in many cases the cost outweighs the benefits. Web Analytics The Web made it much easier to collect data on specific, yet still anonymous consumers using cookies to track visits. Clickstreams and product searches are analyzed to understand the purchase journey, gauge demand, and better understand up-selling opportunities.  Personalization begins to allow retailers target market consumers with recommendations. Cross-Channel Analytics This phase is a minor one, but where most retailers probably sit today.  They are able to use information from one channel to bolster activities in another. However, there are technical challenges combining data silos so its not an easy task.  But for those retailers that are able to perform analytics on both sources of data, the pay-off is pretty nice.  Revenue per customer begins to go up as customers have a better brand experience. Mobile & Social Analytics Big data technologies are enabling a 360-degree view of the customer by incorporating psychographic data from social sites alongside traditional demographic data.  Retailers can track individual preferences, opinions, hobbies, etc. in order to understand a consumer's motivations.  Using mobile devices, consumers can interact with brands anywhere, anytime, accessing deep product information and reviews.  Mobile, combined with a loyalty program, presents an opportunity to put shopping into geographic context, understanding paths to the store, patterns within the store, and be an always-on advertising conduit. Omni-Channel Analytics All this data along with the proper technology represents a new paradigm in which the clock is turned back and retail becomes very personal once again.  Rich, individualized data better illuminates demand, allows for highly localized assortments, and helps tailor up-selling.  Interactions with all channels help build an accurate profile of each consumer, and allows retailers to tailor the retail experience to meet the heightened expectations of today's sophisticated shopper.  And of course this culminates in greater customer satisfaction and business profitability.

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• Workshop in Denver canceled - thanks to hurricane Isaac

  - by Mike Dietrich

  Yesterday Roy did start his journey on time to travel to Denver, CO for today's Upgrade and Migration Workshop.  But unfortunately due to the remnants of  hurricane Issac moving up the East Coast and scrambling up flight schedules Roy's flight from NYC to Denver got canceled after a 3 hour delay leaving Manchester, NH, and there was no option to arrive in Denver this morning on time. So we apologize for canceling that workshop. The local marketing department will contact you regarding an alternative date. Sorry for any inconvenience!

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• Short Season, Long Models - Dealing with Seasonality

  - by Michel Adar

  Accounting for seasonality presents a challenge for the accurate prediction of events. Examples of seasonality include: ·         Boxed cosmetics sets are more popular during Christmas. They sell at other times of the year, but they rise higher than other products during the holiday season. ·         Interest in a promotion rises around the time advertising on TV airs ·         Interest in the Sports section of a newspaper rises when there is a big football match There are several ways of dealing with seasonality in predictions. Time Windows If the length of the model time windows is short enough relative to the seasonality effect, then the models will see only seasonal data, and therefore will be accurate in their predictions. For example, a model with a weekly time window may be quick enough to adapt during the holiday season. In order for time windows to be useful in dealing with seasonality it is necessary that: The time window is significantly shorter than the season changes There is enough volume of data in the short time windows to produce an accurate model An additional issue to consider is that sometimes the season may have an abrupt end, for example the day after Christmas. Input Data If available, it is possible to include the seasonality effect in the input data for the model. For example the customer record may include a list of all the promotions advertised in the area of residence. A model with these inputs will have to learn the effect of the input. It is possible to learn it specific to the promotion – and by the way learn about inter-promotion cross feeding – by leaving the list of ads as it is; or it is possible to learn the general effect by having a flag that indicates if the promotion is being advertised. For inputs to properly represent the effect in the model it is necessary that: The model sees enough events with the input present. For example, by virtue of the model lifetime (or time window) being long enough to see several “seasons” or by having enough volume for the model to learn seasonality quickly. Proportional Frequency If we create a model that ignores seasonality it is possible to use that model to predict how the specific person likelihood differs from average. If we have a divergence from average then we can transfer that divergence proportionally to the observed frequency at the time of the prediction. Definitions: Ft = trailing average frequency of the event at time “t”. The average is done over a suitable period of to achieve a statistical significant estimate. F = average frequency as seen by the model. L = likelihood predicted by the model for a specific person Lt = predicted likelihood proportionally scaled for time “t”. If the model is good at predicting deviation from average, and this holds over the interesting range of seasons, then we can estimate Lt as: Lt = L * (Ft / F) Considering that: L = (L – F) + F Substituting we get: Lt = [(L – F) + F] * (Ft / F) Which simplifies to: (i)                  Lt = (L – F) * (Ft / F)  +  Ft This latest expression can be understood as “The adjusted likelihood at time t is the average likelihood at time t plus the effect from the model, which is calculated as the difference from average time the proportion of frequencies”. The formula above assumes a linear translation of the proportion. It is possible to generalize the formula using a factor which we will call “a” as follows: (ii)                Lt = (L – F) * (Ft / F) * a  +  Ft It is also possible to use a formula that does not scale the difference, like: (iii)               Lt = (L – F) * a  +  Ft While these formulas seem reasonable, they should be taken as hypothesis to be proven with empirical data. A theoretical analysis provides the following insights: The Cumulative Gains Chart (lift) should stay the same, as at any given time the order of the likelihood for different customers is preserved If F is equal to Ft then the formula reverts to “L” If (Ft = 0) then Lt in (i) and (ii) is 0 It is possible for Lt to be above 1. If it is desired to avoid going over 1, for relatively high base frequencies it is possible to use a relative interpretation of the multiplicative factor. For example, if we say that Y is twice as likely as X, then we can interpret this sentence as: If X is 3%, then Y is 6% If X is 11%, then Y is 22% If X is 70%, then Y is 85% - in this case we interpret “twice as likely” as “half as likely to not happen” Applying this reasoning to (i) for example we would get: If (L < F) or (Ft < (1 / ((L/F) + 1)) Then  Lt = L * (Ft / F) Else Lt = 1 – (F / L) + (Ft * F / L)  

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• Hai mai pensato a quanto ti costa qualificare le tue opportunità commerciali?

  - by user812481

  Il successo delle attività di marketing è dovuto alla profonda conoscenza dei propri clienti: chi sono, cosa acquistano e perché, come preferiscono essere contattati. Se i dati sui clienti sono distribuiti su più sistemi, rispondere a queste domande diventa difficile ed oneroso. Hai bisogno di un mix di strumenti best-in-class per l'automazione della forza di vendita e per l'efficienza delle attività di marketing, facendo confluire i dati chiave in un unico punto di accesso, per una visione a 360 gradi dei clienti. Vorresti incrementare il ROI delle campagne di marketing, proponendo diversi messaggi in funzione dei differenti target, ottenendo così un maggior successo delle iniziative? Scopri come ottenere una conoscenza maggiore del target per creare campagne di successo, mirate e personalizzate, attraverso video in italiano e docuemtni da condividere con i vostri colleghi.

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• Sneak Peak: Social Developer Program at JavaOne

  - by Mike Stiles

  By guest blogger Roland Smart We're just days away from what is gunning to be the most exciting installment of OpenWorld to date, so how about an exciting sneak peak at the very first Social Developer Program? If your first thought is, "What's a social developer?" you're not alone. It’s an emerging term and one we think will gain prominence as social experiences become more prevalent in enterprise applications. For those who keep an eye on the ever-evolving Facebook platform, you'll recall that they recently rebranded their PDC (preferred developer consultant) group as the PMD (preferred marketing developer), signaling the importance of development resources inside the marketing organization to unlock the potential of social. The marketing developer they're referring to could be considered a social developer in a broader context. While it's true social has really blossomed in the marketing context and CMOs are winning more and more technical resources, social is starting to work its way more deeply into the enterprise with the help of developers that work outside marketing. Developers, like the rest of us, have fallen in "like" with social functionality and are starting to imagine how social can transform enterprise applications in the way it has consumer-facing experiences. The thesis of my presentation is that social developers will take many pages from the marketing playbook as they apply social inside the enterprise. To support this argument, lets walk through a range of enterprise applications and explore how consumer-facing social experiences might be interpreted in this context. Here's one example of how a social experience could be integrated into a sales enablement application. As a marketer, I spend a great deal of time collaborating with my sales colleagues, so I have good insight into their working process. While at Involver, we grew our sales team quickly, and it became evident some of our processes broke with scale. For example, we used to have weekly team meetings at which we'd discuss what was working and what wasn't from a messaging perspective. One aspect of these sessions focused on "objections" and "responses," where the salespeople would walk through common objections to purchasing and share appropriate responses. We tried to map each context to best answers and we'd capture these on a wiki page. As our team grew, however, participation at scale just wasn't tenable, and our wiki pages quickly lost their freshness. Imagine giving salespeople a place where they could submit common objections and responses for their colleagues to see, sort, comment on, and vote on. What you'd get is an up-to-date and relevant repository of information. And, if you supported an application like this with a social graph, it would be possible to make good recommendations to individual sales people about the objections they'd likely hear based on vertical, product, region or other graph data. Taking it even further, you could build in a badging/game element to reward those salespeople who participate the most. Both these examples are based on proven models at work inside consumer-facing applications. If you want to learn about how HR, Operations, Product Development and Customer Support can leverage social experiences, you’re welcome to join us at JavaOne or join our Social Developer Community to find some of the presentations after OpenWorld.

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• Update: GTAS and EBS

  - by jeffrey.waterman

  Provided below are updated target date timeframes for provided patches for upcoming legislative enhancements.   Dates have been pushed out from previous dates provided due to changes in Treasury mandatory dates.  Mandatory dates for GTAS and IPAC have changes since previous target dates for patches were provided.   These are target dates, not commitments to deliver functionality. Deliverable Target Timeframes for Customer Patches Comments R12 GTAS Configuration Apr 2012 Patch is available GTAS Key Processes Oct/Nov 2012 Includes GTAS processes necessary to create the GTAS interface file, migration of FACTS balances to GTAS, GTAS Trial Balance, and GTAS Transaction Register. GTAS Reports Nov/Dec 2012 GTAS Trial Balance GTAS Transaction Register Capture of Trading Partner TAS/BETC Apr/May 2013 Includes modification necessary to capture BETC, Trading Partner TAS/BETC on relevant transactions. GTAS Other Processes May/Jun  2013 Includes GTAS Customer and Vendor  update processes. IPAC Aug/Sep Includes modification required to IPAC to accommodate Componentized TAS and BETC. 11i GTAS Configuration May 2012 Patch is available GTAS Key Processes Nov/Dec 2012 Includes GTAS processes necessary to create the GTAS interface file, migration of FACTS balances to GTAS, GTAS Trial Balance, and GTAS Transaction Register. GTAS Reports Dec/Jan 2012 GTAS Trial Balance GTAS Transaction Register Capture of Trading Partner TAS/BETC May/Jun 2013 Includes modification necessary to capture BETC, Trading Partner TAS/BETC on relevant transactions. GTAS Other Processes Jun/Jul 2013 Includes GTAS Customer and Vendor  update processes. IPAC Sep/Oct 2013 Includes modification required to IPAC to accommodate Componentized TAS and BETC.

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• Week 17: Specialization Flashback

  - by sandra.haan

  Remember when E.T. phoned home and Ferris had a day off? Or when Michael Jackson did the moonwalk and Madonna was the Material Girl? That's what we call an 80's flashback. Remember when we offered you 11 specializations? That's what we call a Specialization flashback considering we now have over 35 Specializations available. A lot has changed since we rolled-out OPN Specialized last year. Listen in as Nick Kritikos talks about the latest specializations available. Now get out of that DeLorean and take a look at the Specialization Guide to determine how your company can get Specialized. Until next time, The OPN Communications Team

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• How to Waste Your Marketing Budget

  - by Mike Stiles

  Philosophers have long said if you find out where a man’s money is, you’ll know where his heart is. Find out where money in a marketing budget is allocated, and you’ll know how adaptive and ready that company is for the near future. Marketing spends are an investment. Not unlike buying stock, the money is placed in areas the marketer feels will yield the highest return. Good stock pickers know the lay of the land, the sectors, the companies, and trends. Likewise, good marketers should know the media available to them, their audience, what they like & want, what they want their marketing to achieve…and trends. So what are they doing? And how are they doing? A recent eTail report shows nearly half of retailers planned on focusing on SEO, SEM, and site research technologies in the coming months. On the surface, that’s smart. You want people to find you. And you’re willing to let the SEO tail wag the dog and dictate the quality (or lack thereof) of your content such as blogs to make that happen. So search is prioritized well ahead of social, multi-channel initiatives, email, even mobile - despite the undisputed explosive growth and adoption of it by the public. 13% of retailers plan to focus on online video in the next 3 months. 29% said they’d look at it in 6 months. Buying SEO trickery is easy. Attracting and holding an audience with wanted, relevant content…that’s the hard part. So marketers continue to kick the content can down the road. Pretty risky since content can draw and bind customers to you. Asked to look a year ahead, retailers started thinking about CRM systems, customer segmentation, and loyalty, (again well ahead of online video, social and site personalization). What these investors are missing is social is spreading across every function of the enterprise and will be a part of CRM, personalization, loyalty programs, etc. They’re using social for engagement but not for PR, customer service, and sales. Mistake. Allocations are being made seemingly blind to the trends. Even more peculiar are the results of an analysis Mary Meeker of Kleiner Perkins made. She looked at how much time people spend with media types and how marketers are investing in those media. 26% of media consumption is online, marketers spend 22% of their ad budgets there. 10% of media time is spent with mobile, but marketers are spending 1% of their ad budgets there. 7% of media time is spent with print, but (get this) marketers spend 25% of their ad budgets there. It’s like being on Superman’s Bizarro World. Mary adds that of the online spending, most goes to search while spends on content, even ad content, stayed flat. Stock pickers know to buy low and sell high. It means peering with info in hand into the likely future of a stock and making the investment in it before it peaks. Either marketers aren’t believing the data and trends they’re seeing, or they can’t convince higher-ups to acknowledge change and adjust their portfolios accordingly. Follow @mikestilesImage via stock.xchng

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• links for 2010-06-14

  - by Bob Rhubart

  White Paper: Application Portfolio Rationalization: How IT Standardization Fuels Growth Co-authors Hamidou Dia and Roy Hunter describe an Enterprise Architecture approach to application portfolio rationalization. (tags: oracle otn entarch) @soatoday: Cloud & Compliance: Write a Solid Prenup "Think of your cloud contract as a prenuptial agreement," says Oracle ACE Director Jordan Braunstein. "There must be clear recourse and commitments." (tags: soa cloud oracleace entarch) @fteter: Resilience and Relationships "Take a look at your own enterprise architecture with these ideas in mind," suggests Oracle ACE Director Floyd Teter, "and see if your outlook doesn't change." (tags: entarch complexity oracleace) @lucasjellema: Calling an EJB from a SOA Composite Application using the EJB Binding based on Java Interface Oracle ACE Director Lucas Jellema illustrates the use of one of several new capabilities in Oracle SOA Suite 11g R1 Patch Set 2 (11.1.1.3.0). (tags: soa oracleace middleware soasuite oracle)

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• Developer Day @ OOP 2001with SOA Specialized Partners

  - by Jürgen Kress

  Oracle SOA Specialized Partners like Opitz Consulting participate in our key marketing events. Therefore make sure that you start your journey to SOA Specialization! ORACLE Developer Day auf der OOP: Entdecken Sie die Einsatzmöglichkeiten und Leistungsfähigkeit der Java-Technologie! incl. Live Hacking mit Special Guest: JAVA Guru Adam Bien! Enterprise-Anwendungen leicht gemacht! Beschleunigen Sie Ihre Entwicklung mit Java. Kommen Sie zum kostenlosen Ganztages-Workshop von ORACLE auf der OOP und lernen Sie die Leistungsfähigkeit von Java kennen. Erfahren Sie mehr über die Java Strategie und die Produktroadmap, welche Einsatzmöglichkeiten Java SE für Embedded erschließt und wie sich eine SOA und BPM-Lösung auf der Basis von Java realisieren lässt. Die vielfältigen Verbesserungen von Java EE6 erleichtern den Entwicklern das Leben erheblich. Kennen Sie bereits das Potential von Java EE6? Adam Bien wird Sie mit einem Live-Hacking von den Stühlen reißen. Torsten Winterberg, Oracle Fusion Middleware ACE Director und Danilo Schmiedel stellen vor wie Java Entwickler die Oracle SOA & BPM Lösungen einbinden können. Am Nachmittag können Sie dann in einer Hands-On Session mit Ihrem eigenen Laptop Java Persistence API, Java Beans, CDI und weitere Technologien ausprobieren. In diesem kostenlosen Workshop von Oracle können Sie sich mit Gleichgesinnten austauschen, sich die neueste Technik direkt von den Oracle Experten zeigen lassen und an praktischen Programmierübungen teilnehmen. Auf dieser Veranstaltung sind Sie richtig, wenn Sie mehr über den aktuellen Status der Java Roadmap wissen wollen, mehr über Java Technologie- und Lösungen (Java SE, ME, etc) erfahren wollen, die Plattform Java EE erproben, die Vorteile der Java EE 6 für Ihre Arbeit verstehen möchten, wenn Sie auf eine Enterprise-Landschaft hochskalieren wollen, mit Java Server Faces Front-Ends erstellen, neue Entwicklungsprojekte planen oder gerade in Angriff annehmen. Registrieren Sie sich jetzt!   ICM - Internationales Congress Center München Am Messesee, Trudering-Riem 81829 München 27. Januar 2011 9.00 Uhr - 16.30 Uhr For more information on SOA Specialization and the SOA Partner Community please feel free to register at www.oracle.com/goto/emea/soa (OPN account required) Blog Twitter LinkedIn Mix Forum Wiki Website Technorati Tags: OOP,Adam Bien,Torsten Winterberg,Opitz Consulting,Oracle,SOA,SOA Specialization,OPN

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• Always disable the 8.3 name creation on Windows before installing WebCenter Content or WebLogic Server

  - by Kevin Smith

  You should always disable the 8.3 name creation feature when installing WebCenter Content on a Windows platform. The installs will normally work without it disabled, but you will find the weird 8.3 file and directory names in all the config files. Disabling it can also improve performance. On Windows XP and Windows Server 2003 and above you can do it with this command: fsutil.exe behavior set disable8dot3 1 To make sure it is disabled you can run this command to check: fsutil.exe behavior query disable8dot3 If the 8.3 file name creation is disabled you will see the following output from the command: The registry state of NtfsDisable8dot3NameCreation is 1 (Disable 8dot3 name creation on all volumes). Here is a Microsoft note on how to do this on Windows 2000 and Windows NT. How to Disable the 8.3 Name Creation on NTFS Partitions

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• CRM vs VRM

  - by David Dorf

  In a previous post, I discussed the potential power of combining social, interest, and location graphs in order to personalize marketing and shopping experiences for consumers.  Marketing companies have been trying to collect detailed information for that very purpose, a large majority of which comes from tracking people on the internet.  But their approaches stem from the one-way nature of traditional advertising.  With TV, radio, and magazines there is no opportunity to truly connect to customers, which has trained marketing companies to [covertly] collect data and segment customers into easily identifiable groups.  To a large extent, we think of this as CRM. But what if we turned this viewpoint upside-down to accommodate for the two-way nature of social media?  The notion of marketing as conversations was the basis for the Cluetrain, an early attempt at drawing attention to the fact that customers are actually unique humans.  A more practical implementation is Project VRM, which is a reverse CRM of sorts.  Instead of vendors managing their relationships with customers, customers manage their relationships with vendors. Your shopping experience is not really controlled by you; rather, its controlled by the retailer and advertisers.  And unfortunately, they typically don't give you a say in the matter.  Yes, they might tailor the content for "female age 25-35 interested in shoes" but that's not really the essence of you, is it?  A better approach is to the let consumers volunteer information about themselves.  And why wouldn't they if it means a better, more relevant shopping experience?  I'd gladly list out my likes and dislikes in exchange for getting rid of all those annoying cookies on my harddrive. I really like this diagram from Beyond SocialCRM as it captures the differences between CRM and VRM. The closest thing to VRM I can find is Buyosphere, a start-up that allows consumers to track their shopping history across many vendors, then share it appropriately.  Also, Amazon does a pretty good job allowing its customers to edit their profile, which includes everything you've ever purchased from Amazon.  You can mark items as gifts, or explicitly exclude them from their recommendation engine.  This is a win-win for both the consumer and retailer. So here is my plea to retailers: Instead of trying to infer my interests from snapshots of my day, please just ask me.  We'll both have a better experience in the long-run.

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• Customisation / overriding of the Envelop ecs files

  - by Dheeraj Kumar M

  There are few usecases where the requirement is to customise the envelop information (Interchange/Group ecs file). Such scenarios might be required to be used for only few of the customers. Hence, in addition to the default seeded envelop definitions, it also required to upload the customised definitions. Here is the steps for achieving the same. 1. Create only the Interchange ecs and save 2. Create only the group ecs and save 3. Use the same in B2B 1. Create only the Interchange ecs and save :       Open the document editor and select the required version and doctype. During creating new ecs, ensure to select the checkbox for insert envelop.       Once created, delete the group and transactionset nodes and retain only the Interchange ecs nodes, including both header and trailer. Save this file. 2. Create only the group ecs and save       After creating the ecs file as mentioned in steps of Interchange creation, delete the Interchange and transactionset nodes and retain only the group ecs nodes, including both header and trailer. Save this file. 3. Use the same in B2B       These newly created ecs can be used in B2B by 2 ways.              a. By overriding at the trading partner Level:              This will be very useful when the configuration is complete and then need to incorporate the customisation. In this case, just select the Trading partner - document - select the document which need to be customised.              Upload the newly created Interchange and group ECS files under the Interchange and group tabs respectively and re-deply the associated agreement.              The advantage of this approach is              - Flexibility to add customised envelop definitions to the partners              - Save the re-work of design time effort.              b. By adding another document definition in Administration - document screen:              This scenario can be used if there is no configuration done at the trading partner level. Create the required document revision and overtide the Interchange and group ECS files under the Interchange and group tabs respectively. Add the document in Trading partner - document. Create and deploy the agreements

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• Demo on Data Guard Protection From Lost-Write Corruption

  - by Rene Kundersma

  Today I received the news a new demo has been made available on OTN for Data Guard protection from lost-write corruption. Since this is a typical MAA solution and a very nice demo I decided to mention this great feature also in this blog even while it's a recommended best practice for some time. When lost writes occur an I/O subsystem acknowledges the completion of the block write even though the write I/O did not occur in the persistent storage. On a subsequent block read on the primary database, the I/O subsystem returns the stale version of the data block, which might be used to update other blocks of the database, thereby corrupting it.  Lost writes can occur after an OS or storage device driver failure, faulty host bus adapters, disk controller failures and volume manager errors. In the demo a data block lost write occurs when an I/O subsystem acknowledges the completion of the block write, while in fact the write did not occur in the persistent storage. When a primary database lost write corruption is detected by a Data Guard physical standby database, Redo Apply (MRP) will stop and the standby will signal an ORA-752 error to explicitly indicate a primary lost write has occurred (preventing corruption from spreading to the standby database). Links: MOS (1302539.1). "Best Practices for Corruption Detection, Prevention, and Automatic Repair - in a Data Guard Configuration" Demo MAA Best Practices Rene Kundersma

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• Announcement: New Tutorial - Using ADF Faces and ADF Controller with OEPE

  - by Juan Camilo Ruiz

  We are happy to announce the publication of our newest tutorial, that explores some of the latest features added in our OEPE 12c release for ADF Development. The tutorial walks you through the creation of an ADF application that uses the ADF Faces Rich Client components, in combination with the ADF Controler, ADF Model and JPA. By developing this tutorial you will work and understand various features added into OEPE 12c that are specific to ADF development such as: ADF taskflow editor Visual pageDefinition editor ADF integration with AppXRay Navigation across artifacts such as pages, pageDefinition, managed beans, etc. Property inspector for ADF Faces components. Stay tunned for more and exciting tutorials that explore this and much more OEPE features. And of course your feedback is always welcome!

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• Announcing Upcoming SOA and JMS Introductory Blog Posts

  - by John-Brown.Evans

  Announcing Upcoming SOA and JMS Introductory Blog Posts Beginning next week, SOA Proactive Support will begin posting a series of introductory blogs here on working with JMS in a SOA context. The posts will begin with how to set up JMS in WebLogic server, lead you through reading and writing to a JMS queue from the WLS Java samples, continue with how to access it from a SOA composite and, finally, describe how to set up and access AQ JMS (Advanced Queuing JMS) from a SOA/BPEL process. The posts will be of a tutorial nature and include step-by-step examples. Your questions and feedback are encouraged. The following topics are planned: How to Create a Simple JMS Queue in Weblogic Server 11g Using the QueueSend.java Sample Program to Send a Message to a JMS Queue Using the QueueReceive.java Sample Program to Read a Message from a JMS Queue How to Create an 11g BPEL Process Which Writes a Message Based on an XML Schema to a JMS Queue How to Create an 11g BPEL Process Which Reads a Message Based on an XML Schema from a JMS Queue How to Set Up an AQ JMS (Advanced Queueing JMS) for SOA Purposes How to Write to an AQ JMS Queue from a BPEL Process How to Read from an AQ JMS Queue from a BPEL Process

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• Linking to BIP reports from BIEE Analyses

  - by Tim Dexter

  Bryan found a great blog post from Fiston over on the OBIEEStuff blog. It covers the ability to link to a BIP report from a BIEE analyses report with the ability to pass parameters to it. I have doubled checked and you need to be on OBIEE 11.1.1.5 to see the 'Shared Report Link' mentioned in Fiston's post when you open a BIP report from the /analytics side of the house. Enjoy! OBIEE to BIP trick

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• View Link inConsistency

  - by Abhishek Dwivedi

  What is View Link Consistency? When multiple instances (say VO1, VO2, VO3 etc) of an EO-based VO are based on the same underlying EO, a new row created in one of these VO instances (say VO1)can be automatically added (without re-query) to the row sets of the others (VO2, VO3 etc ). This capability is known as the view link consistency. This feature works for any VO for which it is enabled, regardless of whether they are involved in a view link or not. What causes View Link inConsistency? Unless jbo.viewlink.consistent  is disabled for this VO (or globally), or setAssociationConsistent(false) is applied, any of the following can cause View Link inConsistency.  1. setWhereClause 2. Unreferenced secondary EO 3. findByViewCriteria() 4. Using view link accessor row set Why does this happen - View Link inConsistency? Well, there can be one of the following reasons. a. In case of 1 & 2, the view link consistency flag is disabled on that view object. b. As far as 3 is concerned, findByViewCriteria is used to retrieve a new row set to process programmatically without changing the contents of the default row set. In this case, unlike previous cases, the view link consistency flag is not disabled, meaning that the changes in the default row set would be reflected in the new row set.  However, the opposite doesn't hold true. For instance, if a row is deleted from this new row set, the corresponding row in the default row set does not get deleted. In one of my features, which involved deletion of row(s), I resolved the view link inconsistency issue by replacing findByViewCriteria by applyViewCriteria. b. For 4, it's similar to 3 - whenever a view link accessor row set is retrieved, a new row set is created. Now, creating new row set does not mean re-executing the query each time, only creating a new instance of a RowSet object with its default iterator reset to the "slot" before the first row. Also, please note that this new row set always originates from an internally created view object instance, not one you that added to the data model. This internal view object instance is created as needed and added with a system-defined name to the root application module. Anyway, the very reason a distinct, internally-created view object instance is used is to guarantee that it remains unaffected by developer-related changes to their own view objects instances in the data model.

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• To access parentAM instance from within nestedAM JUnit test class

  - by Abhishek Dwivedi

  In normal model project, the way to access parent AM from within nested AM is simple - ParentAMImpl parentAM =  (ParentAMImpl)this.getRootApplicationModule(); However, the same approach doesn't help in JUnit model project. Use the following approach -  Inside setUp() method --  ParentAM parentAM =  (ParentAM)Configuration.createRootApplicationModule(ROOT_AM, ROOT_AM_CONFIG); Inside tearDown() method -- Configuration.releaseRootApplicationModule(parentAM, true);

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• What's Old is New Again

  - by David Dorf

  Last night I told my son he could stream music to his tablet "from the cloud" (in this case, the Amazon Cloud).  He paused, then said, "what is the cloud?"  I replied, "a bunch of servers connected to the internet."  Apparently he had visions of something much more magnificent.  Another similar term is "big data."  These marketing terms help to quickly convey topics but are oversimplifications that are open to many interpretations.  At their core, those terms a shiny packages holding recycled ideas. I see many headlines declaring big data changes everything, but it doesn't.  Savvy retailers have been dealing with large volumes of data since the electronic cash register was invented.  But the there have a been a few changes to the landscape that make big data a topic of conversation: 1. Computing power has caught up to storage volumes. Its now possible to more thoroughly analyze the copious volumes of data retailers have been squirreling away.  CPUs are faster, sold state drives more plentiful, and new ways to store and search data are available.  My iPhone is more power than the computer used in the Apollo mission to the moon. 2. Unstructured data is everywhere.  The Web used to be where retailers published product information, but now users are generating the bulk of the content in the form of comments, videos, and "likes."  The variety of information available to retailers is huge, and it meaning difficult to discern. 3. Everything is connected.  Looking at a report from my router, there are no less than 20 active devices on my home network.  We can track the location of mobile phones, tag products with RFID, and set our thermostats (I love my Nest) from a thousand miles away.  Not only is there more data, but its arriving at higher velocity. Careful readers will note the three Vs that help define so-called big data: volume, variety, and velocity. We now have more volume, more variety, and more velocity and different technologies to deal with them.  But at the heart, the objectives are still the same: Informed decisions Accurate forecasts Improved optimizations So don't let the term "big data" throw you off the scent.  Retailers still need to execute on the basics.  But do take a fresh look at the data that's available and the new technologies to process it.  The landscape will continue to change and agile organizations will always be reevaluating their approaches.  You can just add some more weapons to the arsenal.

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• New Cloud Security Book: Securing the Cloud by Vic Winkler

  - by user12608550

  It's rare that I read a technical book straight through; I usually read key chapters and save the rest for later reference. But Winkler's book, written by an accomplished and highly experienced security professional, was worth a complete read, cover to cover. Of the recently published cloud security books, such as... Cloud Security and Privacy: An Enterprise Perspective on Risks and Compliance, by Tim Mather, Subra Kumaraswamy, and Shahed Latif; O'Reilly Media Inc, 2009; Cloud Computing: Implementation, Management, and Security, by John Rittenhouse and James Ransome; CRC Press 2010; Cloud Security: A Comprehensive Guide to Secure Cloud Computing, by Ronald Krutz and Russell Vines; Wiley Publishing Inc, 2010 ...Securing the Cloud is the most useful and informative about all aspects of cloud security. Clearly, through his experience, the author has thought through many practical issues of securing large, virtualized IT installations. His Chapter 6 on Best Practices and Chapter 9 with its valuable checklists are worth the price of the book. If you are among the many new cloud computing professionals, Securing the Cloud is an essential reference for your work.

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• ODI y Las funciones GROUP BY, SUM, etc

  - by Edmundo Carmona

  Las bondades de ODI Pase un buen rato buscando la forma de usar la función SUM en ODI, encontré que se puede modificar el KM para agregar la función "GROUP by" y agregar una función jython en el atributo destino, pero esa solución es muy "DURA" ya que si agregamos en el futuro un nuevo atributo, tendríamos que cambiar nuevamente el KM.  Pues bien la solución es bastante más fácil, resulta que podemos agregar la función SUM, MIN, MAX, etcétera a cualquier atributo numérico y ODI automáticamente agregará la función GROUP by con el resto de los atributos. Por ejemplo. La tabla destino tiene los siguientes atributos y asignaciones (mapeos en spanglish): T1.Att1 = T2.Att1 T1.Att2 = T2.Att2 T1.Att3 = SUM(T2.Att3)  ODI crea este Quey: Select T2.Att1, T2.Att2, SUM(Att3) from Table2 T2 group by T2.Att1, T2.Att2 Listo Nada más sencillo.

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• Adatlopások, adatszivárgások és más incidensek az USA egészségügyében

  - by user645740

  A The New York Times blogján olvastam a hírt, hogy ismét adatlopás történt, most 4,5 milló páciens adatát szerezték meg hackerek 2014 április és június között, most a Community Health Systems rendszerébol. A cég 206 kórházat üzemeltet. Az ellopott adatok tartalmazzák a születési dátumokat, telefonszámokat, stb. is, viszont most egészségügyi állapotukra, kezelésükre vonatkozó adatot nem szereztek meg. A cikk itt olvasható: Hack of Community Health Systems Affects 4.5 Million Patients: http://bits.blogs.nytimes.com/2014/08/18/hack-of-community-health-systems-affects-4-5-million-patients/ Az USÁ-ban törvényi kötelezettségnek megfeleloen publikálni kell minden biztonsági incidenst, ami legalább 500 személy érint. Ezeket az adatokat a következo oldalon tekinthetjük meg: http://www.hhs.gov/ocr/privacy/hipaa/administrative/breachnotificationrule/breachtool.htmlCsak 2014-ben legalább 75 incidens volt, összesen több mint 1080 incidens van az adathalmazban. Sokszor papír alapon szivárogtak ki az infók, vagy nem titkosított USB drive, laptop tunt el, stb, illetve hacking is jó néhányszor elofordult.

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