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• Securing Flexfield Value Sets in EBS 12.2

  - by Sara Woodhull

  Release 12.2 includes a new feature: flexfield value set security. This new feature gives you additional options for ensuring that different administrators have non-overlapping responsibilities, which in turn provides checks and balances for sensitive activities.  Separation of Duties (SoD) is one of the key concepts of internal controls and is a requirement for many regulations including: Sarbanes-Oxley (SOX) Act Health Insurance Portability and Accountability Act (HIPAA) European Union Data Protection Directive. Its primary intent is to put barriers in place to prevent fraud or theft by an individual acting alone. Implementing Separation of Duties requires minimizing the possibility that users could modify data across application functions where the users should not normally have access. For flexfields and report parameters in Oracle E-Business Suite, values in value sets can affect functionality such as the rollup of accounting data, job grades used at a company, and so on. Controlling access to the creation or modification of value set values can be an important piece of implementing Separation of Duties in an organization. New Flexfield Value Set Security feature Flexfield value set security allows system administrators to restrict users from viewing, adding or updating values in specific value sets. Value set security enables role-based separation of duties for key flexfields, descriptive flexfields, and report parameters. For example, you can set up value set security such that certain users can view or insert values for any value set used by the Accounting Flexfield but no other value sets, while other users can view and update values for value sets used for any flexfields in Oracle HRMS. You can also segregate access by Operating Unit as well as by role or responsibility.Value set security uses a combination of data security and role-based access control in Oracle User Management. Flexfield value set security provides a level of security that is different from the previously-existing and similarly-named features in Oracle E-Business Suite: Function security controls whether a user has access to a specific page or form, as well as what operations the user can do in that screen. Flexfield value security controls what values a user can enter into a flexfield segment or report parameter (by responsibility) during routine data entry in many transaction screens across Oracle E-Business Suite. Flexfield value set security (this feature, new in Release 12.2) controls who can view, insert, or update values for a particular value set (by flexfield, report, or value set) in the Segment Values form (FNDFFMSV). The effect of flexfield value set security is that a user of the Segment Values form will only be able to view those value sets for which the user has been granted access. Further, the user will be able to insert or update/disable values in that value set if the user has been granted privileges to do so.  Flexfield value set security affects independent, dependent, and certain table-validated value sets for flexfields and report parameters. Initial State of the Feature upon Upgrade Because this is a new security feature, it is turned on by default.  When you initially install or upgrade to Release 12.2.2, no users are allowed to view, insert or update any value set values (users may even think that their values are missing or invalid because they cannot see the values).  You must explicitly set up access for specific users by enabling appropriate grants and roles for those users.We recommend using flexfield value set security as part of a comprehensive Separation of Duties strategy. However, if you choose not to implement flexfield value set security upon upgrading to or installing Release 12.2, you can enable backwards compatibility--users can access any value sets if they have access to the Values form--after you upgrade. The feature does not affect day-to-day transactions that use flexfields.  However, you must either set up specific grants and roles or enable backwards compatibility before users can create new values or update or disable existing values. For more information, see: Release 12.2 Flexfield Value Set Security Documentation Update for Patch 17305947:R12.FND.C (Document 1589204.1) R12.2 TOI: Implement and Use Application Object Library (AOL) - Flexfields Security and Separation of Duties for Value Sets (recorded training)

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• BizTalk&ndash;Mapping repeating EDI segments using a Table Looping functoid

  - by Bill Osuch

  BizTalk’s HIPAA X12 schemas have several repeating date/time segments in them, where the XML winds up looking something like this: <DTM_StatementDate> <DTM01_DateTimeQualifier>232</DTM01_DateTimeQualifier> <DTM02_ClaimDate>20120301</DTM02_ClaimDate> </DTM_StatementDate> <DTM_StatementDate> <DTM01_DateTimeQualifier>233</DTM01_DateTimeQualifier> <DTM02_ClaimDate>20120302</DTM02_ClaimDate> </DTM_StatementDate> The corresponding EDI segments would look like this: DTM*232*20120301~ DTM*233*20120302~ The DateTimeQualifier element indicates whether it’s the start date or end date – 232 for start, 233 for end. So in this example (an X12 835) we’re saying the statement starts on 3/1/2012 and ends on 3/2/2012. When you’re mapping from some other data format, many times your start and end dates will be within the same node, like this: <StatementDates> <Begin>20120301</Begin> <End>20120302</End> </StatementDates> So how do you map from that and create two repeating segments in your destination map? You could connect both the <Begin> and <End> nodes to a looping functoid, and connect its output to <DTM_StatementDate>, then connect both <Begin> and <End> to <DTM_StatementDate> … this would give you two repeating segments, each with the correct date, but how to add the correct qualifier? The answer is the Table Looping Functoid! To test this, let’s create a simplified schema that just contains the date fields we’re mapping. First, create your input schema: And your output schema: Now create a map that uses these two schemas, and drag a Table Looping functoid onto it. The first input parameter configures the scope (or how many times the records will loop), so drag a link from the StatementDates node over to the functoid. Yes, StatementDates only appears once, so this would make it seem like it would only loop once, but you’ll see in just a minute. The second parameter in the functoid is the number of columns in the output table. We want to fill two fields, so just set this to 2. Now drag the Begin and End nodes over to the functoid. Finally, we want to add the constant values for DateTimeQualifier, so add a value of 232 and another of 233. When all your inputs are configured, it should look like this: Now we’ll configure the output table. Click on the Table Looping Grid, and configure it to look like this: Microsoft’s description of this functoid says “The Table Looping functoid repeats with the looping record it is connected to. Within each iteration, it loops once per row in the table looping grid, producing multiple output loops.” So here we will loop (# of <StatementDates> nodes) * (Rows in the table), or 2 times. Drag two Table Extractor functoids onto the map; these are what are going to pull the data we want out of the table. The first input to each of these will be the output of the TableLooping functoid, and the second input will be the row number to pull from. So the functoid connected to <DTM01_DateTimeQualifier> will look like this: Connect these two functoids to the two nodes we want to populate, and connect another output from the Table Looping functoid to the <DTM_StatementDate> record. You should have a map that looks something like this: Create some sample xml, use it as the TestMap Input Instance, and you should get a result like the XML at the top of this post. Technorati Tags: BizTalk, EDI, Mapping

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• Best way to distribute form that can be printed or saved?

  - by Jason Antman

  I need to develop a simple form (intended only for printing) to be filled in by arbitrary end users (i.e. no specialized software). Ideally, I'd like the end-user to be able to save their inputs to the form and update it periodically. It seems that (at least without LiveCycle Enterprise Suite) Adobe Reader won't save data input in a PDF form. Aside from just distributing the form as a Word document, does anyone have any suggestions? Background: I do some work for a volunteer ambulance corps. They have a lot of elderly patients who don't know (or can't remember) their medical history. They want to develop a common form with personal information (name, address, DOB, medications list, etc.) for elderly residents to hang on their refrigerators (apparently a common solution to this problem). As some of them (or their children/grandchildren) are computer literate, it would make most sense to provide a download-able blank form that can be filled in, saved, updated, and re-printed as needed. Due to worries about privacy, HIPAA, etc. anything with server-side generation is out, it needs to be 100% client-side, and in a format that the majority of non-technical computer users can access without additional software. Thanks for any tips... at this point, I'm leaning towards just using a .doc form.

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• Reference Data Management and Master Data: Are Relation ?

  - by Mala Narasimharajan

  Submitted By:  Rahul Kamath  Oracle Data Relationship Management (DRM) has always been extremely powerful as an Enterprise Master Data Management (MDM) solution that can help manage changes to master data in a way that influences enterprise structure, whether it be mastering chart of accounts to enable financial transformation, or revamping organization structures to drive business transformation and operational efficiencies, or restructuring sales territories to enable equitable distribution of leads to sales teams following the acquisition of new products, or adding additional cost centers to enable fine grain control over expenses. Increasingly, DRM is also being utilized by Oracle customers for reference data management, an emerging solution space that deserves some explanation. What is reference data? How does it relate to Master Data? Reference data is a close cousin of master data. While master data is challenged with problems of unique identification, may be more rapidly changing, requires consensus building across stakeholders and lends structure to business transactions, reference data is simpler, more slowly changing, but has semantic content that is used to categorize or group other information assets – including master data – and gives them contextual value. In fact, the creation of a new master data element may require new reference data to be created. For example, when a European company acquires a US business, chances are that they will now need to adapt their product line taxonomy to include a new category to describe the newly acquired US product line. Further, the cross-border transaction will also result in a revised geo hierarchy. The addition of new products represents changes to master data while changes to product categories and geo hierarchy are examples of reference data changes.1 The following table contains an illustrative list of examples of reference data by type. Reference data types may include types and codes, business taxonomies, complex relationships & cross-domain mappings or standards. Types & Codes Taxonomies Relationships / Mappings Standards Transaction Codes Industry Classification Categories and Codes, e.g., North America Industry Classification System (NAICS) Product / Segment; Product / Geo Calendars (e.g., Gregorian, Fiscal, Manufacturing, Retail, ISO8601) Lookup Tables (e.g., Gender, Marital Status, etc.) Product Categories City à State à Postal Codes Currency Codes (e.g., ISO) Status Codes Sales Territories (e.g., Geo, Industry Verticals, Named Accounts, Federal/State/Local/Defense) Customer / Market Segment; Business Unit / Channel Country Codes (e.g., ISO 3166, UN) Role Codes Market Segments Country Codes / Currency Codes / Financial Accounts Date/Time, Time Zones (e.g., ISO 8601) Domain Values Universal Standard Products and Services Classification (UNSPSC), eCl@ss International Classification of Diseases (ICD) e.g., ICD9 à IC10 mappings Tax Rates Why manage reference data? Reference data carries contextual value and meaning and therefore its use can drive business logic that helps execute a business process, create a desired application behavior or provide meaningful segmentation to analyze transaction data. Further, mapping reference data often requires human judgment. Sample Use Cases of Reference Data Management Healthcare: Diagnostic Codes The reference data challenges in the healthcare industry offer a case in point. Part of being HIPAA compliant requires medical practitioners to transition diagnosis codes from ICD-9 to ICD-10, a medical coding scheme used to classify diseases, signs and symptoms, causes, etc. The transition to ICD-10 has a significant impact on business processes, procedures, contracts, and IT systems. Since both code sets ICD-9 and ICD-10 offer diagnosis codes of very different levels of granularity, human judgment is required to map ICD-9 codes to ICD-10. The process requires collaboration and consensus building among stakeholders much in the same way as does master data management. Moreover, to build reports to understand utilization, frequency and quality of diagnoses, medical practitioners may need to “cross-walk” mappings -- either forward to ICD-10 or backwards to ICD-9 depending upon the reporting time horizon. Spend Management: Product, Service & Supplier Codes Similarly, as an enterprise looks to rationalize suppliers and leverage their spend, conforming supplier codes, as well as product and service codes requires supporting multiple classification schemes that may include industry standards (e.g., UNSPSC, eCl@ss) or enterprise taxonomies. Aberdeen Group estimates that 90% of companies rely on spreadsheets and manual reviews to aggregate, classify and analyze spend data, and that data management activities account for 12-15% of the sourcing cycle and consume 30-50% of a commodity manager’s time. Creating a common map across the extended enterprise to rationalize codes across procurement, accounts payable, general ledger, credit card, procurement card (P-card) as well as ACH and bank systems can cut sourcing costs, improve compliance, lower inventory stock, and free up talent to focus on value added tasks. Change Management: Point of Sales Transaction Codes and Product Codes In the specialty finance industry, enterprises are confronted with usury laws – governed at the state and local level – that regulate financial product innovation as it relates to consumer loans, check cashing and pawn lending. To comply, it is important to demonstrate that transactions booked at the point of sale are posted against valid product codes that were on offer at the time of booking the sale. Since new products are being released at a steady stream, it is important to ensure timely and accurate mapping of point-of-sale transaction codes with the appropriate product and GL codes to comply with the changing regulations. Multi-National Companies: Industry Classification Schemes As companies grow and expand across geographies, a typical challenge they encounter with reference data represents reconciling various versions of industry classification schemes in use across nations. While the United States, Mexico and Canada conform to the North American Industry Classification System (NAICS) standard, European Union countries choose different variants of the NACE industry classification scheme. Multi-national companies must manage the individual national NACE schemes and reconcile the differences across countries. Enterprises must invest in a reference data change management application to address the challenge of distributing reference data changes to downstream applications and assess which applications were impacted by a given change. References 1 Master Data versus Reference Data, Malcolm Chisholm, April 1, 2006.

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• Taking the Plunge - or Dipping Your Toe - into the Fluffy IAM Cloud by Paul Dhanjal (Simeio Solutions)

  - by Greg Jensen

  In our last three posts, we’ve examined the revolution that’s occurring today in identity and access management (IAM). We looked at the business drivers behind the growth of cloud-based IAM, the shortcomings of the old, last-century IAM models, and the new opportunities that federation, identity hubs and other new cloud capabilities can provide by changing the way you interact with everyone who does business with you. In this, our final post in the series, we’ll cover the key things you, the enterprise architect, should keep in mind when considering moving IAM to the cloud. Invariably, what starts the consideration process is a burning business need: a compliance requirement, security vulnerability or belt-tightening edict. Many on the business side view IAM as the “silver bullet” – and for good reason. You can almost always devise a solution using some aspect of IAM. The most critical question to ask first when using IAM to address the business need is, simply: is my solution complete? Typically, “business” is not focused on the big picture. Understandably, they’re focused instead on the need at hand: Can we be HIPAA compliant in 6 months? Can we tighten our new hire, employee transfer and termination processes? What can we do to prevent another password breach? Can we reduce our service center costs by the end of next quarter? The business may not be focused on the complete set of services offered by IAM but rather a single aspect or two. But it is the job – indeed the duty – of the enterprise architect to ensure that all aspects are being met. It’s like remodeling a house but failing to consider the impact on the foundation, the furnace or the zoning or setback requirements. While the homeowners may not be thinking of such things, the architect, of course, must. At Simeio Solutions, the way we ensure that all aspects are being taken into account – to expose any gaps or weaknesses – is to assess our client’s IAM capabilities against a five-step maturity model ranging from “ad hoc” to “optimized.” The model we use is similar to Capability Maturity Model Integration (CMMI) developed by the Software Engineering Institute (SEI) at Carnegie Mellon University. It’s based upon some simple criteria, which can provide a visual representation of how well our clients fair when evaluated against four core categories: ·         Program Governance ·         Access Management (e.g., Single Sign-On) ·         Identity and Access Governance (e.g., Identity Intelligence) ·         Enterprise Security (e.g., DLP and SIEM) Often our clients believe they have a solution with all the bases covered, but the model exposes the gaps or weaknesses. The gaps are ideal opportunities for the cloud to enter into the conversation. The complete process is straightforward: 1.    Look at the big picture, not just the immediate need – what is our roadmap and how does this solution fit? 2.    Determine where you stand with respect to the four core areas – what are the gaps? 3.    Decide how to cover the gaps – what role can the cloud play? Returning to our home remodeling analogy, at some point, if gaps or weaknesses are discovered when evaluating the complete impact of the proposed remodel – if the existing foundation wouldn’t support the new addition, for example – the owners need to decide if it’s time to move to a new house instead of trying to remodel the old one. However, with IAM it’s not an either-or proposition – i.e., either move to the cloud or fix the existing infrastructure. It’s possible to use new cloud technologies just to cover the gaps. Many of our clients start their migration to the cloud this way, dipping in their toe instead of taking the plunge all at once. Because our cloud services offering is based on the Oracle Identity and Access Management Suite, we can offer a tremendous amount of flexibility in this regard. The Oracle platform is not a collection of point solutions, but rather a complete, integrated, best-of-breed suite. Yet it’s not an all-or-nothing proposition. You can choose just the features and capabilities you need using a pay-as-you-go model, incrementally turning on and off services as needed. Better still, all the other capabilities are there, at the ready, whenever you need them. Spooling up these cloud-only services takes just a fraction of the time it would take a typical organization to deploy internally. SLAs in the cloud may be higher than on premise, too. And by using a suite of software that’s complete and integrated, you can dramatically lower cost and complexity. If your in-house solution cannot be migrated to the cloud, you might consider using hardware appliances such as Simeio’s Cloud Interceptor to extend your enterprise out into the network. You might also consider using Expert Managed Services. Cost is usually the key factor – not just development costs but also operational sustainment costs. Talent or resourcing issues often come into play when thinking about sustaining a program. Expert Managed Services such as those we offer at Simeio can address those concerns head on. In a cloud offering, identity and access services lend to the new paradigms described in my previous posts. Most importantly, it allows us all to focus on what we're meant to do – provide value, lower costs and increase security to our respective organizations. It’s that magic “silver bullet” that business knew you had all along. If you’d like to talk more, you can find us at simeiosolutions.com.

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• Master Data Management and Cloud Computing

  - by david.butler(at)oracle.com

  Cloud Computing is all the rage these days. There are many reasons why this is so. But like its predecessor, Service Oriented Architecture, it can fall on hard times if the underlying data is left unmanaged. Master Data Management is the perfect Cloud companion. It can materially increase the chances for successful Cloud initiatives. In this blog, I'll review the nature of the Cloud and show how MDM fits in.   Here's the National Institute of Standards and Technology Cloud definition: •          Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction.   Cloud architectures have three main layers: applications or Software as a Service (SaaS), Platforms as a Service (PaaS), and Infrastructure as a Service (IaaS). SaaS generally refers to applications that are delivered to end-users over the Internet. Oracle CRM On Demand is an example of a SaaS application. Today there are hundreds of SaaS providers covering a wide variety of applications including Salesforce.com, Workday, and Netsuite. Oracle MDM applications are located in this layer of Oracle's On Demand enterprise Cloud platform. We call it Master Data as a Service (MDaaS). PaaS generally refers to an application deployment platform delivered as a service. They are often built on a grid computing architecture and include database and middleware. Oracle Fusion Middleware is in this category and includes the SOA and Data Integration products used to connect SaaS applications including MDM. Finally, IaaS generally refers to computing hardware (servers, storage and network) delivered as a service.  This typically includes the associated software as well: operating systems, virtualization, clustering, etc.    Cloud Computing benefits are compelling for a large number of organizations. These include significant cost savings, increased flexibility, and fast deployments. Cost advantages include paying for just what you use. This is especially critical for organizations with variable or seasonal usage. Companies don't have to invest to support peak computing periods. Costs are also more predictable and controllable. Increased agility includes access to the latest technology and experts without making significant up front investments.   While Cloud Computing is certainly very alluring with a clear value proposition, it is not without its challenges. An IDC survey of 244 IT executives/CIOs and their line-of-business (LOB) colleagues identified a number of issues:   Security - 74% identified security as an issue involving data privacy and resource access control. Integration - 61% found that it is hard to integrate Cloud Apps with in-house applications. Operational Costs - 50% are worried that On Demand will actually cost more given the impact of poor data quality on the rest of the enterprise. Compliance - 49% felt that compliance with required regulatory, legal and general industry requirements (such as PCI, HIPAA and Sarbanes-Oxley) would be a major issue. When control is lost, the ability of a provider to directly manage how and where data is deployed, used and destroyed is negatively impacted.  There are others, but I singled out these four top issues because Master Data Management, properly incorporated into a Cloud Computing infrastructure, can significantly ameliorate all of these problems. Cloud Computing can literally rain raw data across the enterprise.   According to fellow blogger, Mike Ferguson, "the fracturing of data caused by the adoption of cloud computing raises the importance of MDM in keeping disparate data synchronized."   David Linthicum, CTO Blue Mountain Labs blogs that "the lack of MDM will become more of an issue as cloud computing rises. We're moving from complex federated on-premise systems, to complex federated on-premise and cloud-delivered systems."    Left unmanaged, non-standard, inconsistent, ungoverned data with questionable quality can pollute analytical systems, increase operational costs, and reduce the ROI in Cloud and On-Premise applications. As cloud computing becomes more relevant, and more data, applications, services, and processes are moved out to cloud computing platforms, the need for MDM becomes ever more important. Oracle's MDM suite is designed to deal with all four of the above Cloud issues listed in the IDC survey.   Security - MDM manages all master data attribute privacy and resource access control issues. Integration - MDM pre-integrates Cloud Apps with each other and with On Premise applications at the data level. Operational Costs - MDM significantly reduces operational costs by increasing data quality, thereby improving enterprise business processes efficiency. Compliance - MDM, with its built in Data Governance capabilities, insures that the data is governed according to organizational standards. This facilitates rapid and accurate reporting for compliance purposes. Oracle MDM creates governed high quality master data. A unified cleansed and standardized data view is produced. The Oracle Customer Hub creates a single view of the customer. The Oracle Product Hub creates high quality product data designed to support all go-to-market processes. Oracle Supplier Hub dramatically reduces the chances of 'supplier exceptions'. Oracle Site Hub masters locations. And Oracle Hyperion Data Relationship Management masters financial reference data and manages enterprise hierarchies across operational areas from ERP to EPM and CRM to SCM. Oracle Fusion Middleware connects Cloud and On Premise applications to MDM Hubs and brings high quality master data to your enterprise business processes.   An independent analyst once said "Poor data quality is like dirt on the windshield. You may be able to drive for a long time with slowly degrading vision, but at some point, you either have to stop and clear the windshield or risk everything."  Cloud Computing has the potential to significantly degrade data quality across the enterprise over time. Deploying a Master Data Management solution prior to or in conjunction with a move to the Cloud can insure that the data flowing into the enterprise from the Cloud is clean and governed. This will in turn insure that expected returns on the investment in Cloud Computing will be realized.       Oracle MDM has proven its metal in this area and has the customers to back that up. In fact, I will be hosting a webcast on Tuesday, April 10th at 10 am PT with one of our top Cloud customers, the Church Pension Group. They have moved all mainline applications to a hosted model and use Oracle MDM to insure the master data is managed and cleansed before it is propagated to other cloud and internal systems. I invite you join Martin Hossfeld, VP, IT Operations, and Danette Patterson, Enterprise Data Manager as they review business drivers for MDM and hosted applications, how they did it, the benefits achieved, and lessons learned. You can register for this free webcast here.  Hope to see you there.

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• How Mature is Your Database Change Management Process?

  - by Ben Rees

  .dbd-banner p{ font-size:0.75em; padding:0 0 10px; margin:0 } .dbd-banner p span{ color:#675C6D; } .dbd-banner p:last-child{ padding:0; } @media ALL and (max-width:640px){ .dbd-banner{ background:#f0f0f0; padding:5px; color:#333; margin-top: 5px; } } -- Database Delivery Patterns & Practices Further Reading Organization and team processes How do you get your database schema changes live, on to your production system? As your team of developers and DBAs are working on the changes to the database to support your business-critical applications, how do these updates wend their way through from dev environments, possibly to QA, hopefully through pre-production and eventually to production in a controlled, reliable and repeatable way? In this article, I describe a model we use to try and understand the different stages that customers go through as their database change management processes mature, from the very basic and manual, through to advanced continuous delivery practices. I also provide a simple chart that will help you determine “How mature is our database change management process?” This process of managing changes to the database – which all of us who have worked in application/database development have had to deal with in one form or another – is sometimes known as Database Change Management (even if we’ve never used the term ourselves). And it’s a difficult process, often painfully so. Some developers take the approach of “I’ve no idea how my changes get live – I just write the stored procedures and add columns to the tables. It’s someone else’s problem to get this stuff live. I think we’ve got a DBA somewhere who deals with it – I don’t know, I’ve never met him/her”. I know I used to work that way. I worked that way because I assumed that making the updates to production was a trivial task – how hard can it be? Pause the application for half an hour in the middle of the night, copy over the changes to the app and the database, and switch it back on again? Voila! But somehow it never seemed that easy. And it certainly was never that easy for database changes. Why? Because you can’t just overwrite the old database with the new version. Databases have a state – more specifically 4Tb of critical data built up over the last 12 years of running your business, and if your quick hotfix happened to accidentally delete that 4Tb of data, then you’re “Looking for a new role” pretty quickly after the failed release. There are a lot of other reasons why a managed database change management process is important for organisations, besides job security, not least: Frequency of releases. Many business managers are feeling the pressure to get functionality out to their users sooner, quicker and more reliably. The new book (which I highly recommend) Lean Enterprise by Jez Humble, Barry O’Reilly and Joanne Molesky provides a great discussion on how many enterprises are having to move towards a leaner, more frequent release cycle to maintain their competitive advantage. It’s no longer acceptable to release once per year, leaving your customers waiting all year for changes they desperately need (and expect) Auditing and compliance. SOX, HIPAA and other compliance frameworks have demanded that companies implement proper processes for managing changes to their databases, whether managing schema changes, making sure that the data itself is being looked after correctly or other mechanisms that provide an audit trail of changes. We’ve found, at Red Gate that we have a very wide range of customers using every possible form of database change management imaginable. Everything from “Nothing – I just fix the schema on production from my laptop when things go wrong, and write it down in my notebook” to “A full Continuous Delivery process – any change made by a dev gets checked in and recorded, fully tested (including performance tests) before a (tested) release is made available to our Release Management system, ready for live deployment!”. And everything in between of course. Because of the vast number of customers using so many different approaches we found ourselves struggling to keep on top of what everyone was doing – struggling to identify patterns in customers’ behavior. This is useful for us, because we want to try and fit the products we have to different needs – different products are relevant to different customers and we waste everyone’s time (most notably, our customers’) if we’re suggesting products that aren’t appropriate for them. If someone visited a sports store, looking to embark on a new fitness program, and the store assistant suggested the latest $10,000 multi-gym, complete with multiple weights mechanisms, dumb-bells, pull-up bars and so on, then he’s likely to lose that customer. All he needed was a pair of running shoes! To solve this issue – in an attempt to simplify how we understand our customers and our offerings – we built a model. This is a an attempt at trying to classify our customers in to some sort of model or “Customer Maturity Framework” as we rather grandly term it, which somehow simplifies our understanding of what our customers are doing. The great statistician, George Box (amongst other things, the “Box” in the Box-Jenkins time series model) gave us the famous quote: “Essentially all models are wrong, but some are useful” We’ve taken this quote to heart – we know it’s a gross over-simplification of the real world of how users work with complex legacy and new database developments. Almost nobody precisely fits in to one of our categories. But we hope it’s useful and interesting. There are actually a number of similar models that exist for more general application delivery. We’ve found these from ThoughtWorks/Forrester, from InfoQ and others, and initially we tried just taking these models and replacing the word “application” for “database”. However, we hit a problem. From talking to our customers we know that users are far less further down the road of mature database change management than they are for application development. As a simple example, no application developer, who wants to keep his/her job would develop an application for an organisation without source controlling that code. Sure, he/she might not be using an advanced Gitflow branching methodology but they’ll certainly be making sure their code gets managed in a repo somewhere with all the benefits of history, auditing and so on. But this certainly isn’t the case (yet) for the database – a very large segment of the people we speak to have no source control set up for their databases whatsoever, even at the most basic level (for example, keeping change scripts in a source control system somewhere). By the way, if this is you, Red Gate has a great whitepaper here, on the barriers people face getting a source control process implemented at their organisations. This difference in maturity is the same as you move in to areas such as continuous integration (common amongst app developers, relatively rare for database developers) and automated release management (growing amongst app developers, very rare for the database). So, when we created the model we started from scratch and biased the levels of maturity towards what we actually see amongst our customers. But, what are these stages? And what level are you? The table below describes our definitions for four levels of maturity – Baseline, Beginner, Intermediate and Advanced. As I say, this is a model – you won’t fit any of these categories perfectly, but hopefully one will ring true more than others. We’ve also created a PDF with a flow chart to help you find which of these groups most closely matches your team:  Download the Database Delivery Maturity Framework PDF here   Level D1 – Baseline Work directly on live databases Sometimes work directly in production Generate manual scripts for releases. Sometimes use a product like SQL Compare or similar to do this Any tests that we might have are run manually Level D2 – Beginner Have some ad-hoc DB version control such as manually adding upgrade scripts to a version control system Attempt is made to keep production in sync with development environments There is some documentation and planning of manual deployments Some basic automated DB testing in process Level D3 – Intermediate The database is fully version-controlled with a product like Red Gate SQL Source Control or SSDT Database environments are managed Production environment schema is reproducible from the source control system There are some automated tests Have looked at using migration scripts for difficult database refactoring cases Level D4 – Advanced Using continuous integration for database changes Build, testing and deployment of DB changes carried out through a proper database release process Fully automated tests Production system is monitored for fast feedback to developers   Does this model reflect your team at all? Where are you on this journey? We’d be very interested in knowing how you get on. We’re doing a lot of work at the moment, at Red Gate, trying to help people progress through these stages. For example, if you’re currently not source controlling your database, then this is a natural next step. If you are already source controlling your database, what about the next stage – continuous integration and automated release management? To help understand these issues, there’s a summary of the Red Gate Database Delivery learning program on our site, alongside a Patterns and Practices library here on Simple-Talk and a Training Academy section on our documentation site to help you get up and running with the tools you need to progress. All feedback is welcome and it would be great to hear where you find yourself on this journey! This article is part of our database delivery patterns & practices series on Simple Talk. Find more articles for version control, automated testing, continuous integration & deployment.

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• Reference Data Management

  - by rahulkamath

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Increasingly, DRM is also being utilized by Oracle customers for reference data management, an emerging solution space that deserves some explanation. What is reference data? Reference data is a close cousin of master data. While master data may be more rapidly changing, requires consensus building across stakeholders and lends structure to business transactions, reference data is simpler, more slowly changing, but has semantic content that is used to categorize or group other information assets – including master data – and give them contextual value. The following table contains an illustrative list of examples of reference data by type. Reference data types may include types and codes, business taxonomies, complex relationships & cross-domain mappings or standards. Types & Codes Taxonomies Relationships / Mappings Standards Transaction Codes Industry Classification Categories and Codes, e.g., North America Industry Classification System (NAICS) Product / Segment; Product / Geo Calendars (e.g., Gregorian, Fiscal, Manufacturing, Retail, ISO8601) Lookup Tables (e.g., Gender, Marital Status, etc.) Product Categories City à State à Postal Codes Currency Codes (e.g., ISO) Status Codes Sales Territories (e.g., Geo, Industry Verticals, Named Accounts, Federal/State/Local/Defense) Customer / Market Segment; Business Unit / Channel Country Codes (e.g., ISO 3166, UN) Role Codes Market Segments Country Codes / Currency Codes / Financial Accounts Date/Time, Time Zones (e.g., ISO 8601) Domain Values Universal Standard Products and Services Classification (UNSPSC), eCl@ss International Classification of Diseases (ICD) e.g., ICD9 à IC10 mappings Tax Rates Why manage reference data? Reference data carries contextual value and meaning and therefore its use can drive business logic that helps execute a business process, create a desired application behavior or provide meaningful segmentation to analyze transaction data. Further, mapping reference data often requires human judgment. Sample Use Cases of Reference Data Management Healthcare: Diagnostic Codes The reference data challenges in the healthcare industry offer a case in point. Part of being HIPAA compliant requires medical practitioners to transition diagnosis codes from ICD-9 to ICD-10, a medical coding scheme used to classify diseases, signs and symptoms, causes, etc. The transition to ICD-10 has a significant impact on business processes, procedures, contracts, and IT systems. Since both code sets ICD-9 and ICD-10 offer diagnosis codes of very different levels of granularity, human judgment is required to map ICD-9 codes to ICD-10. The process requires collaboration and consensus building among stakeholders much in the same way as does master data management. Moreover, to build reports to understand utilization, frequency and quality of diagnoses, medical practitioners may need to “cross-walk” mappings -- either forward to ICD-10 or backwards to ICD-9 depending upon the reporting time horizon. Spend Management: Product, Service & Supplier Codes Similarly, as an enterprise looks to rationalize suppliers and leverage their spend, conforming supplier codes, as well as product and service codes requires supporting multiple classification schemes that may include industry standards (e.g., UNSPSC, eCl@ss) or enterprise taxonomies. Aberdeen Group estimates that 90% of companies rely on spreadsheets and manual reviews to aggregate, classify and analyze spend data, and that data management activities account for 12-15% of the sourcing cycle and consume 30-50% of a commodity manager’s time. Creating a common map across the extended enterprise to rationalize codes across procurement, accounts payable, general ledger, credit card, procurement card (P-card) as well as ACH and bank systems can cut sourcing costs, improve compliance, lower inventory stock, and free up talent to focus on value added tasks. Specialty Finance: Point of Sales Transaction Codes and Product Codes In the specialty finance industry, enterprises are confronted with usury laws – governed at the state and local level – that regulate financial product innovation as it relates to consumer loans, check cashing and pawn lending. To comply, it is important to demonstrate that transactions booked at the point of sale are posted against valid product codes that were on offer at the time of booking the sale. Since new products are being released at a steady stream, it is important to ensure timely and accurate mapping of point-of-sale transaction codes with the appropriate product and GL codes to comply with the changing regulations. Multi-National Companies: Industry Classification Schemes As companies grow and expand across geographies, a typical challenge they encounter with reference data represents reconciling various versions of industry classification schemes in use across nations. While the United States, Mexico and Canada conform to the North American Industry Classification System (NAICS) standard, European Union countries choose different variants of the NACE industry classification scheme. Multi-national companies must manage the individual national NACE schemes and reconcile the differences across countries. Enterprises must invest in a reference data change management application to address the challenge of distributing reference data changes to downstream applications and assess which applications were impacted by a given change.

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• New in MySQL Enterprise Edition: Policy-based Auditing!

  - by Rob Young

  Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} For those with an interest in MySQL, this weekend's MySQL Connect conference in San Francisco has gotten off to a great start. On Saturday Tomas announced the feature complete MySQL 5.6 Release Candidate that is now available for Community adoption and testing. This announcement marks the sprint to GA that should be ready for release within the next 90 days. You can get a quick summary of the key 5.6 features here or better yet download the 5.6 RC (under “Development Releases”), review what's new and try it out for yourself! There were also product related announcements around MySQL Cluster 7.3 and MySQL Enterprise Edition . This latter announcement is of particular interest if you are faced with internal and regulatory compliance requirements as it addresses and solves a pain point that is shared by most developers and DBAs; new, out of the box compliance for MySQL applications via policy-based audit logging of user and query level activity. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} One of the most common requests we get for the MySQL roadmap is for quick and easy logging of audit events. This is mainly due to how web-based applications have evolved from nice-to-have enablers to mission-critical revenue generation and the important role MySQL plays in the new dynamic. In today’s virtual marketplace, PCI compliance guidelines ensure credit card data is secure within e-commerce apps; from a corporate standpoint, Sarbanes-Oxely, HIPAA and other regulations guard the medical, financial, public sector and other personal data centric industries. For supporting applications audit policies and controls that monitor the eyes and hands that have viewed and acted upon the most sensitive of data is most commonly implemented on the back-end database. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} With this in mind, MySQL 5.5 introduced an open audit plugin API that enables all MySQL users to write their own auditing plugins based on application specific requirements. While the supporting docs are very complete and provide working code samples, writing an audit plugin requires time and low-level expertise to develop, test, implement and maintain. To help those who don't have the time and/or expertise to develop such a plugin, Oracle now ships MySQL 5.5.28 and higher with an easy to use, out-of-the-box auditing solution; MySQL Enterprise Audit. MySQL Enterprise Audit The premise behind MySQL Enterprise Audit is simple; we wanted to provide an easy to use, policy-based auditing solution that enables you to quickly and seamlessly add compliance to their MySQL applications. MySQL Enterprise Audit meets this requirement by enabling you to: 1. Easily install the needed components. Installation requires an upgrade to MySQL 5.5.28 (Enterprise edition), which can be downloaded from the My Oracle Support portal or the Oracle Software Delivery Cloud. After installation, you simply add the following to your my.cnf file to register and enable the audit plugin: [mysqld] plugin-load=audit_log.so (keep in mind the audit_log suffix is platform dependent, so .dll on Windows, etc.) or alternatively you can load the plugin at runtime: mysql> INSTALL PLUGIN audit_log SONAME 'audit_log.so'; 2. Dynamically enable and disable the audit stream for a specific MySQL server. A new global variable called audit_log_policy allows you to dynamically enable and disable audit stream logging for a specific MySQL server. The variable parameters are described below. 3. Define audit policy based on what needs to be logged (everything, logins, queries, or nothing), by server. The new audit_log_policy variable uses the following valid, descriptively named values to enable, disable audit stream logging and to filter the audit events that are logged to the audit stream: "ALL" - enable audit stream and log all events "LOGINS" - enable audit stream and log only login events "QUERIES" - enable audit stream and log only querie events "NONE" - disable audit stream 4. Manage audit log files using basic MySQL log rotation features. A new global variable, audit_log_rotate_on_size, allows you to automate the rotation and archival of audit stream log files based on size with archived log files renamed and appended with datetime stamp when a new file is opened for logging. 5. Integrate the MySQL audit stream with MySQL, Oracle tools and other third-party solutions. The MySQL audit stream is written as XML, using UFT-8 and can be easily formatted for viewing using a standard XML parser. This enables you to leverage tools from MySQL and others to view the contents. The audit stream was also developed to meet the Oracle database audit stream specification so combined Oracle/MySQL shops can import and manage MySQL audit images using the same Oracle tools they use for their Oracle databases. So assuming a successful MySQL 5.5.28 upgrade or installation, a common set up and use case scenario might look something like this: Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} It should be noted that MySQL Enterprise Audit was designed to be transparent at the application layer by allowing you to control the mix of log output buffering and asynchronous or synchronous disk writes to minimize the associated overhead that comes when the audit stream is enabled. The net result is that, depending on the chosen audit stream log stream options, most application users will see little to no difference in response times when the audit stream is enabled. So what are your next steps? Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Get all of the grainy details on MySQL Enterprise Audit, including all of the additional configuration options from the MySQL documentation. MySQL Enterprise Edition customers can download MySQL 5.5.28 with the Audit extension for production use from the My Oracle Support portal. Everyone can download MySQL 5.5.28 with the Audit extension for evaluation from the Oracle Software Delivery Cloud. Learn more about MySQL Enterprise Edition. As always, thanks for your continued support of MySQL!

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