Delivering the Key Component of Business  Intelligence—the System Architecture: 3 Best Practices
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Delivering the Key Component of Business Intelligence—the System Architecture: 3 Best Practices

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Delivering the Key Component of Business  Intelligence—the System Architecture: 3 Best Practices Delivering the Key Component of Business Intelligence—the System Architecture: 3 Best Practices Document Transcript

  • TECHNICAL WHITE PAPER Delivering the Key Component of Business Intelligence—the System Architecture: 3 Best Practices A Business Intelligence White Paper | September 2011. A B ST R AC T Business Intelligence is a broadly used term, and encompasses many areas. In this white paper, we will focus on the core component of any business intelligence solution, the end-to-end system architecture. We will also focus on three best practices—information management strategy, BI server selection and deploy- ment, and metadata management strategy—that can help define competent architecture in most organiza- tions. By no means is this the sole definitive approach, every organization’s needs will be different, however it does represent a best-practice, end-to-end architecture that will exist in some form in every business intelligence solution. CUSTO ME R B E N E FI T SThis approach represents a best-practice, end-to-end architecture that will exist in Gartner analysts Dan Sommer has remarked that “it is clear that BI continues to be a technology at the some form in every business intelligence center of information driven initiatives in organizations.” Improving business processes with business solution. intelligence (BI) is a number one priority of many CIOs. While the CIOs in many companies know they need business intelligence to grow their business, we find many organizations do not fully understand all that is involved in becoming a BI-enabled organization. Business Intelligence is a broadly used term, and encompasses many areas. In this white paper, we will focus on the core component of any business intelligence solution, the end-to-end system architecture. We will also focus on three best practices—information management strategy, BI server selection and deploy- ment, and metadata management strategy—that can help define competent architecture in most organiza- tions. By no means is this the sole definitive approach, every organization’s needs will be different, however it does represent a best-practice, end-to-end architecture that will exist in some form in every business intelligence solution. W W W. C P T E C H . C O M 781.273.4100 BUSINESS INTELLIGENCE
  • TECHNICAL WHITE PAPER . 1 . I MP L E M E N T AN I N FO R M AT I O N M AN AGE M E N T S TR AT EGY Data is pervasive in our organizations. We generate new data daily in our line of business applications, we receive data from our partners and vendors, we store data in custom databases, and we copy and enhance data in Excel. Data is also heterogeneous, residing in different vendor platforms such as Oracle, SQL Server, and DB2. Ultimately, we have data duplicated in many environments, we have confusion as to where related data resides, and we develop a trust with only a subset of the data, usually one that we ourselves control. One of the goals of a successful business intelligence Architecture should be to develop an information management strategy, which is the process of gathering data from disparate sources and combining the data into an amalgamated repository. Data in our source databases are usually optimized for data entry (the INSERT and UPDATE of records), and not for analysis (the SELECT of records). They are typically highly normalized, and if we were to look at the underlying database schemas, we would expect to find a large number of tables and joins along with cryptic naming conventions of tables and fields. The complexity of these databases makes it a challenge to create reports and is usually left in the hands of skilled IT developers. In a BI-enabled organization, we can’t expect our business users to understand the nuances of connect- ing to these different systems and how to relate them, nor should we expect them to. We need to find a way to mitigate this complexity, and this is done through a joint effort between the business users and IT. The business should be responsible for identifying what they need access to and how they would like it presented, in short they are the owners of the data. IT should be responsible for enabling access to the data to meet the business users’ needs. This shared ownership of data and system enables the business to become more self-sufficient long term, while reducing the workload on IT. Additionally, data in our source systems may be dirty and contain incorrect information. For example, a customer’s address may contain an invalid state or postal code, or multiple sales reps may be assigned as the active rep on an account, resulting in incorrect reporting, and in turn, incorrect business decisions being made based on that data. In addition to consolidating the data, organizations should also address the quality of their data to ensure accurate reporting and analysis. As data moves through the informa- tion management layer, the data should be cleaned for any anomalies based upon standardized business rules. For example, a business rule would ensure that all city, state, zip combinations are validated against a trusted reference list, and only records that pass this validation should be moved into our amalgamated database. A more complex scenario may include validating several attributes of a sales order record against a master customer list which originated from our CRM application to ensure this is a known customer, a master product list which originated from our ERP application to ensure this is a known product, and that the revenue is considered booked because the invoice payment was received in our Finance application. The qualification of all elements of data ensures we are getting an accurate understanding of our business. The reporting model, or target database, of our information management layer should be optimized for reporting and analysis, ensuring high performance queries with minimal structure complexity. This is achieved through implementation of star-schemas consisting of fact tables (the measurements, i.e. revenue and cost) and dimension tables (the entities, i.e. customers and products). These star schemas are easy to understand and offer great flexibility in query design as they are de-normalized and optimized for reporting. It’s important to note that we may need to further optimize the reporting database performance through the user of database partitioning and the creation of aggregation tables. Further enhancements may include the adoption of OLAP cube technology to maximize multi-dimensional reporting and analysis. 2 . D E P LOY A BU S I N E S S I N T E LLI GE N C E S E RVE R The selection of a Business Intelligence Server product can be daunting, as there are many vendors offering a wide variety of products for your consideration. The process in how you choose the right vendor is specific to each organization’s requirements, but the process can be made easier by choosing to leverage the as- sistance of a Business Intelligence services vendor to assist in understanding the products and what they can do for your organization. When selecting your Business Intelligence Server vendor, there is a common set of macro functionality across Features, Authentication and Authorization that you should require to ensure the most flexibility as your business grows. 2 W W W. C P T E C H . C O M 781.273.4100 BUSINESS INTELLIGENCE
  • TECHNICAL WHITE PAPER CUSTOM E R B E N E FI T S FE AT U RE S In a BI-enabled organization, we can’t A Business Intelligence Server should provide this common set of features: expect our business users to understandthe nuances of connecting to different sys- »» Dashboards provide top-line summaries of key business measures often with trend lines and rule- driven alerts, often providing embedded menus and selectors enabling intuitive interactivity with zero tems and how to relate them, nor should training we expect them to. »» Reports provide creation of controlled content, usually detail oriented, with precision page placement, limited/fixed interactivity, and often batch-generated »» Ad-hoc analysis provides business users with flexible content creation, including the ability to manipu- late the presentation, filter/drill on the data, all while dynamically recalculating aggregates based upon the layout »» Semantic Model provides a metadata layer between your data and your users where you can encap- sulate standardized naming conventions and calculations of your data fields. Additionally, you create simplified views of your data models so users spend their time analyzing the data rather than under- standing how to build queries. »» Scheduling & Distribution provides users with the ability to execute reports at specific dates & times, in different formats, and burst to multiple recipients both internally and externally to the organization »» Auditing allows for the monitoring of system usage, such as who ran what report, how long did it take, and what fields of information did they view AU T H E N TI C ATI O N Authentication is the act of identifying who is accessing your Business Intelligence Server. All users must be authenticated before they can access any content, run any reports, or view any data. The most common authentication method is for each user to have an ID and password managed by the Business Intelligence Server. While this approach is the simplest, you should consider leveraging external authentication methods which provide easier management and most likely better fit into your company’s security protocols. One approach is that users can enter their existing network login information to be authenticated against an Active Directory or a LDAP server so there is no need to remember a new set of credentials for accessing the Business Intelligence Server. Additionally, Single Sign On can be implemented to prevent the user from ever seeing a login screen. Once the user is trusted on the network, they can be trusted into the Business Intelligence Server. AU T H O RI Z ATI O N Authorization determines what a user can see and do within your Business Intelligence Server and is tightly coupled with authentication. Authorization controls access to a variety of BI related entities: »» Folder & Content Security limits what content a user can access, be it a restriction to a folder that con- tains many reports, or a specific report or dashboard »» Object Security limits what fields of information a user can see. For example, User 1 can see the Social Security Number field but User 2 cannot in the same report »» Row Security limits what rows of information a user can see. For example, User 1 can see NY, NJ, CT data, User 2 can only see NY data in the same report »» Database Security controls how users access the reporting databases, removing the necessity of users connecting to databases directly 3 . I MP L EM E N T A M E TADATA M AN AGE M E N T S T R ATEGY Over time, a tremendous amount of metadata is generated around the reporting and information manage- ment layers of your business intelligence architecture. This includes all the details around the data sources that fuel your reporting database, the business rules you apply during the amalgamation of your data, and any semantic model and report level business rules. Without proper change control procedures in your development lifecycle, you will most likely have to perform several cycles of regression testing before rolling out new functionality. A metadata management strategy will provide you with a repository of all your meta- data for your business intelligence system end-to-end, enabling you to perform data lineage and impact analysis queries. 3 W W W. C P T E C H . C O M 781.273.4100 BUSINESS INTELLIGENCE
  • TECHNICAL WHITE PAPER CUSTO ME R B E N E FI T S Data lineage is the ability to trace the source of a piece of data back through the business intelligence implementation. For example, let’s say you are looking at a report and the revenue number for a customer The selection of a Business Intelli- appears to be incorrect. A data lineage query would enable you to quickly identify what semantic model gence Server product can be daunt- that revenue field came from, including what business rule was applied to it. Furthermore, you can see what ing, as there are many vendors database table the semantic model field originated from, what data integration and data quality rules were offering a wide variety of products for performed on that database field, and finally what source systems and fields did it originate from. Ideally, your consideration. this lineage information would be accessible on the report itself. The metadata captured is also beneficial in the reverse order enabling you to understand what impact any future changes to any of the business intelligence system architecture layers would have on your users. For example, you organization has migrated your finance system to Microsoft Dynamics and you need to swap your existing data source for your reporting database accordingly. An impact analysis query against your metadata repository would be able to tell you what data integration tasks, data quality tasks, databases, semantic models, and reports are affected, greatly reducing your regression testing analysis and execution. SU MM A RY Following these best-practices for your Business Intelligence architecture will provide you with a proven, flexible architecture that will scale as your business grows. You do not need to implement all these tiers from day one, in fact, the best solutions is to implement in small iterations, adopting new tiers with subse- quent releases of your project. B U SI N E S S I N T E LLI GE N C E E X PE RT I S E Corporate Technologies Business Intelligence Group architects, implements, and manages production- quality BI solutions encompassing dashboards, reporting/analytics, BI Web portals, data warehouses, data quality enhancements, and custom integration. We’ve done this for clients in many industries—including finance/ insurance, manufacturing, retail, and hospitality—across many functions, including financial, sales, marketing, HR, and operations. We’re experts at understanding the data in your systems, its quality and security issues, and how to integrate it with BI platform and database technologies from market-leading providers including SAP/BOBJ, Oracle, and many others. A B O U T CO R PO R ATE T EC HN O LO GI E S , I N C . Corporate Technologies provides consulting services, project staffing, and systems integration to clients seeking continual transformation and optimization of their IT andData infrastructures. Through the ef- fective use of Virtualization, Cloud Computing, and High Impact Business Intelligence, we help our clients reduce operational costs, protect critical IT assets, and position themselves for growth. We leverage the power of Information Technology to meet our clients’ strategic and critical business goals reducing cost, increasing revenue, and mitigating business risk. We focus on giving IT professionals the resources they need to successfully solve complex business challenges through the use of innovative, high quality and cost effective IT solutions, services, products, staff and strategic recommendations resulting in long term and mutually beneficial relationships. © 2011 Corporate Technologies, Inc. All rights reserved. Corporate Technologies is a registered trademark of Corporate Technologies, Inc. All other trademarks or registered trademarks are the property of their respective owners.