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Deploying an Operational Business Intelligence Architecture

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					Deploying an Operational
    Business Intelligence Architecture
                      The WebFOCUS 7
                      Data Integration Framework




                A White Paper
     Table of Contents

1     Introduction


2     Finding the Sources of Business Intelligence
2     Recognizing Access and Integration Issues
3     Establishing a BI Integration Framework
4     The Framework’s Data Integration Layer
4     The Data Warehousing Layer
6     An Integrated Portfolio of Integration Technologies


7     WebFOCUS – a Data Integration Framework
      Optimized for Business Intelligence
8     A Scalable Platform for Ongoing Flexibility
9     A Metadata Repository That Simplifies Schema Development
10    Powerful Native Query Processing
11    SQL Translation Allows Access Optimization
11    Federation Keeps Data Location Transparent to Users
11    Data Usage Analysis Enables Performance Tuning
13    Preemptive Query Governing Assures Compliant Operations
14    Integrated Data Migration and Synchronization Enables
      Data Sharing
15    Non-DBMS, Business Format Transformation
17    Service Adapters Encapsulate Processes as Data Sources


19    Choose the Right Framework for Operational
      Business Intelligence
Introduction
    Operational business intelligence investments are only as good as the data they deliver, and
    unfortunately, many enterprises believe that business intelligence (BI) begins with data in a
    database or warehouse and ends with a management report. However, scalable, effective BI
    systems optimize data access and processes at the source – the vital information systems that
    run the business. When properly constructed, operational business intelligence systems provide
    critical input and feedback to everyone in the enterprise and beyond – not just to managers and
    business analysts.

    A successful operational system is built on a business intelligence data integration framework
    that enables an organization to create a repeatable, consistent approach for acquiring,
    transforming, integrating, and delivering data to applications and end users who need it.
    Information Builders’ WebFOCUS provides a powerful integration framework combined with
    advanced features to place highly effective business intelligence within reach of most
    organizations. By maximizing data at all of its sources, WebFOCUS helps organizations improve
    the effectiveness of their existing BI tools as well as enhance the quality of the information they
    use for driving business operations.




                                                                1    Information Builders
Finding the Sources of Business Intelligence
    In most people’s minds, business intelligence begins with a data warehouse or datamart and
    ends with an online analytical processing (OLAP) tool or report. However, the data itself doesn’t
    originate in a repository and most of an organization’s data never ends up in one. Data actually
    originates in operational transaction systems, packaged and legacy applications, individual’s
    spreadsheets, and from sources external to the organization. These origins are invisible to the
    traditional BI user or implementer, who have no sense of the time, cost, and complexity involved
    in gathering and preparing disparate data to make it available and useful.

    There is a better way to understand business intelligence. When examined as an end-to-end
    process, traditionally BI has relied upon an elaborate infrastructure comprised of these
    transaction systems, applications, multiple sources, electronic data exchanges, and many
    disparate, often labor-intensive processes. These processes must access, gather, reconcile, and
    prepare data to deliver an accurate view of the business to BI users.

    For example, data for the sales analysis application of a large automobile manufacturer
    originates in Excel spreadsheets, forwarded from all over the globe. Each spreadsheet’s contents
    and structure differs depending on the country of origin. All of these diverse spreadsheets must
    be reformatted, reconciled, and loaded, by hand, into a data store so that the data is available
    for monthly sales analysis processes.



    Recognizing Access and Integration Issues
    Today’s business intelligence needs often demand that source data be available in real time, as
    well as for historical analysis. They also demand that the resulting information be consistent and
    accurate. Therefore, accessing data for use in BI actually begins where source data is created or
    captured – in operational transaction systems, packaged applications, and legacy applications,
    as well as electronic business processes through which businesses exchange data. Data access
    is critically important because the more robust the data-access capabilities of a BI system, the
    more easily, cost-effectively, and consistently information may be produced and delivered to all
    of the information consumers who need it.

    Yet as Gartner points out, data integration issues consume a significant majority of the effort
    expended in a BI project. “Designing a repeatable process by which data is acquired from



                                                                2   Deploying an Operational Business Intelligence Architecture
operational systems, transformed, integrated, and delivered to the data warehouse is technically
challenging.”1 All of these data origins store, represent, and exchange data differently, typically
in mediums and formats that are incompatible with easy access, representation, or manipulation
by business intelligence consumers.



Establishing a BI Integration Framework
The ability of BI tools to exploit individual source interfaces is critical to accessing quality data
from its original sources. Sometimes applications need variable-length virtual storage access
method (VSAM) records or hierarchical data in IMS databases or extensible markup language
(XML) files. Sometimes integration requires access to systems through messaging interfaces like
WebSphere MQ. Sometimes data isn’t directly accessible at all, and an application must access
stored procedures, API calls, or Web services instead. Rather than seeking a single silver bullet
to resolve a wide range of integration challenges, organizations are better served by establishing
a unified BI data integration framework.

The framework’s purpose is to enable BI tools to interconnect, prepare, and aggregate data into
a unified and meaningful representation for information consumers. In addition to efficiently
populating data marts and warehouses, an integration framework can establish (and maintain)
real-time links to production data sources, enabling IT teams to avoid the costly process of
extracting, modeling, and loading data into separate reporting databases. A data integration
framework can also contribute to improved data quality since it is easier to match data against
third-party name, address, and location databases; merge information from disparate sources
into the same information structure, and eliminate duplicate, null, and outlier values.

By employing a unified metadata layer, the BI integration framework makes all required data
available, accessible, and meaningful at all levels of an organization – no matter where the data
exists, how it’s stored, or the latency involved in its access. Only a robust framework can
overcome data availability and accessibility gaps for a complete, consistent, and dependable
view of the business.




1 Friedman, Ted and Strange, Kevin H., “Architecture: The Foundation of Business Intelligence,” Gartner Research,

 AV-226453, April 14, 2004.

                                                                         3    Information Builders
The Framework’s Data Integration Layer
A robust data integration framework can be represented as a layered portfolio of integration
software technologies and tools that reside underneath visible BI tools. Based on the overall
requirements of business intelligence, the framework begins by accessing operational
databases, files, operational application systems, document repositories, electronic data
interchange (EDI) and other business-to-business data origins and wrapping them in unified
metadata. The framework can integrate data from these sources in three ways:
I   By direct access to the operational data stores or files servicing operational systems
I   Using the operational systems’ own application functions to access data on behalf of the BI
    information consumer; this is particularly important for information consistency, for example,
    if the same data is being accessed for both analytical and operational purposes
I   Using a relational staging database that refreshes and populates warehouse data as
    frequently as users’ needs dictate, either for real-time use or historical analysis


While all of these methods deliver high-quality data and metadata that supports users’ needs, a
data integration framework that offers selective direct access also delivers higher efficiency and
performance. Even when the framework must rely on application functions or staged data
integration techniques to access data, by having these processes reside within a single
infrastructure, the framework can utilize common access paths, metadata definitions,
configurations, tuning, and debugging tools. A common, reusable infrastructure simplifies
management and improves performance over having a collection of disparate, separate-access
tools. The data integration layer will also generate a comprehensive metadata representation
that can be captured and used in other framework layers to ensure proper data delivery and
support system administrators and BI users. Building an efficient data integration process is a
key component to quickly delivering powerful, cost-effective business intelligence solutions.



The Data Warehousing Layer
The framework’s data warehouse layer consists of analytical services that increase business
users’ visibility into their areas of responsibility. Information warehouses are usually developed
in phases, over time, and are designed to meet at least two basic requirements.




                                                             4   Deploying an Operational Business Intelligence Architecture
I   Enterprise data warehouses must define business variables that are true across the whole
    enterprise. For example, all financial information must be based on the organization’s
    financial year. Or all data derived from business-to-business exchanges or external sources
    must adhere to the organization’s overall information security policies. When this information
    is available, it will often identify gaps or reveal relevant facts that otherwise would have
    remained obscured by overlying data.
I   They must include, within their structure, business variables and metrics that are required for
    answering any analysis questions posed by the different business groups they serve. For
    example, organizations often develop a sequence of data marts containing information
    related to a specific subject area – such as competitive information or pricing – or a functional
    discipline, such as marketing or finance.


A BI data integration framework can further improve BI performance in several ways. The
framework can aid data warehouse tuning by enabling administrators to see who is using
what data and how frequently it is accessed, which in turn facilitates update prioritization,
elimination of dormant data, and real-time initiatives. A framework can also automate
warehouse administration with features that include operator alerts for exceptions, automated
exception handling based on predefined business rules, DBA alerts for key service-outages,
and a production schedule for running appropriate tasks, such as scheduling warehouse
updates and refreshes.




                                                              5   Information Builders
An Integrated Portfolio of Integration Technologies
Data access and integration capabilities are crucial to operational business intelligence
architecture. Organizations planning to deploy a BI system, therefore, should take a close look
at a potential system’s strengths in access and integration technologies. Information Builders’
WebFOCUS solution is a highly scalable enterprise business intelligence platform whose
integration framework allows business users to effortlessly access, query, analyze, share, and
disseminate information – on demand, where and when needed.

 Information Resources


                   Messages/        Legacy           Documents/                            Processes/
   RDBMS                                                                 Applications
                    Objects        DBMS/Files          Formats                              Services




                                                                       Adapter Manager




                                                     Adapter Framework

   Resource
                                                     Metadata Repository
   Governor

                                                       SQL Translator
   Resource
   Analyzer
                                             Data Manipulation Engine/Optimizer

  DataMigrator
                                                  Communications Subsystem

                                                         Data Server




 Interfaces              OLE DB            JDBC             ODBC                API/SQL




 WebFOCUS data integration architecture.




                                                                  6     Deploying an Operational Business Intelligence Architecture
WebFOCUS – a Data Integration Framework
Optimized for Business Intelligence
    The WebFOCUS data integration framework comprises an entire portfolio of integration
    technologies, for enabling data access and manipulation in a uniform way, regardless of its form,
    format, or location. The framework provides comprehensive, native access to more than 280
    sources – including relational and legacy data, data in enterprise applications, data staged in
    warehouses or marts, and real-time data from operational systems – on any platform.




     WebFOCUS 7’s architecture, integration, and simplicity permeate every level of the organization and make
     any data available, accessible, and meaningful to everyone who needs it, when and how they need it.


    To support business and technical users, WebFOCUS employs different access techniques and
    tools to produce high-quality data, a reusable infrastructure, and comprehensive metadata.
    Access tools include packaged adapters; extract, transform, and load (ETL) technologies; real-
    time transformation; enterprise information integration (EII); and Web services. Access

                                                                    7    Information Builders
techniques, which vary according to need, can include using ETL to extract, transform, and load
data directly into a data warehouse or mart; directly accessing operational data stores or the
files that service an operational system’s own application functions to access data; and trickle-
feeding a data warehouse to populate and refresh it, using real-time transformation.



A Scalable Platform for Ongoing Flexibility
The WebFOCUS data architecture is based upon the WebFOCUS data server, an SQL-based,
multi-threaded, highly scalable data manipulation engine that serves as the configuration and
run-time environment for WebFOCUS adapters.

The WebFOCUS framework enables high scalability, optimizing data access and manipulation at
the individual data adapter level, as well as across data resources, individual servers, or server
clusters. Using universal adapters, the WebFOCUS framework can access data at different levels
of latency and cost-effectively integrate it – without custom coding. Adapters are not limited to
staged data platforms; instead, they provide direct access to data in packaged applications,
legacy systems, EAI environments, and other technologies. They also allow dynamic drill-
through to detail data. Intelligent adapters will handle a wide variety of applications, formats,
databases, and protocols to help create a highly flexible architecture that is fully configurable for
both synchronous and asynchronous messages. This flexibility enables data architects to design
a BI solution architecture that easily meets the unique information needs of a range of users
while preserving the flexibility to adapt as these needs change.

With built-in scalability, even point projects based on standards like J2EE, .NET, XML, SOAP, and
EDI can be aggregated into a service-oriented architecture to accommodate needs ranging from
pulling bulk data and providing full ETL capabilities to incorporating data as part of a look-up.

The WebFOCUS framework also incorporates complete ETL functionality, allowing an
organization to scale its capabilities while protecting production applications and preserving
resources. Automated functionality significantly simplifies data warehouse creation,
maintenance, and expansion, and also streamlines application loading.

Support for Web services enables the framework to dynamically integrate live data as an integral
part of a business process. Further scalability may be achieved through the framework’s ability
to leverage server clusters and distribute workloads across many dissimilar machines.

                                                             8   Deploying an Operational Business Intelligence Architecture
A Metadata Repository That Simplifies Schema Development
The WebFOCUS data server provides a fully integrated Windows-based or Web-based metadata
console for deploying and configuring adapters and defining schema information for all
information resources supported by WebFOCUS adapters. Schema information is created using
automated tools that introspect and generate metadata information from the underlying
databases, files, copybooks, documents, or Web services. Once created, metadata information
may be made generally available to all users or associated with specific application views.

WebFOCUS metadata schema information may be easily cleansed, enriched, or enhanced using
integrated graphic tools contained within its data management console. The ability to create
user-defined and computed virtual fields within metadata schemas eliminates the need for
additional external data cleansing tools or having to write complex SQL logic within applications
or queries.




  WebFOCUS’ metadata configuration console automatically generates schema information that may be
  enriched for data quality purposes.

                                                              9    Information Builders
Powerful Native Query Processing
The data manipulation engine of WebFOCUS is fully SQL-compliant and supports read/write
operations against all relational data sources, VSAMs, IMS database management systems
(IMS/DBs), and Adabas data sources, as well as read operations against any data source
exposed through WebFOCUS adapters. At runtime, the WebFOCUS data manipulation engine
generates the SQL needed for retrieving specific data. A powerful translation engine
automatically translates SQL into the native data manipulation language necessary to access
legacy database systems or files.

An internal optimizer evaluates the best method of executing SQL operations, based on
important data characteristics such as cardinality, key fields, and other aspects. As a result, the
WebFOCUS data manipulation engine supports both homogeneous and heterogeneous join
operations that can be performed on the fly.




 A Web console enables optimization characteristics to be defined for efficient query processing.


                                                                 10    Deploying an Operational Business Intelligence Architecture
SQL Translation Allows Access Optimization
At the heart of WebFOCUS’ ability to access heterogeneous data sources is its SQL translation
engine, an ANSI SQL ’92-compliant data manipulation engine. The translation engine converts
SQL received from applications and queries into an internal, canonical form that is supported by
all WebFOCUS adapters. This form then translates SQL into specific SQL dialects supported by
proprietary RDBMSs. The canonical form can also translate SQL into the native data
manipulation language of legacy databases and files. Automatic pass-through (APT) or non-APT
optimization decisions are made on the fly by the WebFOCUS data server at runtime.

With multiple modes of operation, SQL translator enables data architects to optimize data
access strategies depending on the specific source data. APT operations eliminate translation
overhead, enabling SQL to be passed unaltered to an underlying RDBMS that controls all
aspects of SQL operations performed against it.



Federation Keeps Data Location Transparent to Users
WebFOCUS data servers and adapters reside locally with the information resources they
support. Once schema information is defined to WebFOCUS, it can be easily aggregated in one
or more location for data-location transparency. An application or end-user query accesses local
schema information and sees all available data as local relational tables.

At runtime, data requests are disaggregated and recast into the specific SQL or native requests
necessary to access and retrieve data from the appropriate data sources. Answer sets are
merged as necessary and then returned to the requesting application or user. Retrieved data
may also be cached for reuse.



Data Usage Analysis Enables Performance Tuning
In many cases, database and file design is not optimal for query usage. And frequently, actual
data usage does not align with intended usage. WebFOCUS Resource Analyzer can be used to
monitor how local or distributed data is stored, accessed, and used, giving administrators
visibility into usage patterns and enabling them to better tune their data environment for




                                                          11   Information Builders
improving performance. Resource Analyzer monitors more than 200 independent processing
statistics, such as I/Os, rows retrieved, CPU time, elapsed time, and others, allowing data
retrieval to be tuned to meet user and application performance requirements.




 Resource Analyzer provides information regarding how data is actually used.




                                                                12   Deploying an Operational Business Intelligence Architecture
Preemptive Query Governing Assures Compliant Operations
Optimization tools can enhance performance, but they do not prevent users from writing
incorrect ad hoc queries or application programmers from writing SQL operations that derail
database performance. WebFOCUS Resource Governor, a rules-based preemptive governor, uses
the statistics gathered by Resource Analyzer to create rules for cost-basis governing. Units of
cost and thresholds are defined using graphic tools and an English-like language. Resource
Governor then uses patented pattern-matching techniques to learn the characteristics of queries
being governed and generates governing rules based upon defined thresholds and costs. At
runtime, when a specific query exceeds a threshold, its execution may be disallowed or deferred
for batch execution at a later point in time.




 Resource Governor’s governing-rules-creation graphical
 interface is easy to use.




                                                          13   Information Builders
Integrated Data Migration and Synchronization Enables
Data Sharing
Unlike other data integration architectures, WebFOCUS incorporates a fully integrated ETL tool
within its native architecture. Data Migrator utilizes the WebFOCUS data manipulation engine,
data management console, and adapters to perform batch-oriented ETL operations between
source and target data sources.

In addition, WebFOCUS metadata information can be shared between applications and end
users that access data, as well as shared by utilizing data warehousing or data synchronization
staff implementing ETL scenarios to stage data for applications, data warehouses, or data marts.




 Data Migrator enables the graphic design of data extract, transformation, and loading scenarios.




                                                                 14   Deploying an Operational Business Intelligence Architecture
Non-DBMS, Business Format Transformation
Data in common e-business formats, such as EDI, SWIFT, and FIX must be transformed in
SQL-accessible data before SQL-based tools and applications can use it. WebFOCUS’ adapter
manager makes e-business data sources easily accessible for SQL-based tools and offers
integrated graphic tools for data inspection and metadata creation. WebFOCUS’ adapter
transformer enables business functions and source formats to be easily mapped as
XML schemas.

Application explorer is a graphic WebFOCUS tool that enables users to inspect WebFOCUS
packaged application, transaction, and e-business format sources.




 Application explorer is used to introspect applications and transaction systems.




                                                                 15    Information Builders
Once functions and source formats are mapped as XML schemas, application explorer enables
them to be published as Web services. Web services published using application explorer are
exposed as relational schemas to any application, end user, or WebFOCUS ETL process.




 Adapter transformer is used to graphically map and enrich messages for use as data.




                                                                16   Deploying an Operational Business Intelligence Architecture
Service Adapters Encapsulate Processes as Data Sources
In many cases, the data required by an end user or application is not stored as a unique entity
within a DBMS or file, but is instead the result of aggregating the results of many operations
performed in a specific sequence. For example, “customer” data, as needed by a customer
service representative, might mean the total business relationship a customer has with the
enterprise. To present such data, an application might contain many operations that access and
aggregate data from multiple sources. This assumes, of course, that the application being
written actually has access to all the necessary sources and the application implementer has the
know-how to manipulate such sources to produce the necessary data.

Creating and maintaining the code that generates this customer information might require
accessing specific business functions with SAP and Siebel applications, combined with a lookup
performed against a VSAM file, joined with specific data from an Oracle table. This would be
difficult code for even an application programmer to create, and certainly beyond the skills of
most end users. The WebFOCUS adapter manager enables complex business processes, such as
the given example, to be graphically defined and exposed as a service adapter. Service adapters
may then be reused by any application, tool, or user – saving programming time, eliminating
introduced errors, and reducing the cost of new application deployments.




                                                         17   Information Builders
Once defined as a service adapter, the entire process can also be published as a Web
service, then consumed and exposed as a relational data source through the WebFOCUS
metadata repository.




 Entire processes that gather and enrich data may be graphically defined, then published as service adapters – or
 Web services – for consumption by the WebFOCUS data server.




                                                                 18   Deploying an Operational Business Intelligence Architecture
Choose the Right Framework
for Operational Business Intelligence
    Improving business performance relies on better business information and its consistent
    application. With a business intelligence data integration framework that encompasses
    business data from its source through reconciliation and preparation for use, organizations
    can significantly improve the quality of their information and processes. Information Builders’
    WebFOCUS data integration framework underlies the BI systems of many of the world’s
    leading organizations, where improved business intelligence benefits the organizations’
    profitability, decreased costs, improved productivity, and enhanced market agility. For more
    information about how Information Builders’ WebFOCUS and its data integration framework
    can benefit your organization, visit www.informationbuilders.com.




                                                             19   Information Builders
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