-- Integration modeling, data warehousing, data strategy
System Innovationsemail: email@example.com
Laura Brown – principal consultant
1112 Riverbend Club Drive - Atlanta, GA 30339
PHONE: 770-953-0534 FAX: 770-952-7863
Managing Your Data, On and Off the Net
From the initial customer contact to
the acceptance of customer payment, at the heart of every business
transaction is the creation, capture, or exchange of information. Managing
such information is the focus of data strategy, warehousing, and
architecture efforts. The data that business events revolve around is the
currency of information systems. Ensuring that it is current, well
integrated, and sharable between business applications is the job of data
The Cycle of Data Management
A day in the life of a piece of corporate data will see that data move
through many different perspectives of use and handling. First, the data
is captured, and then checked for errors in entry, format, and other
attributes according to its validation rules. Next, it travels to the
systems that utilize the data for primary business contact, processing
transactions, and supporting primary business functions, such as sales,
order-fulfillment, and services. After being cleaned up for corporate
standards, the data moves on to be shared with other systems that need it
to complete their picture of the company's business, and is manipulated
and stored in decision-support holding areas. Finally, the data is
distributed for selective viewing of both company insiders and external
users, such as customers and suppliers.
Data management needs to recognize the cycle around which data
stewardship revolves. At each step of the process, different priorities
will surface. They will require different technical design and development
approaches employing defined terms and agreed-upon structures. Figure 1
shows the steps of the cycle and some of the supporting technical
structures. It adopts a starting point where customer and supplier
interactions initiate business transactions that must be processed. Keep
in mind that although it's a common starting point, it is a little
arbitrary because activities in any step of this model can act as a
The Cycle of Data Management depicts how data is utilized at each step
of the process.
The following are the steps of the Cycle of Data Management:
1. Process business transactions.
2. Transform data for sharing.
3. Support business decisions.
4. Create internal portals.
5. Create external portals.
6. Interact with customers and suppliers.
- Process Business Transactions
Business events, such as a customer contact resulting in a sales order
being placed, or a customer request that is filled by customer service
personnel, produce data that must be managed. They involve relatively
small amounts of data that must be maintained with a high level of
accuracy at the time of the transaction and access of the data. Business
transactions are typically simple transactions involving very detailed
data. For example, a customer order includes specific mailing address,
product information, and pricing details.
The systems that support such business transactions must handle many
simultaneous updates, reads, and insertions of data. They must often be
available for processing on a continual basis, 24 hours a day, 7 days a
week. They have low requirements for storage of historical information,
usually needing only that information required for supporting the flow of
The data model for supporting business transactions is usually highly
normalized, which means that data components are structured so that they
are stored only once for convenient control of updates. The data model
also attempts to achieve a balance between design for state modification
(insert, update, delete) and speed of retrieval or data access. Because
the data usage is predictable, the data model can be optimized for these
Data management in business transactions usually prioritizes data
persistency and state management. It will be utilized by down-stream
systems (subscribers to the information) that are usually unrelated to the
systems producing the data.
- Transform Data for Sharing
The data produced in business transactions must often be transformed
before being shared with other applications. Sometimes sensitive or
irrelevant information must be removed before sharing. At other times,
information must be made generic so that it matches the definitions of
other application views. Some data will be summarized and used to support
analytical processing or decision support. Other information will be used
internally by other departments such as operations or financial reporting,
whereas some data is selected for sharing with customers and suppliers,
depending on the requirements of their interactions with the company.
Data extraction, transformation, and middleware tools are all means of
transforming data to make is suitable for sharing. Extraction and
transformation tools usually help to convert, cleanse, and standardize
data. Middleware and messaging technologies facilitate the physical
aspects of sharing data, through the use of data delivery mechanisms and
subscription maintenance machinery.
The priorities at this stage are for credible data, verified, cleansed,
and transformed in a streamlined process. Speed of data availability for
sharing with mission-critical applications is also an important factor. In
some cases, speed of data availability is considered more important than
one hundred-percent accuracy of the data. For example, data that is
summarized and used for forecasting might be accurate to within a
five-percent margin of error, a margin that would not be acceptable for
the processing of business transactions.
- Support Business Decisions
The data that is delivered to decision-support applications is used to
help companies measure performance, manipulate revenue, yield ratios, make
market decisions, and monitor operational statistics. It is earmarked for
business management and strategic functions, and used in determining
competitive advantage. It can be used to identify opportunities for
improvement and growth of the company.
Decision-support data is often derived through summarization and
calculations applied to detailed data taken from transaction processing
systems. It often involves large volumes of data, with significant amounts
of historical data used for trend analysis and reporting of regulatory and
markets information. Analytical processing usually involves complex
transactions or queries against the data, utilized in unpredictable ways
by processes characterized by discovery. A fairly small user community
(managers, executives, and analysts) needs actual access to the data.
Data models for analytical processing are optimized for rapid access
through non-repetitive queries, producing unpredictable workloads. The
priority is on efficient data retrieval, which requires that data be
heavily indexed and de-normalized (more than one copy of a data component
stored) for convenient access rather than normalized for convenient
update. Integrity constraints, such as those utilized for transaction
processing (primary keys, foreign keys, and column constraints), are
generally relaxed in decision-support systems because the source systems
can be expected to enforce the referential integrity that is required.
4. Create Internal Portals
Internal portals allow parties within a company to access data
according to the needs of their particular business or application
viewpoint. Data warehouses spawn data marts, which house
application-specific views of data replicated from the central repository.
Intranet portals provide windows on data that can be needed by operational
personnel or marketing analysts.
Internal portals represent multiple views against the company's
information and are generally accessed with low security requirements,
within the confines of a company firewall.
5. Create External Portals
External portals provide access to customers and suppliers for
carefully selected portions of a company's information. Portions of the
business process in which customers or suppliers participate can be
detailed on public Web sites. Financial performance can be provided in
annual reports online or investor information packets. Product and service
specifications and pricing can also be made available through an external
portal on company information.
Characterized by selective viewing, external portals usually reside
outside a company's firewall, providing a highly secured environment for
customer and supplier interactions.
6. Interact with Customers and Suppliers
Interactions with customers and suppliers can occur through the window
of an external portal, or they can be facilitated by business transaction
processing systems. Sometimes they occur with replicated versions of
company data, carried by a sales or marketing representative in a remote
device such as a laptop computer configured to provide price quotes and
Distribution of data becomes important in the interaction step, with an
emphasis on convenient access and accuracy to certain limits established
within a window of time. Partitioning and data replication are schemes
that provide the desired distributed deployment of components of data.
Beyond Data Management
Beyond the stewardship and management of data as an asset, other
disciplines combine to forge corporate information into valuable business
intelligence. Data warehousing converges with business process
re-engineering and Internet disciplines to deliver an enterprise-wide data
strategy. The successful data warehouse often drives the reengineering of
business data and processes by surfacing the contradictions and confusion
in current application systems. Once information is verified, organized,
and available, Internet technologies are utilized both internally and
externally to provide increasingly important data portals, which act as
windows on the world of business information.
(Reprint of an article by Laura Brown, first published on InformIT's guest expert
page. For more information, contact firstname.lastname@example.org.
All rights reserved.)
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- Copyright 1998,
1999, 2000. Laura Brown,
LBPI, Inc. (DBA: System Innovations)
- Last Updated: September 18, 2001