There is an information evolution happening in the data warehouse
environment today. Changing business requirements have placed
demands on data warehousing technology to do more things faster. Data
warehouses have moved from back room strategic decision support
systems to operational, business-critical components of the enterprise. As
your company evolves in its use of the data warehouse, what you need
from the data warehouse evolves too.
Stage 1 - Reporting:
a single source of truth to drive decision-making across functional and/or
product boundaries. Questions are usually known in advance, such as a
weekly sales report.
Stage 2 - Analyzing:
Focus on why something happened, such as why
sales went down or discovering patterns in customer buying habits. Users
perform ad hoc analysis, slicing and dicing the data at a detail level, and
questions are not known in advance.
Stage 3 - Predicting:
Sophisticated analysts heavily utilize the system to
leverage information to predict what will happen next in the business to
proactively manage the organization’s strategy. This stage requires data
mining tools and building predictive models using historical detail. As an
example, users can model customer demographics for target marketing.
Stage 4 - Operationalizing:
Providing access to information for
immediate decision-making in the field enters the realm of Active Data
Warehousing. Stages 1 to 3 focus on
strategic decision-making within
an organization. Stage 4 focuses on
tactical decision support. Tactical
decision support is not focused on developing corporate strategy, but
rather on supporting the people in the field who execute it. Examples: 1)
Inventory management with just-in-time replenishment, 2) Scheduling and
routing for package delivery, 3) Altering a campaign based on current
results.
Stage 5 - Active Warehousing:
The larger the role an ADW plays in the
operational aspects of decision support, the more incentive the business
has to automate the decision processes. You can automate decisionmaking
when a customer interacts with a web site. Interactive customer
relationship management (CRM) on a web site or at an ATM is about
making decisions to optimize the customer relationship through
individualized product offers, pricing, content delivery and so on. As
technology evolves, more and more decisions become executed with
event-driven triggers to initiate fully automated decision processes.
Example: Determine the best offer for a specific customer based on a realtime
event, such as a significant ATM deposit.
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