No matter the size of your business operation, it is
generating data with each and every transaction. More likely than not, that
data is being collected in some form of operational database. Perhaps your
enterprise has several operational databases separated by departments, areas of
responsibility, and possibly physical distance. Bringing these varied bits of
data together into one analytical data warehouse will give decision makers in
your organization a distinct competitive advantage—but only if implemented
properly.

By design, data warehouses are optimized to address queries
that involve the “what if” questions so often asked by decision
makers composing strategic initiatives. The analytical components inherent in a
data warehouse allow users to consider the possibilities of future actions
based on complex relationships discovered by the merging of data collected from
throughout the organization. Implemented carefully, the data warehouse can be a
powerful strategic tool.

Initial planning

TechRepublic has numerous resources to help IT professionals
and DBAs successfully plan and implement a data warehousing system for their
enterprise. The first steps for any major system rollout such as this is to
define the significant parameters and convince the decision makers of the
benefits:

  • TechRepublic
    Tutorial: Data warehousing defined

    Making a business decision using data from several different enterprise
    databases can be complicated. Data warehouses consolidate data into a
    central repository and give you the online analytical processing (OLAP)
    tools necessary to retrieve data pertinent to the solution.
  • Beginning
    and planning your data-warehousing project

    Determine what a data warehouse will accomplish for your enterprise before
    implementation.
  • Making
    the operational case for data warehousing

    The executive mindset of ROI-as-decision-driver isn’t going to work when
    you present the plan for implementing a data warehouse. Learn how to sell
    decision makers on the idea.
  • Hands-on
    tasks in building a data warehouse

    Create a storage system that consolidates vast amounts of relevant data
    and stores it in such a way as to maximize its convertibility into useful
    information. This point is key: In a
    conventional operational system, applications turn data into information;
    in a data warehouse, data is converted into useful information at the time
    it is stored.

Implementation

After planning and selling a data warehousing system, you
will have to put the parts together. TechRepublic has several resources to help
you with this phase:

White paper resources

TechRepublic also has white paper resources focusing on data
warehousing as a strategic solution. These resources range from product
overviews to detailed case studies:

  • United States Securities and Exchange Commission–Data
    Warehouse

    Sybase Business Challenge: A completely new site would have to be
    designed, developed, and implemented to manage the new disaster recovery
    architecture and be able to process large amounts of data and increase the
    performance to benefit the end user. Solution:
    A flexible, scalable, and reliable data-rich warehouse producing faster
    load times, faster query results, and more comprehensive information views—all
    at a lower cost.
  • DB2 Universal Database and the architectural imperatives for
    data warehousing

    IBM – These architectural
    imperatives address basic challenges with regard to database portability,
    scalability, flexibility, and extensibility. Each requires fundamental
    choices in striking a balance among competing dynamics.
  • Delivering a fail-safe data warehousing platform
    Computacenter – Organizations
    today depend on seamless access to corporate information resources for
    effective business decision-making. However, for the IT function,
    effectively managing the sheer volume of data generated by the
    organization every day is proving an uphill struggle. Many companies face
    mounting costs and complexity ensuring the availability, security and
    backup of data held in multiple sources (and often disparate systems)
    across the enterprise.
  • Data Warehousing & BI for the Small to Midsize Business
    Cirista – The Small to Midsize
    Businesses (SMB) cannot approach Business Intelligence (BI) in the same
    manner as a Fortune 1000 company does. They have neither the IT staff nor
    the funds that a big company has to support an ongoing traditional BI
    initiative. More importantly, they need to be more capable in their use of
    data to compete. With the Cirista approach, the small to midsize business
    can employ a powerful BI solution without making large investments in
    software and more importantly IT staffing.

Quality data

Good strategic management decisions require quality,
pertinent information derived from the best data available. A data warehouse
system could be the best way to collect, store and interpret the plethora of
data flowing through an enterprise. However, such a sophisticated system must
be implemented with careful planning and a thorough understanding of how the
intricate pieces of a data warehouse fit together.