Data Centers

Resources for designing, planning, and implementing a data warehouse strategy

The analytical components inherent in a data warehouse allow users to consider the possibilities of future actions based on complex relationships discovered by merging data collected from throughout the organization.

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.

About

Mark Kaelin is a CBS Interactive Senior Editor for TechRepublic. He is the host for the Microsoft Windows and Office blog, the Google in the Enterprise blog, the Five Apps blog and the Big Data Analytics blog.

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