Custom Data Warehousing Services

Put Your Valuable Business Information to Work for You

Transform data into an intelligence infrastructure that delivers integrated, real-time insights that enable your workforce to make critical business decisions. With Xtivia's custom data warehousing (DW) services, you will be able to

• Identify business requirements that are critical to run your business more effectively
• Translate these business requirements into system requirements and corresponding best of the breed architecture (Xtivia strongly recommends RAPID DW)
• Key business resources, including people and infrastructure, are identified and put to the most efficient use
• Technology required for end-to-end implementations of your DW solution, including database platforms, ETL platforms, and all associated processes will be decided with your input
• Implementation of these platforms, along with all the processes
• Leverage years of industry experience from Xtivia and industry leading talent

Scenarios

You may face a variety of challenges including:

• Executives who need a snapshot of business performance at their fingertips
• Business managers who want to change the way they access data
• Power users who are pushing the system to produce more data presented in different ways
• Employees who want to better understand the information presented to them
• Compliance and regulatory issues that must be addressed efficiently
• Fewer resources that require doing more with less
• Disparate data assets that are difficult to manage and access
• Unstructured data that is currently providing little or no value to business performance

Services We Provide

• Project Sponsorship: Receive expert help on setting up the proper foundation for your project sponsorship and information steward organization
• Project Management: Best practices help in managing the DW program and project. Our resources have a number of years of experience and numerous successful implementations under their belts
• Requirements Analysis: Translate business requirements into system requirements and actionable project/program plans
• Architecture Design: Xtivia strongly recommends RAPID DW architecture, having done several successful implementations to date
• Development: Xtivia can provide resources to augment your team or build an effective implementation team
• QA Testing: Provide appropriate resources with years of experience in quality assurance in DW implementations

Our Take on Data Warehousing

Data warehousing as a concept has been around for over 20 years. The concept keeps evolving, changing everyday. Data warehouses are now used for a variety of purposes from day-to-day operational reporting to predictive analytics.

Newer technologies keep emerging -- computing technology keeps getting better. Vendors keep advertising benchmarks for faster, bigger DW technologies. You will also hear several terms like data marts, operational data stored, or DW appliances used quite frequently. There is a sea of information out there and navigating through the information may be a daunting task.

Hybrid Architecture for Your Unique Business

Each organization is unique in terms of its requirements for a data warehouse. The needs of your organization may require a hybrid architecture that implements key concepts from both architectures.

Top Down Implementation Approach

Start with an enterprise model and architecture and through phased implementation construct an enterprise-wide data warehouse.

Bottom Up Implementation Approach

Start with a subject area and build incrementally keeping a standardized conform layer.

Common Data Warehousing Mistakes We Will Help You Avoid

• Lack of executive sponsorship and active business involvement
• Assuming the data exists and the data quality is fine
• Presentation layer complexity not aligned with end user skill sets
• Slow response times
• Too many, too few, or the wrong business intelligence software tools
• Going it alone, without the right kind of expertise
• Underestimating the effort needed to operate and maintain the DW
• Inflexible (neither scalable nor extensible) design
• Modeling the DW to reflect the source data rather than the business
• Not solving a business problem