Technical Solutions
 Business Intelligence
  Quality Assurance / Testing

Scope: Assist client to plan and design enterprise data warehouse technical strategy and assist client to plan, design and implement a series of associated data marts. The primary issue was that compliance and trend reporting for trade activity was not servicing the broker community in a timely manner. The trading mechanisms were slowed down to unacceptable levels, resulting in lost revenues and inefficient information sharing across the enterprise. The overall solution had to be tightly coupled with the company’s on-line web strategy and capability. Data Warehouse size: One terabyte.
Results: Speed to market with technology that will drive a competitive advantage and reduce both cycle times and costs associated with legacy methods. Client’s IT organization was able to begin deployment faster and deploy with quality and confidence. The business is able to complete the compliance review process faster, with fewer resources. The business will be able to use new cross-selling and customer analysis information as a competitive advantage.

Scope: Assist client to plan, design, build, test and deploy a web based business intelligence system to transform high volumes of electronic funds transfer data into useful information.
Results: Enabling efficient Web based customer self serve. The client is now able to deliver important transaction information and analysis to its customers and partners faster, and at a lower cost than the legacy systems. Improved customer satisfaction and significant cost savings.

Scope: Plan, design, build, test and deploy a series of sales and financial data marts. The primary issue here was that multiple applications had been developed without reporting functionality. All new systems passed transactions to the legacy mainframe for financial calculation and posting to the General Ledger. Complex business logic was used to determine profitability at a branch level after all postings were committed; however, they could not determine their profit per transportation load. Data Warehouse size: ½ terabyte.
Results: The client is able to roll up critical financial and customer transaction information and information analysis capabilities, and place it in the hands of decision-makers across the enterprise. This enables faster and more accurate analysis on overall financials, and details like customer profitability, contract profitability, productivity and other KFM’s.

Scope: Plan, design, build, test and deploy a new high performance enterprise data warehouse. The primary issues were that their data warehouse did not contain enough of the data they needed, was not standardized and the response time was too slow. Several reports took more than 5 hours. Most reports took between 30 minutes and 1 hour against the largest fact of 24,000,000 records. Data Warehouse size: ½ terabyte.
Results: Data is pulled nightly from multiple source systems into the mart. Response time on all reports is under 2 minutes, with most reports running in under 1 minute. Eventually this mart will evolve into a Near Real Time system serving Operational Reporting, Historical Reporting and OLAP Analysis.

Scope: Plan, design, build, test and deploy a series of sales and customer related data marts. Because they had multiple silos of specialty areas selling products and services to common customers, cross selling and up selling of solutions was non-existent or negligible. Customers are spread across a variety of geographies making data sharing with existing customers impossible across these silos in the enterprise.
Results: Client customers can now be ‘intelligently’ serviced by fewer sales representatives, with a true customer record that reflects product purchase history and contracted service level agreements. Packaging of common service elements can be done across product contracts. Potential cross selling or up selling of products and services can be viewed through trend analysis and strategic delivery planning mechanisms by Sales, Marketing, Product Development and Service Delivery organizations. Increased product revenue through new product introduction will be realized, cost savings will be incurred through less account representation, and increases in services revenue are expected by expanding across logical sharing with other product offerings.