Data Architecture & Management Services

Data architecture defines how data is stored, managed, and used in a system. It establishes common guidelines for data operations that make it possible to predict, model, gauge, and control the flow of data in an enterprise. This is even more important when system components are developed by or acquired from different contractors or vendors.

Data Management Strategy and Implementation

An effective data management strategy helps align the organization with the business strategy and provides improved communication and data access. Data management is the ongoing process of managing and facilitating access to data in order to provide information consumers with timely access to the data they need. A comprehensive data management program requires:

• Consistent and automated enforcement of data naming conventions and standards
• Governance to protect the quality and integrity of shared data
• Integrated and managed metadata that enables a broad range of capabilities from business self-service to code reuse
• Accountability for ongoing stewardship

Meta-Data Repository Analysis, Design and Implementation

Well-managed master data - typically consisting of hundreds of categories, including customers, products, suppliers, key performance indicators, etc. - provides the consistent information framework that enables enterprises to remain agile, operate effectively and accurately measure performance.

Unfortunately, many organizations struggle to reconcile master data from across the enterprise, particularly as it is duplicated and maintained in multiple systems. As a result, it often conflicts, and there are inadequate solutions in place to validate its integrity as it changes over time. The problem is especially acute in global businesses with a history of mergers or with independent units operating under different cultures and regulatory structures. Therefore, organizations regularly miss major opportunities and make costly errors throughout the business.

The ideal master data management (MDM) solution can harmonize, store and manage master data over time. By enabling business people to collaboratively manage and control master data in a workflow-driven environment, robust master data management solutions increase the consistency and accuracy of corporate performance reporting and operations, including manufacturing, finance, marketing and customer service.

Enterprise Data and Business Process Modeling

The use of models helps organizations visualize and communicate the rules a business enforces on its data and business processes. Modeling helps organizations by enabling them to analyze, document, communicate, and implement the designs of enterprise-scale database applications. Modeling clarifies complex data design problems through visually clear 'blueprints', documents the databases, data warehouses and virtually any database driven application and assists the enterprise understand more about its own data. Wiltech Systems Group can help you to build quality into your designs and the databases by enforcing sound database and business process design principles. We are well versed in several modeling techniques ranging from relational/ dimensional best practices, Federal Enterprise Architecture data reference models (FEA DRM) to UML (Unified Modeling Language) and Object-Oriented Design (OOD) techniques.

Database Administration and Performance Tuning Support

Every organization using a database management system (DBMS) to manage data requires a team of database administrators to ensure the effective use and deployment of the company's databases. Due to the volume of data residing in most organization's DBMS, the need for skilled database administrators (DBA) is greater today than ever before. We offer DBA support for a variety of commercially available DBMS such as Oracle, DB2/UDB, SQL Server, MySQL, Lotus Notes and Access.

Data Warehouse Analysis, Design and Implementation

Data warehouses are often at the heart of the strategic reporting systems used to help manage and control the business. The function of the data warehouse is to consolidate and reconcile information from across disparate business units and IT systems and provide a context for reporting on and analyzing:

• Corporate performance management
• Profitability
• Consolidated financials
• Compliance

As strategic as they are, enterprise data warehousing projects are highly complex and can be risky. Projects fail almost as much as they succeed, often because of long development cycles, poor information quality and an inability to adapt quickly to changing business conditions or requirements.

The purpose of the consulting services is to help organizations keep the probability of success in their favor by staying abreast with the latest technology and best-practices topics, including:

• Data integration and reconciliation
• Data quality and master data management (MDM)
• Iterative delivery
• "Packaged" data warehousing applications
• Data warehouse performance
• Deployment and change management