Data is combined to form information about your organization’s past and current activities and allows leadership to make effective management decisions. In large enterprises, data related to mission critical processes and assets can be distributed across a multitude of integrated information systems. When using that data to make decisions and to drive other processes, and organization must have confidence in the quality and accuracy of that data. Our team focuses on three of the most important components of data:

• Data Management
• Data Governance
• Data Warehousing

Data Management

In today's technical environment, information systems and data creation and collection methods have grown up based on specific customer need. These needs are typically driven by unintegrated organizational issues - not guided by a comprehensive organizational data management strategy. The result is poor customer service, redundant "marketing" campaigns, inaccurate product shipments and, ultimately, a higher cost of doing business. Data management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise in order to more effectively manage and make use of an organization's enterprise data. It includes a variety of disciplines to include:

• Data analysis
• Database management system
• Data modeling
• Database administration
• Data warehousing
• Data movement
• Data mining
• Data quality assurance
• Data security
• Meta-data management (data repositories, and their management)
• Data architecture

Data Governance

Today, organizations are discovering that their success is increasingly tied to the quality of their information. Organizations rely on this data to make significant decisions that can affect supply chain efficiency, financial health, and regulatory compliance. As organizations collect more and more information about their customers, products, suppliers, inventory and finances, it becomes more difficult to accurately maintain that information in a usable, logical framework. Data governance, a relatively new component of data, is the establishment of necessary internal organizational structures, external stakeholder partnerships, processes, and procedures needed to optimize the capture and use of an organization's data. It enables the effective utilization of data to support an organization's bottom line. NovaTech is a leader in helping organizations apply a Data Maturity Model that aligns with their organizational goals, assess their current status relative to the model, and develop an evolutionary plan to govern this most critical enterprise resource.

Data Warehousing

To succeed in today's competitive, fast-paced business environment, it is imperative that the right content is aggregated and delivered to the right people at the critical moment when a decision must be executed. For many organizations, the most efficient and effective way to deliver this content is through the introduction of “Business Intelligence” (BI) or “Data Warehousing” (DW) solutions. In order to deliver these types of solutions, the goals should be accessibility and clarity—not flexibility. End users should not have to wonder how to find the information that they are looking for, and what the information they are looking at means. This focus is further heightened when new and less sophisticated delivery platforms are considered; for example, mobile devices are not equipped to handle large amounts of data manipulation, but are perfect to receive frequent updates of succinct business intelligence. With our unique combination of business and technology understanding, our business intelligence teams will help you:

• Pick the best delivery vehicle for your audience and your data
• Integrate the presentation layer
• Integrate the security layer
• Customize the presentation for target devices and user roles
• Target reports to users
• Use a combined push/pull model
• Keep information timely
• Take advantage of Enterprise Application Integration (EAI)