Enterprise Data Management
AVATAR has developed a comprehensive suite of tools for superior business data management. Our digital marketing asset management, content management solutions, product information management platforms, and ERP integration services run the gamut of effective, efficient, and secure.
But what about your business process data, project management workflows, or raw data? We've got covered too. Find out here:
Data Architecture
AVATAR will help you evaluate your data management needs and build a road map.
Source
Where is the data coming from? This answer is not always that simple. Sometimes it is from a single, manual source and other times (as is the case frequently with product information management) it needs to come from multiple, desperate systems.
Use
Who needs to use this data and how? Understanding the business is also about understanding the people that make that business run!
Externalization
Where is the data being used outside of the organization? How can you effectively support third parties that use your data – vendors, distributors, sales teams, resellers, e-commerce, catalogs, mobile apps, etc.?
Automation
What processes are labor intensive or demand automated features to process data, calculate, or audit using defined business logic?
Using that roadmap, AVATAR will work with you to design a solution that can help you keep your data secure and useful.
Product Information Management
Digital Asset and Media Management
Project Management Suite
Data management is the development and execution of architectures, policies, practices and procedures in order to manage the information lifecycle needs of an enterprise in an effective manner.
Data life cycle management (DLM) is a policy-based approach to managing the flow of an information system's data throughout its life cycle: from creation and initial storage to the time when it becomes obsolete and is deleted. Several vendors offer DLM products but effective data management involves well-thought-out procedures and adherence to best practices as well as applications.
There are various approaches to data management. Master data management (MDM), for example, is a comprehensive method of enabling an enterprise to link all of its critical data to one file, called a master file, that provides a common point of reference.
The effective management of corporate data has grown in importance as businesses are subject to an increasing number of compliance regulations. Furthermore, the sheer volume of data that must be managed by organizations has increased so markedly that it is sometimes referred to as big data.
Stewardship
use of business data in and between transactional and operational business applications
Analysis
discovering useful information, suggesting conclusions, and supporting decision-making
Ubiquity
Consistency across systems is achieved through integration and system awareness.
Modeling
Concept and abstraction assist in the design of systems as well as the management.