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Data Management

EII’s Data Management practice has a proven history of innovation and customer success. EII is widely recognized as a thought leader in using Solution Architectures to define and manage data integration requirements, and in using the most advanced tools to complete a highly-structured data quality methodology. The end result? Data management that aligns with business priorities, whether they be regulatory compliance, data quality for execution, or data harmonization for business intelligence and reporting. We pull data from disparate sources and align it with our clients’ business processes so executives have the necessary visibility to effect end-to-end organizational management. Our end-to-end methodology is called Architecture-Driven Data Management. EII provides strategic as well as technical data integration services to help customers fulfill their data management objectives.

Architecture-Driven Data Management

The keystone to EII’s data architecture approach is the belief that business processes drive data integration requirements, not the reverse. EII models business processes in a Solution Architecture, vets those processes with subject matter experts, and uses those processes to determine functional specifications suitable for passing on to developers.

Managers need accurate and timely information, and to make sure they get it, EII converts complex data integration methodologies into solution packages managers can trust to meet their requirements. Our specific technical capabilities in this area include:

Data Migration / ETL / Data Quality. EII believes that any enterprise integration project should have data quality "baked in" from the start. Our consultants have extensive experience with Extract, Transform, and Load tools and have deep knowledge in migrating data to ERP and other enterprise systems.

Master Data Management. EII views Master Data Management as both a technical as well as a business process solution – ETL and other technologies can move master data between systems, but organizations need business processes to manage and control master data changes. Most data migration and integration projects touch master data, and Master Data Management is a key component of an Enterprise Data Management strategy. EII’s approach to Master Data Management is to leverage business process models to define Master Data Management roles, permissions, and workflow. This takes the emotion out of decisions around Master Data roles by providing a quantifiable assessment of how and where master data is used within the enterprise.

Next-Generation Data Warehousing. Current generation data warehouses are difficult to change and expensive to maintain. Solution Architectures containing business processes, organizations, and data provide the inputs for next-generation data warehousing.  EII designs and builds next-generation Data Warehouses that are faster and are more adaptable, flexible, and ultimately more affordable than traditional approaches. Our modern approaches accelerate data warehouse design and implementation. In addition, we partner with software providers that have proven track records of implementing in record time while leaving behind solutions that are sufficiently flexible to allow rapid change in the management processes that must be supported by the implemented data warehouse.

Data Management Strategy and Planning

Data Management efforts require strategy and planning to be successful – issues of data management roles and governance become critical when data is consolidated into a single system from disparate stovepipes. EII’s core strategy and planning capabilities include:

Data Governance. When enterprise data is put in enterprise systems from legacy stovepipes, issues arise as to who owns and can change enterprise master data. Data governance – establishing data management roles, permissions, and management processes – is essential in order to manage master data, automate data cleansing, and migrate data to an enterprise system. EII’s Architecture-Driven Data Integration methodology helps establish data governance by showing the as-is and to-be in terms of the how, what, and where of business processes interacting with data.

Data Lifecycle Management. EII helps customers understand their overall data life cycle, from the creation of master and transactional data in a set of business processes and the consumption of that data in different processes. A Data Lifecycle Management Plan outlines organizational and individual data management roles and responsibilities and a management plan for establishing data governance.

Enterprise Information Management

EII’s approach to Enterprise Information Management is more than just using a particular technology (in this case EII or other federated query technologies,) but rather has multiple aspects, with EII currently helping our customers with:

Comprehensive Data Architecture. EII is helping its customers define their Enterprise Data Architecture, taking their business process architectures and integrating both logical and physical data architectures. This is essential to understanding the one-to-many relationships between a single logical data element and the multiple manifestations of this data element in physical systems, and leads to an understanding of data lineage. The overall objective is to ensure authoritative sourcing, provide the framework for data governance, simplify your physical data architecture, and inventory the enterprise’s data assets.

Unstructured and Structured Data Management. EII’s customers have large repositories of unstructured data that become structured through product engineering and procurement activities. They also have data quality issues in structured data that can benefit from the analysis of this data.

Product Data Standards. EII is helping its customers work with industry and international standards for the maintenance and exchange of engineering and product data, to lower long-term integration costs and improve data quality across their supply chain.

Bottom Line

EII is an innovator in data management, and has the thought leadership and project experience to back it up. We are a recognized leader in leveraging new data management technologies to address our clients' needs, and partner with other leaders such as IBM to deliver a complete set of Data Management services that provide unparalleled value to our clients. Data integration is our core competency and we take pride in the success of our customers as they derive value from the solutions that we design and implement.

Data Management Support for the U.S. Army Logistics Support Activity (LOGSA)

EII is a member of the IBM Team on the new LOGSA LITeS project, which provides comprehensive information technology support to support Army Logistics. EII’s role on the project is data management support by helping LOGSA optimize its investment in the InfoSphere Data Integration Platform.

In this new role, EII will be tightly integrated with the IBM team, adhering to all IBM ethical, environmental, and technical requirements. The IBM requirements  align with EII’s approach to providing trusted customer support in the delivery of quality solutions.

This project aligns perfectly with EII’s focus on providing best practice data integration solutions.