Big Data is defined by the volume and speed at which data is collected by companies today, from multiple structured and unstructure sources, in real time. Keeping this data timely, integrated, and secure in a centralized location for reporting and analysis is critical to exploiting Big Data
The integration of such disparate data can be a complex and often daunting task. Data integration is fundamental to enterprise information management and other data warehousing initiatives. An effective data integration strategy, architecture, and supporting infrastructure and processes are vital components in the delivery of business intelligence solutions. While Extraction, Transformation & Load (ETL) is still a commonly used technique for data warehouse focused data integration, the evolution of technology coupled with the increasing sophistication of data consumers has driven the increasingly complex nature of data integration. Demand for “real-time” data increases the pressure on a data integration infrastructure, while scorecards and dashboards increase the expectation of seamless visibility into data. As the capabilities of technical infrastructure have increased, initiatives like Enterprise Information Integration (EII), Enterprise Application Integration (EAI), Master Data Management (MDM), and Product/Customer Data Integration (PDI/CDI) are viable components of robust Enterprise Information Management (EIM).
Edgewater’s EIM Practice provides expertise spanning the continuum of data integration:
Data Integration Assessments and Strategies
As organizations move into the world of more complex data integration, they are often uncertain as to whether their current platform is sufficient to address current and future demand. Additionally, organizations embarking on their initial journey into centralized data environments are unsure of what investments need to be made. Edgewater conducts assessments of current environments against the required long-term capabilities to determine if the current platform can meet the ever increasing complexity of an organizations Big Data requirements. Additionally, Edgewater can assist organizations in developing an overall, long-term data integration strategy and roadmap.
Data Integration Architecture
Understanding the various architectural options and determining which are appropriate for an organization’s unique data needs requires deep expertise and experience. Edgewater’s experience understanding of the demands of Big Data, and the various data integration architectures can provide an organization with the necessary insights, best practices and real-world experience in establishing the appropriate data architecture.
Data Integration Implementation Services
The implementation of data integration platforms can be complex and time-consuming. Integrating data quality processing, master data management constructs, and simply dealing with the multitude of data sources can leave organizations wondering if they are implementing all the required components of a true, world class data integration platform. Edgewater’s extensive experience and best practices in data integration provides a sense of confidence that they are moving towards the right goal.