Managing the data that you produce, consume and process is crucial to your business success. The data that you create, send and receive needs to be accurate, safe and ready for use. Creating a framework for data management and then maintaining it can be a daunting task. At Symbolic, we work with clients to ensure that their data management goals are achieved from data strategy to implementation to maintenance.
Data Governance – Our professionals can work with you to create a framework of roles and responsibilities shared by the business and data professionals to obtain formalized guidance and behavior over the definition, production, quality, and usability of information and information-related assets. Implementing a data governance framework is the first step in an overall data management strategy.
Data Architecture, Analysis & Design – Symbolic takes a holistic data approach when developing solutions for data management. We use best practice data methodologies and appropriate data technologies to ensure that the redesigned solution is delivering the right data to right level of the enterprise effectively and efficiently. This includes enterprise data modeling, function/data analysis, logical data modeling, and model management.
Data Quality – Symbolic uses the Total Data Quality Management methodology developed at M.I.T. to improve data quality and ensures that our clients: (1) users (customers) of data are involved in improving data quality, (2) predetermined requirements for excellence are defined in terms of measurable data characteristics, and (3) data conforms to these requirements. Our rigorous methodology ensures that your data quality maintains its integrity through its lifetime.
Data Integration – Aligning, reconciling and coordinating your data across systems, components, and data sources will help you achieve your IT goals. Symbolic works with clients to synchronize and integrate data, our work includes data definition normalization, data semantic mapping, and the formation and operation of data communities of interest.
MetaData Management – Managing all of your data requires a strategy that includes the development and execution of programs and policies for the discovery, vetting, housing, sustaining, and distribution of the characteristics of the data utilized by the enterprise. Symbolic can help you develop and implement a comprehensive metadata management strategy.
Data Interoperability – Your systems need to be able to exchange information and to use the information that has been exchanged. This goes beyond the mechanics of data sharing to a focus on preserving the accuracy, integrity and appropriate use of the data exchanged. Symbolic can help you design a data interoperability strategy that lets you put all of your data to work.