Data Management and Architecture
Successful data management requires much more than investment in technology—it also involves putting the processes and people in place to manage all aspects of the data lifecycle.
Thus, all three areas have an important role to play in how data is created, stored, moved, used and retired. Leading businesses are beginning to understand the importance of data management and architecture, which is vital to ensuring that the data needed for organizational decision making and reporting is available, accurate, complete and secure.
Most executives are constrained by information and data that are often insufficient or untrustworthy, or so copious that they require weeks to analyze. How often are you faced with the following situations?
- I receive numerous reports every day, but they all use different terminology and data formats—what does this all mean?
- I call them products, other people call them parts, one system calls them SKUs—and our customers call them by their catalog names and numbers—are they all the same thing?
- I just reviewed a data model of our business to prepare for an acquisition. It looked very nice but it used indecipherable terminology, a very old business model and had nothing to do with our current organization and strategy.
Effective data management enables insight to support better decision making, leading to compliance with government regulations; reduced risks inherent with improved data quality; improved productivity and operational efficiency; improvements in customer satisfaction; and increased enterprise agility, thus achieving high performance.
Surge’s Data Management & Architecture practice provides a structured, holistic approach that delivers offerings and assets to support our clients in managing their data. We structure data management & architecture into the following domains:
- Data Governance—The human organization to manage and oversee data.
- Data Structure—The definition of data.
- Data Architecture—The storage, movement and retrieval of data.
- Master Data Management—The maintenance of consistent core data throughout an enterprise and with business partners.
- Metadata—The management of data definitions and information about data.
- Data Quality—The accuracy, completeness and legal compliance of data.
- Data Security—The protection of data and the authorization to use it.
Surge’s team of data management & architecture professionals helps clients define and put into place the processes, people and technology to manage data effectively across its lifecycle. With deep expertise in the six key areas that enable effective data management, Surge Assembly combines an industry-specific focus with world-class data management capabilities to allow us to address the technical, as well as the functional, components that underpin all of our strategic solutions. We are able to deploy teams that are uniquely qualified to meet any data management challenge, in any sector, anywhere in the world.
Our services in Data Management & Architecture support the entire data lifecycle, including how data is created, stored, moved, used and retired. We integrate six capabilities into a master framework that leads to a structured data management approach across the enterprise. The six capabilities leverage a comprehensive set of assets including diagnostic and implementation tools, and design guidelines and best practices that reflect the best thinking in effective data management.
Our specific service areas include:
Data Governance includes the rules, policies, procedures, roles and responsibilities that guide overall management of an enterprise’s data.
Data Structure is how data is organized in a specific enterprise, from overall corporate data models down to the level of an individual system.
Data Architecture describes is the processes, systems and human organization required to store, access, move and organize the data.
Master data is the language of doing business, including core information on customers, employees and products.
Metadata is structured information about data that helps enterprise systems work together and makes them easier to maintain.
Data Quality is the ability of data to satisfy the organization’s requirements, typically measured in terms of the data’s accuracy, completeness and legal compliance.
Data Security is the protection of the data from unauthorized access, viewing, modification, or deletion, whether accidental, intentional or malicious.