Organizational must treat data as a valuable business asset. To achieve the most from your data, you must employ a minimum of 4 systems, including a Systems of Record, Systems of Engagement, Systems of Automation, and Systems of design. We’ll focus on Systems of Record, Engagement, and Design in the next few posts. Policies must evolve to catch up with the current digital business, including new criteria policies and procedures. Intelligent data governance begins with clearly defined data policies, standards, and procedures.
For instance, organizations typically have policies, standards, and procedures for information security, privacy, data retention, and records management, but specifying these and other critical policies, standards, and procedures are only the beginning point for an effective data governance program.
Organizations create rules for paper records or electronic PDF documents, challenging to implement with physical documents. For example, a policy for retaining invoices might define the required retention period and process for keeping invoices, but manually implementing and enforcing paper-based policies, standards, and procedures is impractical.
Too often, an organization’s policies don’t evolve with technology. Digital asset management requires a software-based policy engine that allows organizations to automate, implement, and enforce sophisticated policies, criteria, and procedures with today’s live data systems.
Unstructured data and its growth represent a unique data management problem requiring an advanced Data Governance system.
Industry experts predict massive and endless data storage increases. Yet IT budgets worldwide expect only marginal gains. Enterprise IT organizations are looking for ways to effectively manage and secure sensitive documents and big data into the future. These organizations are searching for ways to cost-effectively archive and manage the flood of unstructured information types to derive valuable business information and insights.
More and more IT leaders view object storage as the perfect technology solution for data governance. Object storage is a data storage structure that handles data as variable-sized containers (called objects) organized into a flat address space instead of more complicated hierarchical files or blocks. Objects can contain both user and system-generated metadata to enhance the data and its governance.
Among the most significant advantages of object storage is that it brings structure to unstructured information, such as sound, video, pictures, and documents. The extensive and customizable metadata provides the structure to describe the file, what it contains, and its value to the business, without needing to open the document. This metadata space on the object is where access, retention, preservation, mobility, and other policies are applied and enforced.
The complexity of governing unstructured information stems from its variety and its difference from data found in a conventional database. Object storage makes it easier to store, protect, secure, manage, synchronize, synchronize, share, research, and examine all data, such as unstructured data. Although use cases change, object storage is particularly critical for organizations in highly litigious environments. Compliance with regulations requires these organizations to store and organize large volumes of data. These volumes overwhelm the capabilities of legacy storage systems and conventional transaction-based technology architectures. Fortunately, object storage architectures were designed with this fact in your mind, becoming the data reservoir for organizational data being managed and controlled for extended periods without suffering loss or corruption.
For data to provide management with actionable insights, we must ensure its integrity. We’ll look at data quality in our next post.