Enterprise Data

What is Enterprise Data?

Enterprise Data is digital information that flows through a company's systems, including both structured data (such as spreadsheets and databases) and unstructured data (images, videos, graphics and is shared by the users of an organization, across departments and/or geographic regions.

Enterprise Data can be used to gain insights into operations, network security threats and risks, strategic initiatives such as sales reporting or customer relationship management (CRM), IoT sensor information, or weather trends. It is essential for businesses to understand their enterprise data in order to make informed decisions that will benefit their organization. Data modeling techniques are often used by enterprises when dealing with large amounts of enterprise data in order to make sense of it all more quickly and efficiently.

Enterprise data can have a significant impact on the financial well-being of an organization. Enterprises often implement security measures such as encryption technologies in order to protect their valuable enterprise data from potential threats like cyberattacks or accidental loss due to human error. Enterprise data loss can result in serious consequences such as loss of revenue, customer trust, or even legal action against the organization.

Characteristics of Enterprise Data

A key asset component, enterprise data is subdivided into internal and external data categories, which are classified according to organizational processes, resources, and/or standards.

There is no precise standard for what defines enterprise data from small or medium-sized businesses. However, once an organization gets to the point where it has many operating units in different locations, its needs clearly get more complicated as compared to the one-location business with a single IT department.

Enterprise Data characteristics include:

• Integration: Ensures a single consistent version of enterprise data for sharing throughout an organization
• Minimized redundancy, disparity, and errors: As enterprise data is shared by all of an organization's users, data redundancy and disparity must be minimized. Data modeling and management strategies are directed toward these requirements.
• Quality: To ensure data quality, enterprise data must follow organizational or other identified standards for varying internal and external data components.
• Scalability: Data must be scalable, flexible, and robust to meet different enterprise requirements.
• Security: Enterprise data must be secured via authorized and controlled access.

Types of Enterprise Data

To resolve data issues, it is important to understand different types of enterprise data. Its importance lies in the fact that these different types of data serve their specific purpose and there are different approaches to managing them. Another important reason to understand different types of Enterprise Data is that it helps in adopting a modular and agile approach to fix data issues.

• Master Data: It represents non-transactional information about business objects. It is a consistent and uniform set of identifiers that describe core entities of the business operations. Usually, master data defines unique entities in Products, Customers, Vendors, etc. domains. For example, a specific vendor which has a standardized definition and properties is a master data whose unique ID is used in transactional systems for business activities.
• Transactional Data: It describes core business activities and transactions. Transactional data may contain information about your procurement, production, selling, etc. activities. The description of a sale of a product is transactional data.
• Analytical Data: Analytical (or reporting) data is an aggregated compilation of transactional data which can be sliced and diced with the help of master data for business analysis.
• Reference Data: It is a standardized subset of master data which is less volatile than elements of master data. As the name suggests, it is used as a reference across the organization to maintain common standards. For example, a list of countries and corresponding states and cities is reference data.
• Metadata: It provides descriptive, structural information about other data related to business activities. For example, the Name of a person may have 3 components First Name (mandatory), Last Name (mandatory), and Middle Name (optional). This information is metadata about the name of a person.

See Also

Enterprise Data Integration (EDI)