Enterprise data refers to data shared by employees and their partners in an organization, across various departments and different locations, spread across different continents. This is data that is valuable to the enterprise, such as financial data, business data, employee personal data, and so on, and the enterprise spends considerable time and money to keep this data secure and clean in all aspects.
During all this, this so-called enterprise data passes the current state and becomes stale, or rather dead, and lives in some form of storage, which is hard to analyze and retrieve. This is where the significance of this data and having a single place to analyze it in order to discover various future business opportunities leads to the implementation of a Data lake.
Enterprise data falls into three major high-level categories, as detailed next:
- Master data refers to the data that details the main entities within an enterprise. Looking at the master data, one can, in fact, find the business that the enterprise is involved in. This data is usually managed and owned by different departments. The other categories of data, as follows, need the master data to make meaningful values of them.
- Transaction data refers to the data that various applications (internal and external) produce while transacting various business processes within an enterprise. This also includes people-related data, which, in a way, doesn’t categorize itself as business data but is significant. This data, when analyzed, can give businesses many optimization techniques to be employed. This data also depends and often refers to the master data.
- Analytic data refers to data that is actually derived from the preceding two kinds of enterprise data. This data gives enough insight into various entities (master data) in the enterprise and can also combine with transaction data to make positive recommendations, which can be implemented by the enterprise, after performing the necessary due diligence.
The previously explained different types of enterprise data are very significant to the enterprise, because of which most enterprises have a process for the management of these types of data, commonly known as enterprise data management. This aspect is explained in more detail in the following section.
The following diagram shows the various enterprise data types available and how they interact with each other:
Figure 02: Different types of Enterprise Data
The preceding figure shows that master data is being utilized by both transaction and analytic data. Analytic data also depends on transaction data for deriving meaningful insights as needed by users who use these data for various clients.
