These datasets offer a high-level understanding of the elements involved, allowing for more effective interpretation and guidance. In these dictionaries, we can find names, settings, and any other important attributes of data assets found in specific databases or data pipelines. These are stored as repositories and serve to support data engineering operations.
#Data inventory definition manual
The most efficient way to do this is either by automation or by maintaining a continuously updated data inventory (such as the one Satori creates).įor examples and further references, read our guide to creating manual and automated data inventories in Snowflake.ĭata dictionaries outline information about naming and defining data assets. Therefore, you need an agile system to create and maintain your data inventory. The primary challenge in creating a data inventory is keeping it current. By implication, this requires a detailed and up-to-date data inventory. Most regulations detailing privacy policy guidelines, such as the GDPR (Europe's General Data Protection Regulation), require companies to know the location of all sensitive data they collect and store. When performed effectively, the data inventory facilitates broad, streamlined data access, making data usage and related operations more effective and efficient.Ī data inventory further allows for better regulatory compliance. This document provides data consumers with a starting point for data discovery and access. For this reason, a data inventory is far more granular, detailed, and technical than a data catalog.īefore conducting a data inventory, we must understand its function. While each entry in a data inventory is unique, a data catalog can refer to the same data point in various entries. A data catalog allows users to locate those datasets by referencing them in various categories. While these terms are often used interchangeably, they are not the same and perform different functions.Ī data inventory is a unique set of data detailing the location and type of each data point in a company's collection. Here, it is important to distinguish between a data inventory and a data catalog. Data stewards maintain these data inventories and define the relevant data access policies for each dataset.Ĭonducting a data inventory can be a mammoth task, especially when an organization undertakes this task for the first time.
On a practical level, this inventory allows data analysts to determine what data is available to them and how it is accessed. This document (or collection of documents) pinpoints each dataset's location and the type of data it contains. We also unpack when each of these structures is necessary as well as the critical factors involved in effective data governance.Ī data inventory is a centralized metadata collection, indicating all of the datasets an organization collects and maintains. In each case, we include guidelines for building the structure along with examples of its use.
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