A Data Dictionary is a file or set of files that stores a database’s metadata. This metadata is important for organizing and maintaining data, preventing redundant or incorrect information from being created, and allowing for easy searching and retrieval of information.
A data dictionary is a critical part of any relational database, although it is rarely seen by most users. Typically, it is only used by database administrators to interact with and manage the metadata in a database.
Data dictionaries can be active or passive.
An active data dictionary is one that updates itself automatically when changes are made to a database’s structure. This is a convenient way to ensure the latest information is always available in a database. On the other hand, a passive data dictionary requires manual updates and is more time-consuming to maintain.
The benefits of a data dictionary include the ability to create and enforce consistent terminology, improve data integrity within your organization, and support a centralized approach to enterprise-wide data standards. A data dictionary can also help prevent data silos from forming and facilitate reusability of information across your organization.
Data Storage Automation
SDS can automatically adjust storage tiers based on your day-to-day capacity needs, without any intervention by an administrator. This can save your company money and make the entire storage process more efficient.
Automated data tiering is especially useful for organizations that have performance-constrained workloads, such as open source databases like MariaDB, MySQL and PostgreSQL. These types of databases typically produce large numbers of hot transactions per second, resulting in expensive data storage and operations.
The cost of storing large amounts of data is becoming an increasingly significant expense. Rather than spending tens of thousands of dollars on new storage capacity, SDS allows you to store only the minimum amount of data that you need for day-to-day business operations.
This means that you can reduce your overall storage costs while increasing performance. SDS also eliminates the need to manually connect and manage new storage devices and systems.
Taxonomy is a common pattern that holds metadata, which helps you understand and think about the data in your organization. A data dictionary defines and contextualizes the elements of a taxonomy, making it easier to navigate your data’s pattern and interpret its meaning.
Data dictionaries are a key component of the data integrity strategy, and they are also critical to an organization’s ability to create and enforce consistent definitions, naming conventions and element values. This foundation for consistency in your organization’s data policies and procedures will lead to greater trust and reliability in your data.
The data integrity approach can be applied to many types of data, including data from marketing campaigns, customer and employee data, and financial statements. The goal is to have your data in a consistent, reliable format that can be accessed and understood by all members of your organization, whether they are data scientists, business analysts, or other personnel with an interest in the information.