As more data is generated, collected, processed and analyzed, companies around the world and from the most diverse sectors seek to implement data reading and governance protocols in their routines.
But it turns out that to get the most business value from data, organizations need a strategic mindset coupled with advanced technologies.
This is where the concept of data architecture comes in. But do you know what it means?
What is data architecture?
We can define data architecture as a plan that an organization another important point about the reservation system for the data it has at hand.
A good data architecture should contain the answers to questions such as: how will this data be managed? In what ways will it be useful for the organization’s purposes? How will the data flow through the storage systems? Among other questions.
Another purpose of data architecture is to ensure that data access is always secure, timely and clear.
Data quality
Data quality is the key sms mailing for business as an additional marketing channel of a strong data architecture.
Ensuring data quality ensures that information is well governed, which proves very useful when creating accurate models and strong schemas.
Taking care to ensure data quality also makes it easier to extract valuable information.
Data governance
Data governance is also very important and, as you may have mobile lead when reading the previous topic, it is directly related to data quality.
In practice, when we talk about governance applied to data, we are referring to a form of data management that involves standards, metrics and processes.
Establishing data governance measures is a mandatory step for the success of a data architecture structure.
Data origin
Data provenance, as the name suggests, refers to information about data from its origins.
It is through provenance that we know when data was collected, cleaned, structured or processed. Having this information at hand is essential for establishing a reliable and efficient data architecture.