Working with data is a daily activity for companies across all sectors. Proper management requires data normalization to avoid anomalies and problems in the future. Additionally, it allows for better use of information. Let us explain the benefits of this process and why you should implement it.
Databases are a fundamental tool in any sector. An example is the banking industry, which handles large amounts of data: from customer and account information to websites storing user data. As an essential work element, databases need a correct structure and organization to ensure process efficiency.
This is why database normalization is essential for data analysts and decision-makers in companies and organizations. It is a process of structuring a relational database following what is known as normal forms. The goal is to reduce data redundancy and inconsistency while improving integrity.
Before normalization, a preliminary requirements analysis should be carried out to define policies and procedures, especially for large companies. Through consensus, business rules are established that will set the guidelines for achieving the desired objectives. Different goals, such as data reading or writing, require different approaches to the processes.
Failure to normalize databases can lead to system inaccuracies, slower processes, and operational inefficiencies. Therefore, it is imperative to design databases from the beginning according to these standards. If databases are already unnormalized, they can also be normalized afterward, which is recommended if it wasn’t done initially.
Side effects of denormalization
When modifying a database that has not been normalized, several negative side effects may occur. One example is the update anomaly. This happens when the same information is expressed in multiple rows, resulting in logical inconsistencies.
Another example is the insertion anomaly, which means that a record will not appear in the database until all the data is complete. Finally, the deletion anomaly occurs when, to delete certain data, it is necessary to remove other data that represents completely different facts.
Normalization aims to prevent these anomalies. In large databases, these types of anomalies can cause significant headaches for managers, so it is always recommended to carry out appropriate normalization for each context.
Normalization also has another advantage: it does not require extra work when redesigning or expanding the database. Its structure allows new data types to be easily and quickly accommodated without major changes. This minimizes the impact on applications that depend on these databases.
Normal forms are the various levels of depth achieved through normalization. Each normal form has a set of criteria that determine a table’s vulnerability to inconsistencies and logical anomalies. The higher the level, the more protected it will be against these issues.
Normalization is not only about a company’s internal operations but also has positive effects on third parties. For instance, it simplifies application development, resulting in better services for users.
It also offers additional user benefits, such as faster response times. This is highly demanded today, thanks to correct access to unique and unambiguous data.
It should be noted that normalization is generally very beneficial for any database. The necessary level of normalization must be analyzed in each case. For example, in large databases such as those managed by banking institutions, light normalization can be applied to improve processes without slowing operations (avoiding the need to navigate the entire structure). Therefore, this should be studied and analyzed by experts to design an optimal structure.
In conclusion, database normalization is a very beneficial process because it reduces data duplication and database size, directly impacting performance. Additionally, it maintains referential integrity, essential for the consistency of relationships between combined table data.
When developing applications that need to access these databases, normalization makes developers’ work easier and faster. After all, a company that works with properly normalized databases offers guarantees to the end user, positively affecting its image. Proper functioning translates into greater customer satisfaction on many levels and improves the efficiency and effectiveness of business processes and decision-making.
In the future, we will explore the concept of Robotic Process Automation (RPA), which refers to automations developed through artificial intelligence. It is often used to reduce workloads in highly repetitive and high-volume processes, such as supply chain management or certain accounting tasks.
