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How do you ensure your database schema supports future growth and change?

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In the dynamic world of Business Intelligence (BI), where data is the linchpin of decision-making, ensuring that your database schema can accommodate future growth and change is crucial. A well-designed schema not only supports efficient data retrieval and analysis but also adapts to evolving business needs without requiring extensive modifications. As you look to future-proof your database, consider these key strategies to maintain flexibility and scalability.

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1 Plan Ahead

Anticipating future needs is the cornerstone of a scalable database schema. When you design your database, think about potential changes in data volume, new types of data, and future reporting requirements. Use a flexible data modeling approach that allows for easy addition of new tables and columns. Abstracting your schema by using views or stored procedures can help insulate applications from changes, making it easier to evolve your database without disrupting existing functionality.

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Micha?l Dubus

Freelance - DBA Etude et Production multi éditeur / DataEngineer
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Modélisation Merise 1 & 2 (orientée POO) pour un schéma relationnel Mise en place du contr?le de volume afin de faire des projections temporelles de croissance

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Jonathan Fielding

Conference Speaker, Neurodiversity and inclusivity advocate, Principal Engineer at Legend
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When designing your database schema, it is incredibly important to plan ahead, focusing on simplicity, and flexibility. To enable you to do this, you need to do some discovery into current and future business needs. Through talking to both product and engineers on the team you should be able to get an idea of where you need the data to be flexible and where you can be strict. You might also consider using JSON columns for data that is subject to change however be wary that these unschemaed columns could be a source of tech debt in the future as they can be more difficult to update when new fields are added

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2 Normalize Data

Normalization is a process in database design that minimizes data redundancy and dependency by organizing data into tables according to rules designed to safeguard the data and to make the database more flexible. By normalizing your database schema, you create a structure that logically groups data, which can help in managing data more efficiently as your database grows. However, be mindful of not over-normalizing, as it can lead to complex queries and affect performance.

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Micha?l Dubus

Freelance - DBA Etude et Production multi éditeur / DataEngineer
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Ventiler les tables et objets selon leurs usages table d'exploitation table d'archivage vue fonctionnelle Respecter le typage des données dans la définition des colonnes

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3 Use Indexes

Indexes are critical for enhancing the performance of a database. They allow you to quickly locate and access the data without scanning the entire table. Proper indexing is a balancing act; too few can lead to slow query performance, while too many can affect write operations and consume additional storage. Plan your indexes based on the queries you expect to run, and review them regularly as usage patterns change.

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Micha?l Dubus

Freelance - DBA Etude et Production multi éditeur / DataEngineer
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Utiliser les fonctions d'explain plan afin d'ajouter ou supprimer les index nécessaires aux requêtes Attention à bien utiliser les types d'index unique, non unique, bitmap L'indexation permet une optimisation du retour du résultat de requête mais ralentit les opérations d'insert et d'update. Les index doivent être maintenus afin d'éviter une défragmentation dudit objet sans rebuild ou reorganize fréquents, les performances peuvent se dégrader très vite si la maintenance n'est pas en place de manière périodique (journalière ou hebdomadaire au plus)

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4 Implement Versioning

Versioning your database schema is a method for tracking changes over time, which can be especially useful when multiple teams are working on a database or when deploying updates to production environments. By keeping a record of schema changes, you can roll back to previous versions if needed and understand the evolution of your database structure. This practice aids in managing changes and ensures that your schema supports continuous integration and deployment processes.

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Micha?l Dubus

Freelance - DBA Etude et Production multi éditeur / DataEngineer
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La mise en place du contr?le de version permet d'avoir un différentiel entre avant/après un patch applicatif par exemple, également pour comparer des environnements devant être identiques et faire une mise à niveau rapide si nécessaire. Je développe selon le moteur, des requêtes sur les tables systèmes afin de générer ce contr?le de structure.

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5 Optimize Queries

Optimizing queries is an ongoing task that directly impacts database performance. Analyze query performance and look for ways to improve efficiency by refining joins, selecting only necessary columns, and avoiding functions that prevent the use of indexes. Regularly monitor slow queries and analyze the execution plan to spot bottlenecks. As your database grows, so will the importance of well-optimized queries.

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Micha?l Dubus

Freelance - DBA Etude et Production multi éditeur / DataEngineer
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Tous les moteurs actuels permettent avec des requêtes de ressortir toutes les sessions longues ou co?teuses (CPU/Mémoire/IO waits) Par la suite, il faut utiliser l'explain plan et des fonctions permettant d'indiquer si des index sont manquants ou non.

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6 Test Rigorously

Testing is an essential part of ensuring that your database schema can handle growth and change. Perform load testing to simulate increased data volumes and user loads to see how your database performs under stress. Also, test any schema changes in a staging environment before deploying them to production. This helps you catch potential issues early and ensures that your database remains robust and reliable.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Jonathan Fielding

Conference Speaker, Neurodiversity and inclusivity advocate, Principal Engineer at Legend
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When planning how you structure your database schema it is important to consider how it is going to be displayed on the frontend. While you shouldn't tie the structure completely to how it is displayed, you do want to ensure you have an easy way to transform the data into what will be displayed. You also want to ensure that you have flexibility for when the requirements of that frontend change.

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How do you ensure your database schema supports future growth and change?

1

2

3

4

5

6

7

1 Plan Ahead

2 Normalize Data

3 Use Indexes

4 Implement Versioning

5 Optimize Queries

6 Test Rigorously

7 Here’s what else to consider

Business Intelligence

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How do you ensure your database schema supports future growth and change?

1

2

3

4

5

6

7

1 Plan Ahead

2 Normalize Data

3 Use Indexes

4 Implement Versioning

5 Optimize Queries

6 Test Rigorously

7 Here’s what else to consider

Business Intelligence

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