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How do you manage your data warehouse and ETL code?

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Data warehouse and ETL code are essential components of any database development project. They help you store, transform, and analyze large volumes of data from various sources. However, managing them can be challenging, especially as your project grows and changes. In this article, you will learn some best practices and tips on how to manage your data warehouse and ETL code effectively and efficiently.

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Rávilla M.
Mo Sijarrey

Data Expert Person

1 Use a version control system

A version control system (VCS) is a tool that tracks the changes and history of your code files. It allows you to create, update, and revert your code in a consistent and organized way. Using a VCS can help you avoid losing or overwriting your code, collaborate with other developers, and document your code changes. Some popular VCS options are Git, Subversion, and Mercurial.

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Mo Sijarrey

Data Expert Person
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TL;DR: version control is not required in most data ops, but it's nice to have and worth learning. Version control seems irrelevant to data science projects (even to any data ops in general). For two reasons: (1) Lack of knowledge (2) Many of those projects are solo. Personally, I use GitHub for any project I build, it's just my default first step is to create a project in there. It's amazing how you can organise your code and gradually build it. There are many ways to back the code and update it, but using version control allows you to approach it in a professional way, even for ad hoc projects. Finally, relying on advanced tools such as dbt, requires using version control.

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Sean Robinson

Freelance Contractor for Software Development
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Whatever type of version control you use is a valuable tool for any development team. I'd argue that even if you're doing your own personal projects, it's not a bad idea to have some form of version control, but with a team, it's imperative.

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2 Follow a naming convention

A naming convention is a set of rules and guidelines for naming your code elements, such as tables, columns, functions, and variables. It helps you create clear, consistent, and meaningful names that reflect the purpose and structure of your code. Following a naming convention can help you avoid confusion, errors, and conflicts in your code, as well as make it easier to read and maintain. Some common naming conventions are camelCase, snake_case, and PascalCase.

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3 Organize your code files and folders

Organizing your code files and folders is another way to improve the clarity and readability of your code. It helps you group your code by functionality, type, or source, and avoid cluttering your code base. Organizing your code files and folders can help you find, access, and modify your code faster and easier. Some common ways to organize your code files and folders are by layer, by module, or by feature.

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4 Document your code

Documenting your code is the process of adding comments, descriptions, and annotations to your code to explain what it does, why it does it, and how it does it. It helps you communicate your code logic, design, and assumptions to yourself and other developers. Documenting your code can help you debug, test, and improve your code quality and performance. Some common ways to document your code are by using comments, docstrings, or metadata.

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Nicholas G. Piesco

AI Software Architect | Data Solutions Architect | Data Sommelier
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Code readability is the best documentation tool, it makes it easier to maintain and understand code. Applying DRY principle helps to cut down on repeated code, further lending to a cleaner and more organized code base. Additionally, utilizing SOLID principles encourages creation of designs/systems that are logical and flexible. Simple strategies such as choosing descriptive variable names, maintaining a consistent style, and avoiding complicated structures all improve readability by essentially letting the code explain itself.

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5 Test your code

Testing your code is the process of verifying that your code works as expected and meets the requirements and specifications of your project. It helps you identify and fix any errors, bugs, or anomalies in your code before deploying it to production. Testing your code can help you ensure the accuracy, reliability, and security of your data warehouse and ETL code. Some common ways to test your code are by using unit tests, integration tests, or regression tests.

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Nicholas G. Piesco

AI Software Architect | Data Solutions Architect | Data Sommelier
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Data-driven testing methodology enhances traditional testing strategies mentioned (e.g., as unit, integration, and regression tests) by separating test scripts from test data. This allows the same script to be run with multiple data sets. The process is facilitated through use of frameworks/tools which automate test cases, with the data managed separately, often in external databases/files.

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6 Automate your code deployment

Automating your code deployment is the process of using tools and scripts to automate the steps and tasks involved in moving your code from development to production. It helps you save time, reduce errors, and streamline your workflow. Automating your code deployment can help you achieve faster, smoother, and more consistent code delivery and execution. Some common tools and scripts for automating your code deployment are Jenkins, Airflow, or Bash.

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Rávilla M.
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Automating code deployment is a way to optimize manual and repetitive activities, giving professionals the freedom to focus on importants projects that will add more value to their deliveries.

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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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How do you manage your data warehouse and ETL code?

1

2

3

4

5

6

7

1 Use a version control system

2 Follow a naming convention

3 Organize your code files and folders

4 Document your code

5 Test your code

6 Automate your code deployment

7 Here’s what else to consider

Database Development

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How do you manage your data warehouse and ETL code?

1

2

3

4

5

6

7

1 Use a version control system

2 Follow a naming convention

3 Organize your code files and folders

4 Document your code

5 Test your code

6 Automate your code deployment

7 Here’s what else to consider

Database Development

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