Review website copy in rebranded preview

[stichbury]

A small (I hope) task to review the website copy on the newly branded website in case any small tweaks would be beneficial at the time we make a new release. I'll create a set of suggestions here for signoff.

[stichbury]

Kedro is an open sourced Python framework for creating maintainable and modular data science code

Replace with

Kedro is a toolbox for production-ready data science.

[stichbury]

Machine Learning Engineering
Puts the "engineering" back into data science because it borrows concepts from software engineering and applies them to machine-learning code. It is the foundation for clean, data science code.

Can we make the first sentence a proper sentence?

Machine Learning Engineering
Kedro is the foundation for clean, data science code. It borrows concepts from software engineering and applies them to machine-learning projects.

To make the change:
Copy and replace text.

[stichbury]

Handles Complexity
Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems.
Standardisation
Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together.
Production-Ready
Makes a seamless transition from development to production, as you can write quick, throw-away exploratory code and transition to maintainable, easy-to-share, code experiments quickly.

Some changes to copy to make proper sentences as above.

Handles Complexity
A Kedro project provides scaffolding for complex data and machine-learning pipelines. You spend less time on tedious "plumbing" and focus instead on solving new problems.
Standardisation
Kedro standardises how data science code is created, ensuring teams can collaborate to solve problems together.
Production-Ready
Make a seamless transition from development to production with throw-away exploratory code that you can transition to reproducible, maintainable, and modular experiments.

[stichbury]

Integrations
Apache Spark, Pandas, Dask, Matplotlib, Plotly, fsspec, Apache Airflow, Jupyter Notebook and Docker.

Should we add any of the following?

• Databricks
• Amazon SageMaker
• Azure ML
• VertexAI
• Kubeflow
• MLFlow

Note: We'd want their logos too

[stichbury]

This is now done thanks to this PR

> FAQs > > You can find the [Kedro community on Slack](https://slack.kedro.org/). > > We also maintain a list of articles, podcasts, talks, and Kedro showcase projects in the [kedro-community](https://github.com/kedro-org/kedro-community) repository.

Change link

FAQs

You can find the Kedro community on Slack.

We also maintain a list of articles, podcasts, talks, and Kedro showcase projects in the awesome-kedro repository.

However, it would be great to add links here to the archives of discussions.

Change:

You can find the Kedro community on Slack.

To

You can find the Kedro community on Slack. Discussions from the Slack channels are also archived online, as are those from an earlier set of Discord channels.

This will help address #84

[stichbury]

Ready to start?
You are ready to get going with the Kedro workflow. But first, head to our documentation to learn how to install Kedro and then get up to speed with concepts like nodes, pipelines, the data catalog in our introductory tutorial.

Replace the copy

Ready to start?
Visit the introductory tutorial to learn how to install Kedro and get up to speed with concepts like nodes, pipelines, and the data catalog.

[stichbury]

@yetudada @astrojuanlu A few copy suggestions to update the website ahead of re-launch. I can collate all comments and build one single list of changes for the team to make.

[yetudada]

I like the changes on this! I have two points:

• This is a larger change but can we pull some of the copy from the deck into this?
• On integrations, I would add the checked ones and only ones that GetInData have provided with their plugin ecosystem. We can't put Prefect because we don't support Prefect 2.0.

[stichbury]

FAQs

What is Kedro?

Kedro is an open-source Python framework hosted by the Linux Foundation (LF AI & Data). Kedro uses software engineering best practices to help you build production-ready data science code.

What's Kedro's origin story?
Kedro was born at QuantumBlack to reduce technical debt in data science experiments, making an easier transition from experimentation to production. The latest iteration of Kedro is an incubating project within https://lfaidata.foundation/.

[stichbury]

Closing this because I've created a final collated set of changes for the website here: kedro-org/kedro-website#143