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write-for-the-community's Introduction

Guidelines

Our full guidelines for publishing can be found here. Additionally, our FAQ which includes information on payment and the review process can be found here.

Our Philosophy

Airbyte is fully open by design. We share our roadmap, strategy and everything about our business model.

In this fashion, this repository is designed to share about our roadmap in terms of content publications, so you can vote on the articles, tutorials and videos we plan to work on, and also contribute them!

Contributing

If you want to help push our content roadmap forward, the first thing to do is to join the #write-for-the-community channel in our Slack by clicking here.

Here are the different types of contributions you can help with.

This is how we differentiate the different types of publications:

  • Articles are pieces that will go on our blog, which are usually higher level explorations of the data engineering space, but not always.
  • Recipes are educational use cases to help Airbyte users understand how they can leverage Airbyte in data engineering, marketing, customer success, sales, finance and other use cases. You can see examples here
  • Operator guides are located in our documentation to help Airbyte users better leverage Airbyte with other tools of the data stack. Some examples are here.

Once you're submitted your content, you can move it down the different steps of the process in the community project here.

We look forward to seeing what the community requests and produces! We value the different ways that people use Airbyte and would love to explore all the possibilities that exist with the technology.

We are not looking for promotional pieces or marketing pitches.

write-for-the-community's People

Contributors

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Stargazers

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Watchers

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write-for-the-community's Issues

Quick demo! 2 months of building

A quick video demo of what we have built in the last 2 months.
This would be the 1st video of a series of videos that we could publish every month with the new features/progress of the latest month. This could be a new approach to changelogs that we could publish on external publication platforms, such as dev.to.

How to build and contribute a new destination

Some potential contributors prefer to see video tutorials instead of documentation articles, and see people actually show them exactly how to do things. We could also use the video to improve the documentation, and an article on external publications to show how building your own integration is going to be trivial using Airbyte, which is great for awareness towards our mission.

Partition and cluster BigQuery tables with Airbyte and dbt

Request Details
What type tutorial/article would you like to see?

dbt allows a long list of configurations of materialization options:
https://docs.getdbt.com/reference/resource-configs/bigquery-configs

If a user exports the generated normalization project from a sync and re-import it as a custom operation, they should be able to edit and customize advanced configurations such as these (not only applicable to bigquery but to other destinations too)

Examples:

  • Using table partitioning and clustering
  • (in other databases, set primary keys?)
  • Policy tags: BigQuery enables column-level security by setting policy tags on specific columns.

User requests here:
https://airbytehq.slack.com/archives/C01MFR03D5W/p1623396575421800

Distribution:

[TOPIC] Centralize Transactional Data for Reporting

Connectors: AWS Lambda, MongoDB, Google Analytics, Google Sheets, SendGrid, SFTP, Stripe
Destination: Google BigQuery
Business Intelligence Tool: Looker

Some data to report on:

  • Conversion rates according to channels
  • Potential LTV for each stage for each channel
  • Cost to get prospects through the door according to channels
  • Marketing spend info synced via a Google Sheet for instance

Inspiration: https://fivetran.com/case-studies/case-study-branch-insurance

How to showcase your project to Airbyte's community

Some potential contributors prefer to see video tutorials instead of documentation articles. We could also use the video to improve the website. Building something is always something to be proud of, so we want to put our contributors' and users' work forward as much as possible. We want to help them as much as possible achieve whatever they want to achieve. Airbyte is above all an enabler.

[TOPIC] How to uncover the time spent by your team in Zoom calls (using Airbyte and Tableau)

  • Set up data replication from Zoom to a database supported by Tableau: https://docs.airbyte.io/integrations/sources/zoom
  • Plug Tableau
  • Product the following charts:
    • Meetings:
      • Evolution of the # meetings per week in the team
      • Evolution of the # hours per week in meeting in the team
      • Evolution of the # external participants for all meeting in the team per week
      • Listing of team members with the number of meetings per week and number of hours spent in meeting, ranked
    • Webinars:
      • Evolution of the # webinar per week in the team
      • Evolution of the # hours per week in webinars in the team
      • Evolution of the # participants for all webinars in the team per week
      • Listing of team members with the number of webinars per week and number of hours spent in meeting, ranked

[TOPIC] Automate Reliable Financial Reporting Across Your Organization

Sources: Intercom, Google Analytics, LinkedIn Ads, Marketo, NetSuite, Salesforce, Stripe, Zuora
Destination: Snowflake
Visualization: Tableau

  • The accounting team uses the data to consider its general accounting principles, such as how it manages payments and accounts receivable.
  • The financial planning and analysis team uses segmentation and customer performance data to develop a long-term strategy.
  • Revenue and customer information informs the core customer lifetime value model: a predictive model based on the invoices collected from Zuora.
  • Finance and marketing data helps the business increase efficiency with paid ad spend.
  • Zuora data informs how the business allocates costs, and evaluates performance and profitability.

Inspirations:

Building a GitHub activity dashboard on your project with Airbyte and Metabase

Inspiration: https://preset.io/blog/2020-04-15-github-community-dashboard/

Metrics we'd like to see:

  • evolution of the # stargazers
  • evolution of the # watchers
  • evolution of the # forks
  • evolution of the # issue contributors
  • evolution of the # PR contributors
  • evolution of the # new comments from non-team members
  • evolution of the # new issues from non-team members
  • evolution of the # new PRs from non-team members
  • time to 1st comment for non-team members interactions (50th, 90th percentile)
  • time until 1st review for a PR (50th, 90th percentile)
  • time until merge for a PT (50th, 90th percentile)

Finalize content:
https://airbyte.io/recipes/build-a-github-activity-dashboard-for-your-project

TO PROMOTE:

[TOPIC] K8s - Wrapping Docker Image at Runtime

Would love to see a blogpost explaining what we're doing with K8s (needing to "wrap" a docker image at runtime in K8s; sidecar + socat). @davinchia @jrhizor . It seems like what we're doing here isn't super common, so it could be a cool go to article for people in similar situations.

How open-source can help you scrape LinkedIn in a Postgres database (using BeautifulSoup + Airbyte)

  • Set up BeautifulSoup
  • Take a LinkedIn profile page
  • Scrape that data and export in a JSON
  • Set up Airflow and use Airflow to trigger a data integration of the JSON files to a Postgres database using Airbyte's API
  • User in the end should be able to input a csv of LinkedIn Profile URLs

PROMOTION TO DO

[TOPIC] How to forecast your purchase orders on Shopify using Airbyte and MindsDB

This is a tutorial on which we will collaborate on with the MindsDB team. The agreement we reached is that we write the 1st part of the tutorial about: how to replicate data from Shopify to a Postgres database to save store info.

The MindsDB team will write about using MindsDB Ai Tables to train the model that will forecast the purchase order.

Using singer within airbyte

Blog post on using singer within airbyte to bootstrap. What we learned. Pros, cons.

Will try to take a stab at this in the next couple days.

Why we chose Java to build Airbyte's platform

A question that the community sometimes ask is why we chose Java, over Python, to build the platform.
Please note again that you can build your connector in whatever language you want.

[TOPIC] Building a Slack activity dashboard using Airbyte and Preset

Inspiration:

Metrics that we would like to see in the dashboard:

  • evolution of the # members
  • evolution of the # weekly active members (WAU) (meaning they posted a message or read at least one channel or direct message) and monthly active members (MAU)
  • evolution of the # messages with distinction between team and community members, so 2 lines.
  • time to 1st reply in thread for non-team members (50%, 90% percentile) - meaning for any message made by non-team members for which a thread is created, what is the time to first reply in the thread. So we don't consider messages without threads.
  • messages posted per channel for past month and in total

  • evolution of the # members per timezone and of weekly active members

Java 8 stream gotchas we faced

We ran into a lot of whacky java 8 stream issues early on in development. I think there's a light, fun article to write about some of the gotchas there.

How we increase our leverage with contractors

We use contractors in various parts of our engineering works. I think our thought process here is interesting and would be worth reading. e.g. using contractors forces us to be really honest about what work we need to internally or whether we could do something higher leverage.

This was a bit inspired by the fact that I was trying to find something online on how to structure FE teams using contractors and I'm finding very little.

[TOPIC] Personalize Your E-commerce Interactions To Drive Revenues

Source: Amplitude
Destination: Google BigQuery, Twilio (after creating segments on reverse ETL tool)
Reverse ETL tool: Hightouch / Census

  • For a business that runs on a freemium ‘try-before-you-buy’ model, identifying ways to optimise the user experience and convert them to a purchase is business critical.
  • Consolidation of data before running ML model to understand which items would be most appealing to each customer segment
  • Leverage a reverse ETL tool to push the data back to Twilio and send personalized emails and texts

How to build and contribute a new source

Some potential contributors prefer to see video tutorials instead of documentation articles, and see people actually show them exactly how to do things. We could also use the video to improve the documentation, and an article on external publications to show how building your own integration is going to be trivial using Airbyte, which is great for awareness towards our mission.

How to set up your 1st connection in 2 minutes

It is important for new users to understand how easy it is to use Airbyte.
This tutorial should be published in several format to suit the preferences of our users: article, video.
It can help improve our documentation too.

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