sayn
dbt
sayn | dbt | |
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2 | 1 | |
117 | 3,802 | |
0.9% | - | |
6.8 | 10.0 | |
10 days ago | over 2 years ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sayn
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Average reply times from some of my Facebook friends over the last few years [OC], full article here: https://medium.com/@timsugaipov/taking-your-facebook-messenger-data-further-f9da079b1409?source=friends_link&sk=3bd04bb35ad9a4b6f586300e52f96e4f
Data Processing: SAYN
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Introducing SAYN: A Simple Yet Powerful Data Processing Framework.
We believe simplicity to be crucial when maintaining pipelines at scale. However, we also believe that simplicity should not come at the expense of flexibility. This is why we have built our own open source data processing framework: SAYN. SAYN is designed to empower analytics teams by being simple, flexible and centralised. It democratises the contribution to data processes within an analytics team, enables full flexibility and helps save a lot of time through automation.
dbt
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Open Source Analytics Stack: Bringing Control, Flexibility, and Data-Privacy to Your Analytics
Due to the rise in cloud-based data warehouses, businesses can directly load all the raw data into the data warehouse without prior transformations. This process is known as ELT (Extract, Load, Transform) and gives data and analytics teams freedom to develop ad-hoc transformations based on their particular needs. ELT became popular as the cloud's processing power and scale became better suited to transforming data. DBT (website, GitHub) is a popular open-source tool recommended for ELT and allows businesses to transform data in their warehouses more effectively. It's a great pairing with with RudderStack's Cloud Extract ETL tool.
What are some alternatives?
dbt-databricks - A dbt adapter for Databricks.
Apache Kafka - Mirror of Apache Kafka
dataform - Dataform is a framework for managing SQL based data operations in BigQuery
airbyte - The leading data integration platform for ETL / ELT data pipelines from APIs, databases & files to data warehouses, data lakes & data lakehouses. Both self-hosted and Cloud-hosted.
tinvois-parser - Extract receipt info
superset - Apache Superset is a Data Visualization and Data Exploration Platform
data-engineering-wiki - The best place to learn data engineering. Built and maintained by the data engineering community.
Snowplow - The enterprise-grade behavioral data engine (web, mobile, server-side, webhooks), running cloud-natively on AWS and GCP
beneath - Beneath is a serverless real-time data platform ⚡️
nbdev - Create delightful software with Jupyter Notebooks
yaetos - Write data & AI pipelines in (SQL, Spark, Pandas) and deploy to the cloud, simplified
rudderstack-docs - Documentation repository for RudderStack - the Customer Data Platform for Developers.