From 985369786f79f47218b87e8cc426a2bd0051b173 Mon Sep 17 00:00:00 2001 From: Gil Benghiat Date: Tue, 6 Aug 2024 14:47:25 -0400 Subject: [PATCH] Edits to install page. --- README.md | 27 +++++++++++++++------------ 1 file changed, 15 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index 19f13a0..a680b34 100644 --- a/README.md +++ b/README.md @@ -1,11 +1,11 @@ -# DataOps Data Quality TestGen +# DataOps Data Quality TestGen ![apache 2.0 license Badge](https://img.shields.io/badge/License%20-%20Apache%202.0%20-%20blue) ![PRs Badge](https://img.shields.io/badge/PRs%20-%20Welcome%20-%20green) [![Latest Version](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fhub.docker.com%2Fv2%2Frepositories%2Fdatakitchen%2Fdataops-testgen%2Ftags%2F&query=results%5B0%5D.name&label=latest%20version&color=06A04A)](https://hub.docker.com/r/datakitchen/dataops-testgen) [![Docker Pulls](https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fhub.docker.com%2Fv2%2Frepositories%2Fdatakitchen%2Fdataops-testgen%2F&query=pull_count&style=flat&label=docker%20pulls&color=06A04A)](https://hub.docker.com/r/datakitchen/dataops-testgen) [![Documentation](https://img.shields.io/badge/docs-On%20datakitchen.io-06A04A?style=flat)](https://docs.datakitchen.io/articles/#!dataops-testgen-help/dataops-testgen-help) [![Static Badge](https://img.shields.io/badge/Slack-Join%20Discussion-blue?style=flat&logo=slack)](https://data-observability-slack.datakitchen.io/join) -*

DataOps Data Quality TestGen delivers simple, fast data quality test generation and execution by data profiling, Β new dataset screening and hygiene review, algorithmic generation of data quality validation tests, ongoing production testing of new data refreshes, and continuous anomaly monitoring of datasets. DataOps TestGen is part of DataKitchen's Open Source Data Observability.

* +*

DataOps Data Quality TestGen can help you find data issues so you can alert your users and notify your suppliers. It dies this by delivering simple, fast data quality test generation and execution by data profiling, Β new dataset screening and hygiene review, algorithmic generation of data quality validation tests, ongoing production testing of new data refreshes, and continuous anomaly monitoring of datasets. DataOps TestGen is part of DataKitchen's Open Source Data Observability.

* ## Features -What does DataKitchen's DataOps Data Quality TestGen do? It helps you understand and find data issues in new data. +What does DataKitchen's DataOps Data Quality TestGen do? It helps you understand and find data issues in new data.

DatKitchen Open Source Data Quality TestGen Features - New Data

@@ -22,7 +22,7 @@ A single place to manage Data Quality across data sets, locations, and te ## Installation -The [dk-installer](https://github.com/DataKitchen/data-observability-installer/?tab=readme-ov-file#install-the-testgen-application) program installs DataOps Data Quality TestGen. +The [dk-installer](https://github.com/DataKitchen/data-observability-installer/?tab=readme-ov-file#install-the-testgen-application) program installs DataOps Data Quality TestGen. ### Install the prerequisite software @@ -74,7 +74,7 @@ In the TestGen UI, you will see that new data profiling and test results have be The [dk-installer](https://github.com/DataKitchen/data-observability-installer/?tab=readme-ov-file#install-the-testgen-application) and [docker compose CLI](https://docs.docker.com/compose/reference/) can be used to operate the installed TestGen application. All commands must be run in the same folder that contains the `dk-installer.py` and `docker-compose.yaml` files used by the installation. -### Remove demo data +### Remove demo data After completing the quickstart, you can remove the demo data from the application with the following command. @@ -116,19 +116,24 @@ docker compose down docker compose up -d ``` -## Community +## What Next? -### Getting Started Guide +### Getting started guide We recommend you start by going through the [Data Observability Overview Demo](https://docs.datakitchen.io/articles/open-source-data-observability/data-observability-overview). ### Support -For support requests, [join the Data Observability Slack](https://data-observability-slack.datakitchen.io/join) and ask post on #support channel. +For support requests, [join the Data Observability Slack](https://data-observability-slack.datakitchen.io/join) πŸ‘‹ and ask post on #support channel. -### Connect -Talk and Learn with other data practitioners who are building with DataKitchen. Share knowledge, get help, and contribute to our open-source project. +### Connect to your database +Follow [these instructions](https://docs.datakitchen.io/articles/#!dataops-testgen-help/connect-your-database) to improve the quality of data in your database. + +### Community +Talk and Learn with other data practitioners who are building with DataKitchen. Share knowledge, get help, and contribute to our open-source project. Join our community here: +* πŸ‘‹ [Join us on Slack](https://data-observability-slack.datakitchen.io/join) + * 🌟 [Star us on GitHub](https://github.com/DataKitchen/data-observability-installer) * 🐦 [Follow us on Twitter](https://twitter.com/i/flow/login?redirect_after_login=%2Fdatakitchen_io) @@ -139,8 +144,6 @@ Join our community here: * πŸ“š [Read our blog posts](https://datakitchen.io/blog/) -* πŸ‘‹ [Join us on Slack](https://data-observability-slack.datakitchen.io/join) - * πŸ—ƒ [Sign The DataOps Manifesto](https://DataOpsManifesto.org) * πŸ—ƒ [Sign The Data Journey Manifesto](https://DataJourneyManifesto.org)