From c4528e4124abbae68cda1e5766177aea465a6ff0 Mon Sep 17 00:00:00 2001 From: Fabiana Clemente Date: Mon, 31 Jul 2023 22:47:48 +0100 Subject: [PATCH] docs: add profiling databases example --- README.md | 2 +- docsrc/source/index.rst | 1 + .../pages/use_cases/profiling_databases.rst | 20 +++++++++++++++++++ 3 files changed, 22 insertions(+), 1 deletion(-) create mode 100644 docsrc/source/pages/use_cases/profiling_databases.rst diff --git a/README.md b/README.md index 856c00d9e..2473c0f55 100644 --- a/README.md +++ b/README.md @@ -100,7 +100,7 @@ YData-profiling can be used to deliver a variety of different use-case. The docu | [Handling sensitive data](https://ydata-profiling.ydata.ai/docs/master/pages/use_cases/sensitive_data.html ) | Generating reports which are mindful about sensitive data in the input dataset | | [Dataset metadata and data dictionaries](https://ydata-profiling.ydata.ai/docs/master/pages/use_cases/metadata.html) | Complementing the report with dataset details and column-specific data dictionaries | | [Customizing the report's appearance](https://ydata-profiling.ydata.ai/docs/master/pages/use_cases/custom_report_appearance.html ) | Changing the appearance of the report's page and of the contained visualizations | - +| [Profiling Databases](https://ydata-profiling.ydata.ai/docs/master/pages/use_cases/profiling_databases.html) | For a seamless profiling experience in your organization's databases, check [Fabric Data Catalog](https://ydata.ai/products/data_catalog), which allows to consume data from different types of storages such as RDBMs (Azure SQL, PostGreSQL, Oracle, etc.) and object storages (Google Cloud Storage, AWS S3, Snowflake, etc.), among others. | ### Using inside Jupyter Notebooks There are two interfaces to consume the report inside a Jupyter notebook: through widgets and through an embedded HTML report. diff --git a/docsrc/source/index.rst b/docsrc/source/index.rst index 1b0e02f04..a1f0ca5a5 100644 --- a/docsrc/source/index.rst +++ b/docsrc/source/index.rst @@ -19,6 +19,7 @@ pages/use_cases/big_data pages/use_cases/sensitive_data pages/use_cases/comparing_datasets + pages/use_cases/profiling_databases pages/use_cases/metadata pages/use_cases/custom_report_appearance diff --git a/docsrc/source/pages/use_cases/profiling_databases.rst b/docsrc/source/pages/use_cases/profiling_databases.rst new file mode 100644 index 000000000..bceaf4c85 --- /dev/null +++ b/docsrc/source/pages/use_cases/profiling_databases.rst @@ -0,0 +1,20 @@ +================== +Profiling Databases +================== + +``ydata-profiling`` provides overall metrics and statistics for your datasets. However, data is often not stored in a single table but rather across multiple tables in a database. + +Databases consist of schemas, each composed of several tables. Being able to profile the relationships between tables, such as primary keys and foreign keys relationships, +while being able to combine it with detailed statistics and metrics per table is crucial to ensure data integrity , effective data management and avoid anomalies. + +`YData Fabric Data Catalog `_ delivers detailed databases data quality insights and profiling metrics combined with built-in connectors +for easy integration with existing data architectures. With a Fabric Data Catalog, you can: + +* Connect to existing data architecture through built-in data connectors +* Manage data connections and dataset ownership +* Organize data on a project basis +* Analyze the schema and profile referential integrity +* View detailed statistics and plots per table +* Experience an interactive interface that supports tables with hundreds of columns through distributed computing + +`Learn more about the benefits of adopting Data Catalogs. `_. \ No newline at end of file