AWS Big Data

APRIL 19, 2023

We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The first component (metadata setup) consumes existing Hive job configurations and generates metadata such as number of parameters, number of actions (steps), and file formats. sql_path SQL file name.

Metadata 76

Metadata Testing Data Lake Consulting 76

AWS Big Data

JUNE 6, 2023

Founded in 2012, SumUp is the financial partner for more than 4 million small merchants in over 35 markets worldwide, helping them start, run and grow their business. Unless, of course, the rest of their data also resides in the Google Cloud. The Data Science teams also use this data for churn prediction and CLTV modeling.

Analytics 55

Analytics Data Lake Testing Optimization 55

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

APRIL 26, 2024

Use Lake Formation to grant permissions to users to access data. Test the solution by accessing data with a corporate identity. Audit user data access. On the Lake Formation console, choose Data lake permissions under Permissions in the navigation pane. Select Named Data Catalog resources.

Analytics 85

Analytics Data Lake Management Enterprise 85

AWS Big Data

JUNE 13, 2023

Download the SAML metadata file. In the navigation pane under Clients , import the SAML metadata file. Download the Keycloak IdP SAML metadata file from that URL location. For Metadata document , upload the Keycloak IdP SAML metadata XML file you downloaded and saved to your local machine earlier. Choose Browse.

Metadata 52

Metadata Dashboards Business Intelligence Management 52

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. There are multiple tables related to customers and order data in the RDS database.

Metadata 117

Metadata Visualization Data Lake Data-driven 117

Domino Data Lab

AUGUST 8, 2019

I mention this here because there was a lot of overlap between current industry data governance needs and what the scientific community is working toward for scholarly infrastructure. The gist is, leveraging metadata about research datasets, projects, publications, etc., Or something. Nothing Spreads Like Fear”. No big deal.”.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71