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 122

Metadata Visualization Data Lake Data-driven 122

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 82

Metadata Testing Data Lake Consulting 82

AWS Big Data

APRIL 26, 2024

Set up EMR Studio In this step, we demonstrate the actions needed from the data lake administrator to set up EMR Studio enabled for trusted identity propagation and with IAM Identity Center integration. On the Lake Formation console, choose Data lake permissions under Permissions in the navigation pane.

Analytics 96

Analytics Data Lake Management Enterprise 96

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

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

AWS Big Data

JANUARY 22, 2024

Data as a product Treating data as a product entails three key components: the data itself, the metadata, and the associated code and infrastructure. In this approach, teams responsible for generating data are referred to as producers. Srikant Das is an Acceleration Lab Solutions Architect at Amazon Web Services.

Data-driven 87

Data-driven Advertising Metadata Data Architecture 87

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., Data governance, for the win! Or something.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71