Data Transformation Metadata Publishing Testing 
Cloudera
MARCH 14, 2023
Allows them to iteratively develop processing logic and test with as little overhead as possible. Plays nice with existing CI/CD processes to promote a data pipeline to production. Provides monitoring, alerting, and troubleshooting for production data pipelines.
Cloudera
DECEMBER 9, 2022
Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow. This allows developers to make changes to their processing logic on the fly while running some test data through their flow and validating that their changes work as intended.
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
datapine
SEPTEMBER 29, 2022
This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g.,
AWS Big Data
MARCH 13, 2024
Developers can use the support in Amazon Location Service for publishing device position updates to Amazon EventBridge to build a near-real-time data pipeline that stores locations of tracked assets in Amazon Simple Storage Service (Amazon S3). Athena is used to run geospatial queries on the location data stored in the S3 buckets.
Alation
MARCH 22, 2022
More specifically, IDF has been integrated with Alation at an API level; this means that all generated pipeline code, metadata attributes, configuration files, and lineage are automatically synced (representing a huge time savings). They can better understand data transformations, checks, and normalization. Transparency is key.
AWS Big Data
APRIL 25, 2023
The following AWS services are used for data ingestion, processing, and load: Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between SaaS applications like Salesforce, SAP, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift , in just a few clicks.
AWS Big Data
OCTOBER 11, 2023
Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.
Expert insights. Personalized for you.
81 
Let's personalize your content