Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So Subscribe to Alation's Blog Get the latest data cataloging news and trends in your inbox.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

JULY 12, 2023

Amazon Redshift helps you break down the data silos and allows you to run unified, self-service, real-time, and predictive analytics on all data across your operational databases, data lake, data warehouse, and third-party datasets with built-in governance.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

AWS Big Data

JUNE 12, 2023

Therefore, it’s crucial to keep the schema definition in the Schema Registry and the Data Catalog table in sync. To avoid this, it’s recommended to use a data quality check mechanism to identify such anomalies and take appropriate action in case of unexpected behavior. Retrieve the name of the Crawler from the stack output.

Management 79

Management Metadata Testing Internet of Things 79

Domino Data Lab

JUNE 15, 2021

At a certain point, as the demand keeps growing, the data volumes rapidly increase. Data is no longer stored in CSV files, but in a dedicated, purpose built data lake / data warehouse. Existing preprocessing, data ingestion, and data quality processes can be converted from Java/Spark into Java UDFs.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Alation

JUNE 17, 2021

Lastly, active data governance simplifies stewardship tasks of all kinds. Tehnical stewards have the tools to monitor data quality, access, and access control. A compliance steward is empowered to monitor sensitive data and usage sharing policies at scale. The Data Swamp Problem. Sign up for a weekly demo today.

Data Governance 98

Data Governance Data Lake Insurance Enterprise 98

IBM Big Data Hub

JULY 27, 2023

Request a demo to see how watsonx can put AI to work There’s no AI, without IA AI is only as good as the data that informs it, and the need for the right data foundation has never been greater. It provides the combination of data lake flexibility and data warehouse performance to help to scale AI.

Management 54

Management Enterprise Modeling Data Quality 54

Alation

APRIL 19, 2022

In that sense, data modernization is synonymous with cloud migration. Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. Consolidating all data across your organization builds trust in the data.

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52