AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Then, you transform this data into a concise format.

Data Strategy 103

Data Strategy Strategy Data Warehouse Prescriptive Analytics 103

Ontotext

JULY 12, 2024

We offer two different PowerPacks – Agile Data Integration and High-Performance Tagging. The High-Performance Tagging PowerPack bundle The High-Performance Tagging PowerPack is designed to satisfy taxonomy and metadata management needs by allowing enterprise tagging at a scale.

Enterprise 59

Enterprise Cost-Benefit Metadata Data Integration 59

Wayne Yaddow

FEBRUARY 18, 2025

Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis. To achieve these needs, data engineers and data scientists must use rigorous testing frameworks that are tailored to the unique problems given by each process.

Testing 52

Testing Data Transformation Data-driven Data Quality 52

IBM Big Data Hub

JANUARY 5, 2023

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

Ontotext

MAY 16, 2024

This includes defining the underlying drivers (cost containment, process automation, flexible query, regulatory compliance, governance simplification) and prioritizing use cases (data integration, digitalization, enterprise search, lineage traceability, cybersecurity, access control).

Enterprise 52

Enterprise Data-driven Cost-Benefit Business Objectives 52

Alation

FEBRUARY 10, 2022

Let’s discuss what data classification is, the processes for classifying data, data types, and the steps to follow for data classification: What is Data Classification? Either completed manually or using automation, the data classification process is based on the data’s context, content, and user discretion.

Data Governance 52

Data Governance Risk Insurance Business Objectives 52

AWS Big Data

OCTOBER 24, 2024

This will import the metadata of the datasets and run default data discovery. Tag the data fields Immuta automatically tags the data members using a default framework. Industry use cases The following are example industry use cases where Immuta and Amazon Redshift integration adds value to customer business objectives.

Data Warehouse 111

Data Warehouse Business Objectives Data-driven Management 111

Ontotext

AUGUST 21, 2024

data integration, digitalization, enterprise search, lineage traceability, cybersecurity, access control). The opportunities exist when you gain the trust across stakeholders that there is a path to ensure that data is true to original intent, defined at a granular level and in a format that is traceable, testable, and flexible to use.

Knowledge Discovery 52

Knowledge Discovery Cost-Benefit Data-driven Metadata 52