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 Quality 52

Data Quality Data Architecture Strategy Data Lake 52

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. Nine Steps to Data Modeling.

Modeling 98

Modeling Metadata Data Governance Visualization 98

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 Digital Transformation 52

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. Then, you transform this data into a concise format. Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

Data Strategy 71

Data Strategy Strategy Data Warehouse Prescriptive Analytics 71

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 Strategy 52

erwin

NOVEMBER 6, 2020

Prashant Parikh, erwin’s Senior Vice President of Software Engineering, talks about erwin’s vision to automate every aspect of the data governance journey to increase speed to insights. Although AI and ML are massive fields with tremendous value, erwin’s approach to data governance automation is much broader.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97