IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

erwin

JULY 12, 2019

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

MARCH 14, 2023

It should make data available, maintain data consistency and accuracy, and support data security. Gartner describes it as ‘ a highly dynamic process employed to support the acquisition, organisation, analysis, and delivery of data in support of business objectives ’. Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

AWS Big Data

MARCH 7, 2023

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. A data hub contains data at multiple levels of granularity and is often not integrated. Let’s look at the components of the architecture in more detail.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

IBM Big Data Hub

JUNE 30, 2022

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. This requires a deep understanding of the organization’s strengths and weaknesses.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

O'Reilly on Data

JULY 28, 2020

Internally, AI PMs must engage stakeholders to ensure alignment with the most important decision-makers and top-line business metrics. Put simply, no AI product will be successful if it never launches, and no AI product will launch unless the project is sponsored, funded, and connected to important business objectives.

Marketing 363

Marketing Experimentation Metrics Testing 363

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