Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

erwin

APRIL 21, 2020

By combining physical system catalogs, critical data elements, and key performance measures with clearly defined product and sales goals, you can manage the effectiveness of your business and ensure you understand what critical systems are for business continuity and measuring corporate performance.

Measurement 97

Measurement Sales Data Governance Metadata 97

erwin

APRIL 21, 2020

One of the biggest lessons we’re learning from the global COVID-19 pandemic is the importance of data, specifically using a data catalog to comply, collaborate and innovate to crisis-proof our businesses. So one of the biggest lessons we’re learning from COVID-19 is the need for data collection, management and governance.

Measurement 96

Measurement Sales Data Governance Metadata 96

Grooper

OCTOBER 23, 2019

By measuring performance, they drive improvements through necessary process and workflow changes. It simply takes the right resources and a measured approach to get there. Most companies today are more reactive to information governance. As Peter Drucker so famously said, “If you can’t measure it, you can’t improve it.”

Metrics 59

Metrics Measurement Strategy Optimization 59

Alation

DECEMBER 8, 2022

Data governance is growing in urgency and prominence. As regulations grow more complex (and compliance fines more onerous) organizations aren’t just adapting data governance frameworks to drive compliance – they’re leveraging governance to fuel a growing range of use cases, from collaboration to stewardship, discovery, and more.

Data Governance 52

Data Governance Data-driven Strategy Risk 52

AWS Big Data

AUGUST 14, 2023

In the same way, overly restrictive data governance practices that either prevent data products from taking root at all, or pare them back too aggressively (deforestation), can over time create “data deserts” that drive both the producers and consumers of data within an organization to look elsewhere for their data needs.

Management 75

Management Risk Measurement Optimization 75

Laminar Security

MAY 3, 2023

They define DSPM technologies this way: “DSPM technologies can discover unknown data and categorize structured and unstructured data across cloud service platforms. Start by using DSG to establish the data security policies and posture, and then take the final three steps to assess the DSPM deployment.”

Management 52

Management Risk Risk Management Data Processing 52

Andrew White

JANUARY 11, 2021

What are you seeing as the differences between a Chief Analytics Officer and the Chief Data Officer? Governance. Value Management or monetization. Risk Management (most likely within context of governance). Product Management. measuring value, prioritizing (where to start), and data literacy?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52