Cloudera

JUNE 29, 2023

Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs. Thus identifying trends that may impact liquidity and take preemptive action to manage their position.

Data Architecture 84

Data Architecture Risk Management Risk Management 84

erwin

APRIL 29, 2020

Data is crucial to every organization’s survival. For that reason, businesses must think about the flow of data across multiple systems that fuel organizational decision-making. For example, the marketing department uses demographics and customer behavior to forecast sales. Who are the data owners? Data Governance.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Octopai

JANUARY 19, 2020

The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks. It will not surprise you to learn all 11 of the bank-relevant principles are related to data in some form or fashion.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

Alation

MARCH 14, 2023

Data gathering and use pervades almost every business function these days — and it’s widely acknowledged that businesses with a clear strategy around data are best placed to succeed in competitive, challenging markets such as defence. Curate Data must be packaged in a way users can access and understand.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

erwin

SEPTEMBER 17, 2020

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry. Automating data capture frees up resources to focus on more strategic and useful tasks.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Ontotext

APRIL 21, 2021

That lack of dexterity in the competitive market of finance will hamper the company for years after the lawsuits are over. The problem was the left hand had no way of knowing the systemic issues around data governance, risk management and compliance framework. The lost cash and fines were only part of the problem.

Metadata 59

Metadata Finance Cost-Benefit Data Quality 59