erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Data Governance Bottlenecks. Regulations.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

CIO Business Intelligence

MARCH 19, 2025

Yet, while businesses increasingly rely on data-driven decision-making, the role of chief data officers (CDOs) in sustainability remains underdeveloped and underutilized. Most data management conferences and forums focus on AI, governance and security, with little emphasis on ESG-related data strategies.

IT 59

IT Data Governance Data-driven Metrics 59

datapine

FEBRUARY 22, 2022

This includes defining the main stakeholders, assessing the situation, defining the goals, and finding the KPIs that will measure your efforts to achieve these goals. A planned BI strategy will point your business in the right direction to meet its goals by making strategic decisions based on real-time data.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

CIO Business Intelligence

SEPTEMBER 24, 2024

Chief data and analytics officers need to reinvent themselves in the age of AI or risk their responsibilities being assimilated by their organizations’ IT teams, according to a new Gartner report. In many cases, the CDOs have been hired for the skill set of data governance,” he adds.

Data Governance 115

Data Governance Risk Management Risk Data Quality 115

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 Reporting Strategy 52

erwin

DECEMBER 20, 2018

The driving factors behind data governance adoption vary. Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. Defining Data Governance.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

Cloudera

FEBRUARY 15, 2024

From stringent data protection measures to complex risk management protocols, institutions must not only adapt to regulatory shifts but also proactively anticipate emerging requirements, as well as predict negative outcomes. This results in enhanced efficiency in compliance processes.

Insurance 88

Insurance Data Architecture Risk Management Risk 88

Octopai

JULY 9, 2020

By adopting automated data lineage and automated metadata tagging, companies have the opportunity to increase their data processing speed. That increase can manage huge endeavors, such as migrations, error location, and new data governance integrations which then become “routine” operations.

Insurance 98

Insurance Risk Management Machine Learning Metadata 98

Octopai

JUNE 19, 2023

Everyone has access to the same data and the same understanding of what the data represents, reducing miscommunications and discrepancies. Catalogs also allow for better Risk Management; data catalogs help businesses maintain regulatory compliance by providing a clear record of what data is stored and how it’s used.

Metadata 98

Metadata Data Governance Measurement Risk Management 98

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

CIO Business Intelligence

APRIL 29, 2022

The strategy should put formalized processes in place to quantify the value of different types of information, leveraging the skills of a chief data officer (CDO), who should form and chair a data governance committee. CIOs measure technical debt against the value of their entire technology estate.

Digital Transformation 132

Digital Transformation Data-driven Strategy Data Strategy 132

Laminar Security

DECEMBER 22, 2023

Implementing DSPM for cost reduction Effective implementation of Data security posture management (DSPM) can drive significant cost reductions in cloud storage by addressing three critical areas: risk management, access governance, and compliance. Data Access Governance (DAG) is pivotal for storage optimization.

Cost-Benefit 95

Cost-Benefit Risk Optimization Risk Management 95

CIO Business Intelligence

MARCH 25, 2022

Policy makers around the world have been recognizing this heightened risk, which has been further amplified by the recent geopolitical tensions. The European Union (EU) has pulled together a proposal for a unified framework to regulate risk management for financial institutions.

Finance 98

Finance KPI Risk IoT 98

IBM Big Data Hub

MAY 28, 2024

While every data protection strategy is unique, below are several key components and best practices to consider when building one for your organization. What is a data protection strategy? Its principles are the same as those of data protection—to protect data and support data availability.

Strategy 81

Strategy Measurement Risk Cost-Benefit 81

IBM Big Data Hub

DECEMBER 14, 2023

While the need for reliable, resilient, recoverable and corruption-free data governance has long been achieved by a backup and recovery routine, more modern techniques have been developed to support proactive measures that protect against threats before they occur. Cyber resiliency goes beyond mere cybersecurity measures.

Risk 78

Risk Measurement Business Objectives Optimization 78

IBM Big Data Hub

JUNE 29, 2023

Continuous monitoring and performance management Integrated Business Planning is an ongoing process that requires continuous monitoring of performance against plans and targets. Key performance indicators (KPIs) are established to measure progress and enable proactive management.

Key Performance Indicator 76

Key Performance Indicator Forecasting Sales Data Integration 76

Cloudera

MARCH 25, 2021

Will the data privacy controls ultimately help create an enterprise approach to data? Data lies at the heart of knowing the customer and enabling a better customer experience. Risk management can be optimized by the improved use of data and analytics to run models, account for more variables and scrutinize probable outcomes.

Data Strategy 65

Data Strategy Strategy Enterprise Insurance 65

CIO Business Intelligence

MAY 30, 2023

Other top 10 initiatives seeing increased CIO involvement include the related areas of data privacy and compliance (at No. 3, with 55% of responding IT leaders listing this area) and risk management (at No. 9, with 47% involved in such). It’s a shift in emphasis that makes all the difference.

IT 131

IT Risk Optimization Technology 131

CIO Business Intelligence

DECEMBER 9, 2024

Finally, Indias thriving start-up ecosystem, coupled with government initiatives such as Startup India, is increasingly focused on AI innovation across sectors like healthcare, agriculture, education, and fintech, and that investment infrastructure will directly result in further acceleration in both AI creation and adoption.

Data Governance 52

Data Governance Data-driven Risk Digital Transformation 52

IBM Big Data Hub

MARCH 26, 2024

While ESG seeks to provide standard methods and approaches to measuring across environmental, social and governance KPIs, and holds organizations accountable for that performance, sustainability is far broader. Sustainability and ESG: An opportunity for synergy Sustainability and ESG are not synonymous.

Measurement 60

Measurement Metrics Strategy Reporting 60

Alation

MARCH 24, 2022

Data security, on the other hand, focuses on unauthorized access to data. In this blog, we’ll compare and contrast data privacy and security, and make the case that both are essential and complementary for an effective data governance program. What Is Data Privacy? Privacy measures prevent internal threats.

Data Governance 52

Data Governance Risk Data-driven Measurement 52

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

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 98

Management Risk Measurement Optimization 98

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 Data-driven Strategy 59

Alation

MARCH 14, 2023

All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Some business processes may need reviewing to include data analysis — even going as far as requiring specific data to make a business decision.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

FineReport

APRIL 9, 2024

Financial Services Optimization : In the financial services sector, a major institution leveraged a sophisticated BI platform to analyze market trends, customer behavior, and risk management strategies. This framework ensures that data remains accurate, consistent, and secure across all levels of the organization.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

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 40

Management Risk Risk Management Data Processing 40

IBM Big Data Hub

JULY 7, 2023

Best practices for proactive data security Best cybersecurity practices mean ensuring your information security in many and varied ways and from many angles. Here are some data security measures that every organization should strongly consider implementing. Define sensitive data. Manage third-party-related risks.

Risk 40

Risk Data Governance Data Lake Data-driven 40

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

CIO Business Intelligence

MARCH 5, 2025

The EU AI Act introduces a strict legal framework with a detailed classification of AI risks and mandatory requirements for high-risk systems, which is more prescriptive than NISTs voluntary framework or the UKs principles-based approach. Emphasizes governance and risk management similar to the EU AI Act and Canadas Bill C-27.

Risk 121

Risk Risk Management Measurement Modeling 121

CIO Business Intelligence

OCTOBER 2, 2024

Data governance Strong data governance is the foundation of any successful AI strategy. It’s essential to regularly audit your AI systems to detect and mitigate biases in data collection, algorithm design and decision-making processes.

Gap analysis 119

Gap analysis Risk Manufacturing Data Governance 119

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Governance 101.

Insurance 150

Insurance Risk IoT Data-driven 150

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

IBM Big Data Hub

MAY 14, 2024

Many federal agencies are appointing CAIOs to oversee AI use within their domains, promote responsible AI innovation and address risks associated with AI, including generative AI (gen AI), by considering its impact on citizens. But, how will these CAIOs balance regulatory measures and innovation? How will they cultivate trust?

Risk 83

Risk Risk Management Measurement Strategy 83

CIO Business Intelligence

MAY 29, 2024

Measuring impacts is about more than how well a model functions in a laboratory setting,” Schwartz said. Reva Schwartz, NIST Information Technology Lab’s ARIA program lead, spoke of the criticality of testing AI functions in controlled laboratory settings and applying real-world factors.

Risk 130

Risk Testing Interactive Technology 130

CIO Business Intelligence

FEBRUARY 13, 2025

Ethics and governance in AI AI also challenges organizations to address algorithmic bias, transparency and accountability issues. Regulatory frameworks like the EU AI Act and NIST AI Risk Management Framework are shaping expectations around responsible AI deployment. Data governance gaps. Complementary solutions.

Risk 116

Risk Data-driven Finance Risk Management 116