erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

CIO Business Intelligence

FEBRUARY 20, 2025

However, it is often unclear where the data needed for reporting is stored and what quality it is in. Often the data quality is insufficient to make reliable statements. Insufficient or incorrect data can even lead to wrong decisions, says Kastrati.

Big Data 84

Big Data Measurement Visualization Machine Learning 84

erwin

APRIL 29, 2020

Regulatory compliance places greater transparency demands on firms when it comes to tracing and auditing data. For example, capital markets trading firms must understand their data’s origins and history to support risk management, data governance and reporting for various regulations such as BCBS 239 and MiFID II.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

datapine

FEBRUARY 22, 2022

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

SEPTEMBER 24, 2024

Out of the back office The first wave of CDOs and CDAOs focused on back-office tasks such as data governance, data quality, and data management, but people in the positions now need to become more visible by showing how they bring value to the business, Duncan says.

Data Governance 115

Data Governance Risk Management Risk Data Quality 115

erwin

MARCH 25, 2021

Risk Management and Regulatory Compliance. Risk management, specifically around regulatory compliance, is an important use case to demonstrate the true value of data governance. According to Pörschmann, risk management asks two main questions. How likely is a specific event to happen? “You

Data Governance 109

Data Governance Cost-Benefit IT Risk 109

erwin

JANUARY 23, 2025

Data intelligence software is continuously evolving to enable organizations to efficiently and effectively advance new data initiatives. With a variety of providers and offerings addressing data intelligence and governance needs, it can be easy to feel overwhelmed in selecting the right solution for your enterprise.

Metadata 52

Metadata Data Quality Data Governance Software 52

erwin

FEBRUARY 4, 2021

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. Overcoming Data Governance Bottlenecks. Put data quality first : Users must have confidence in the data they use for analytics.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

CIO Business Intelligence

DECEMBER 19, 2023

Third, in the CDO Agenda: 2024: Navigating Data and Generative AI Frontiers , 57% of respondents haven’t changed their data environments to support generative AI. CIOs should look for other operational and risk management practices to complement transformation programs.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

AUGUST 7, 2023

According to Rocket Software’s survey: Only 33% of respondents are extremely confident that they have the right technology/software in place to execute an effective approach to IT risk management. Only 28% of respondents are extremely confident they have the right people in place to execute an effective approach to IT risk management.

Risk 98

Risk IT Management Risk Management 98

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 85

Data Architecture Risk Management Risk Management 85

CIO Business Intelligence

SEPTEMBER 17, 2024

Sponsor for operational and risk management solutions While many business risk areas will find sponsors in operations, finance, and risk management functions, finding sponsors and prioritizing investments to reduce IT risks can be challenging.

Enterprise 145

Enterprise Digital Transformation Cost-Benefit Risk 145

erwin

OCTOBER 24, 2019

Addressing the Complexities of Metadata Management. The complexities of metadata management can be addressed with a strong data management strategy coupled with metadata management software to enable the data quality the business requires. With erwin, organizations can: 1.

Metadata 104

Metadata Management Data-driven Data Architecture 104

erwin

APRIL 4, 2019

Some other common data governance obstacles include: Questions about where to begin and how to prioritize which data streams to govern first. Issues regarding data quality and ownership. Concerns about data lineage. Competing project and resources (time, people and funding).

Data Governance 75

Data Governance Data Quality Risk Management Data-driven 75

Octopai

JANUARY 19, 2020

It will not surprise you to learn all 11 of the bank-relevant principles are related to data in some form or fashion. Here’s a sampling: – Principle 1 covers data governance, including “a firm’s policies on data confidentiality, integrity, and availability, as well as risk-management policies.”.

Metadata 89

Metadata Risk Management Business Intelligence Data Governance 89

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.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Cloudera

JULY 15, 2021

For financial institutions and insurers, risk and exposure management has always been a fundamental tenet of the business. Now, risk management has become exponentially complicated in multiple dimensions. . Attendees included senior risk managers and analytics experts from financial institutions and insurance companies.

Risk 100

Risk Optimization Management Insurance 100

DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. To reference SR 11-7: .

Risk 64

Risk Modeling Machine Learning Data Quality 64

Jet Global

AUGUST 28, 2023

We are eager to offer this additional support to insightsoftware customers, advancing our own capabilities that improve data quality and visibility, and enhance performance.” “This acquisition seamlessly connects insightsoftware’s expertise and product offerings with our extensive visualization library.

Dashboards 75

Dashboards Visualization Finance Data Quality 75

CIO Business Intelligence

APRIL 28, 2022

Its success is one of many instances illustrating how the financial services industry is quickly recognizing the benefits of data analytics and what it can offer, especially in terms of risk management automation, customized experiences, and personalization. .

Analytics 98

Analytics Insurance Big Data Uncertainty 98

IBM Big Data Hub

FEBRUARY 28, 2024

Successful strategic sourcing often results in process optimization, cost management, customer satisfaction, risk management , increased sustainability and other benefits. Sourcing teams are automating processes like data analysis as well as supplier relationship management and transaction management.

Strategy 94

Strategy Technology Cost-Benefit Risk Management 94

CIO Business Intelligence

APRIL 29, 2022

From a policy perspective, the organization needs to mature beyond a basic awareness and definition of data compliance requirements (which typically holds that local operations make data “sovereign” by default) to a more refined, data-first model that incorporates corporate risk management, regulatory and reporting issues, and compliance frameworks.

Digital Transformation 132

Digital Transformation Data-driven Strategy Data Strategy 132

DataRobot Blog

JULY 21, 2022

Inquire whether there is sufficient data to support machine learning. Document assumptions and risks to develop a risk management strategy. Data aggregation such as from hourly to daily or from daily to weekly time steps may also be required. Perform data quality checks and develop procedures for handling issues.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Octopai

JULY 12, 2020

An enormous amount of time was being wasted performing manual searches, as the BI team needed to frequently comb through the enterprise data warehouse’s fields to determine how each was calculated or to find their sources. We now get the benefit of proliferated data quality.” – Andrew Stewardson, Data Risk Manager, FCSA.

Data Warehouse 84

Data Warehouse Data Quality Metadata Risk Management 84

DataRobot

JULY 16, 2021

They all serve to answer the question, “How well can my model make predictions based on data?” In performance, the trust dimensions are the following: Data quality — the performance of any machine learning model is intimately tied to the data it was trained on and validated against.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

CIO Business Intelligence

MAY 15, 2024

This should fall under the responsibility of a company’s risk management team, she says, and the person who makes sure that developers, and the business as a whole, understands there’s a process is the CIO. They’re the ones best positioned to set the culture,” she says.

Modeling 137

Modeling Risk Software Enterprise 137

IBM Big Data Hub

APRIL 20, 2023

This level of visibility also helps ensure that changes made over time don’t introduce new risks into the organization, can make it easier for banks to stay within regulatory guidelines, and helps ensure banks can respond quickly to changing business needs.

Risk 68

Risk Risk Management Reporting Metadata 68

CIO Business Intelligence

SEPTEMBER 2, 2022

As more financial companies embrace the cloud, there’s been an increase in demand for data engineers to help manage AWS and Azure services in the organization. Part of the role also includes continually improving the organization’s technology stack, while maintaining a priority for business continuity and risk management.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

As more financial companies embrace the cloud, there’s been an increase in demand for data engineers to help manage AWS and Azure services in the organization. Part of the role also includes continually improving the organization’s technology stack, while maintaining a priority for business continuity and risk management.

Finance 98

Finance IT Software Reporting 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

IBM Big Data Hub

NOVEMBER 28, 2022

Provide early indicators of data quality. Poor data quality is one of the top barriers faced by organizations aspiring to be data-driven. Most data quality management approaches are reactive, triggered only when consumers complain to data teams about the integrity of datasets.

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

Cloudera

SEPTEMBER 7, 2023

The way to manage this is by embedding data integration, data quality-monitoring, and other capabilities into the data platform itself , allowing financial firms to streamline these processes, and freeing them to focus on operationalizing AI solutions while promoting access to data, maintaining data quality, and ensuring compliance.

Insurance 83

Insurance Risk Data-driven Finance 83

Alation

AUGUST 17, 2022

Data governance policy should be owned by the top of the organization so data governance is given appropriate attention — including defining what’s a potential risk and what is poor data quality.” It comes down to the question: What is the value of your data? Enterprise risk management.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

Alation

JUNE 14, 2021

Do we know the business outcomes tied to data risk management? Once you have data classification then you can talk about whether you need to tokenize and why, or anonymize and why, or encrypt and why, etc.” These are essential to enabling a more rapid process of sensitive data discovery. What am I required to do?

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Metadata 97

Ontotext

APRIL 21, 2021

The problem was the left hand had no way of knowing the systemic issues around data governance, risk management and compliance framework. One of the biggest, and costly failures, was the inability to produce reports for management and regulatory agencies.

Metadata 59

Metadata Finance Cost-Benefit Data Quality 59