erwin

JULY 12, 2019

With all the advance notice and significant chatter for GDPR/CCPA, why aren’t organizations more prepared to deal with data regulations? The complexity of regulatory requirements in and of themselves is aggravated by the complexity of the business and data landscapes within most enterprises. Complexity. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

IBM Big Data Hub

NOVEMBER 28, 2022

How do you keep pace with growing data volumes and increased demand from data consumers and deliver real-time data governance for trusted outcomes? It is imperative to evolve metadata management approaches to keep pace with the proliferation of enterprise data. Provide early indicators of data quality.

Metadata 57

Metadata Data Quality Data-driven Data Governance 57

Jet Global

AUGUST 28, 2023

It also complements insightsoftware’s previous acquisition of Power ON , and extends write-back : the ability to update source data in enterprise databases directly onto the Qlik platform. With this deal, insightsoftware can provide Qlik users with powerful new capabilities to supercharge operational planning, reporting, and analytics.

Dashboards 75

Dashboards Visualization Finance Data Quality 75

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Regulatory compliance places greater transparency demands on firms when it comes to tracing and auditing data.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Ontotext

SEPTEMBER 1, 2023

Enterprises worldwide are analyzing Generative AI capabilities and seeking ways to leverage them for a variety of use cases to improve their competitive edge and incorporate automation and efficiency. Additionally, data is the fulcrum of AI, and the data used to train LLMs must be properly governed and controlled.

Risk 52

Risk Modeling Data Quality Data Governance 52

Alation

AUGUST 17, 2022

We’ve seen the emergence of new, less invasive approaches, yet the question remains: What do CIOs think is most required to deliver a successful data governance program? The Risks of Early Data Governance Programs. The biggest risk was a lack of ownership. If your definitions are bad, so is your governance/risk/security.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. Changing the game with knowledge graphs So how does knowledge graph technology help enterprises in the Financial Services Industry become data-driven?

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

CIO Business Intelligence

MARCH 24, 2023

Overcoming data challenges Despite their growing commitment to ESG, financial firms have learned the path to sustainability and prosperity can be rocky. “ESG ESG data quality is the biggest challenge. revenue growth from businesses showing a lower commitment to ESG.

Risk Management 52

Risk Management Consulting Metrics Data Quality 52

CIO Business Intelligence

APRIL 29, 2022

The data-first transformation journey can appear to be a lengthy one, but it’s possible to break it down into steps that are easier to digest and can help speed you along the pathway to achieving a modern, data-first organization. Key features of data-first leaders. 5x more likely to be highly resilient in terms of data loss.

Digital Transformation 132

Digital Transformation Strategy Data-driven Data Strategy 132

Ontotext

APRIL 21, 2021

Ontotext clients have used enterprise knowledge graphs to ensure inventory control is done in an intelligent and automated way. Inventory here refers to the vast amounts of information and data that financial institutions need on a daily basis, which are core assets to the business. Manage Regulation, Manage Risk.

Metadata 59

Metadata Finance Cost-Benefit Data Quality 59

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. 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.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

O'Reilly on Data

JULY 15, 2019

After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Model risk management. AI projects in financial services and health care.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

Octopai

JUNE 19, 2023

Data Catalogs also allow for Improved Collaboration by serving as a central repository for enterprise data, a data catalog facilitates collaboration among different teams. Everyone has access to the same data and the same understanding of what the data represents, reducing miscommunications and discrepancies.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

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

erwin

SEPTEMBER 17, 2020

It’s paramount that organizations understand the benefits of automating end-to-end data lineage. Critically, it makes it easier to get a clear view of how information is created and flows into, across and outside an enterprise. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

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.” Intelligent systems powered by machine learning are necessary for overcoming the challenges of data management.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

FineReport

MARCH 24, 2024

Their role extends to managing information for corporate decision-making, improving reporting systems , and performing complex analyses. Additionally, they facilitate organizational risk assessments, provide consulting services to leadership, and mentor junior analysts. The business department can view reports or update data fillings.

Statistics 52

Statistics Data mining Visualization Reporting 52

Sisense

SEPTEMBER 3, 2020

As you can imagine, data scientists with all these aptitudes can be of considerable value to their employers. They are the link between the data resources available to an enterprise and executives looking for opportunities to make the business better, faster, and stronger. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

Cloudera

FEBRUARY 14, 2018

operations, and our CISO’s team while we invest in and form a stronger data and analytics team. their customer insights, connected products, risk mitigation). Mitigate risk to Cloudera’s business – for example in the area of Cybersecurity, and to ensure compliance with regulatory and consumer privacy policies and concerns.

Data-driven 43

Data-driven Data Quality Risk Interactive 43

Smart Data Collective

SEPTEMBER 25, 2019

However, according to a 2018 North American report published by Shred-It, the majority of business leaders believe data breach risks are higher when people work remotely. Whether you work remotely all the time or just occasionally, data encryption helps you stop information from falling into the wrong hands.

Technology 86

Technology Statistics Strategy Insurance 86

Cloudera

SEPTEMBER 7, 2023

But it’s also fraught with risk. This June, for example, the European Union (EU) passed the world’s first regulatory framework for AI, the AI Act , which categorizes AI applications into “banned practices,” “high-risk systems,” and “other AI systems,” with stringent assessment requirements for “high-risk” AI systems.

Insurance 81

Insurance Risk Data-driven Finance 81

erwin

FEBRUARY 4, 2021

While acknowledging that data governance is about more than risk management and regulatory compliance may indicate that companies are more confident in their data, the data governance practice is nonetheless growing in complexity because of more: Data to handle, much of it unstructured. Sources, like IoT.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

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. Large projects or those involving text, images, or streaming data may need specialized infrastructure. Reshape and aggregate data as necessary. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. Addressing the Complexities of Metadata Management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

erwin

APRIL 4, 2019

A strong data governance framework is central to the success of any data-driven organization because it ensures this valuable asset is properly maintained, protected and maximized. But despite this fact, enterprises often face push back when implementing a new data governance initiative or trying to mature an existing one.

Data Governance 75

Data Governance Data Quality Risk Management Data-driven 75

IBM Big Data Hub

DECEMBER 4, 2023

By implementing Oracle , one of the world’s leading enterprise resource planning (ERP) tools, organizations can transform their business processes and significantly increase operational efficiency. Companies large and small are increasingly digitizing and managing vast troves of data.

Testing 82

Testing Consulting Digital Transformation Cost-Benefit 82

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Octopai

JULY 12, 2020

Like many BI teams, FCSA’s struggles began with the massive amount of data that existed in their enterprise data warehouse. Perhaps most frustrating for FCSA was the major data-quality issues that arose due to manual, error-prone data processing. Think of the wonders it could work for your enterprise.

Data Warehouse 58

Data Warehouse Data Quality Metadata Risk Management 58

Cloudera

JANUARY 22, 2019

In conjunction with the evolving data ecosystem are demands by business for reliable, trustworthy, up-to-date data to enable real-time actionable insights. Big Data Fabric has emerged in response to modern data ecosystem challenges facing today’s enterprises. What is Big Data Fabric? Source: Cloudera.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

datapine

AUGUST 29, 2022

The book has three main ideas: The biggest risk your company faces is investing a lot of time and resources into building something that the market doesn’t want. and this book will give you an insight into their data collecting procedures and the reasons behind them. Product/market fit is THE most important factor to get right.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

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 Key Performance Indicator 218

Alation

NOVEMBER 23, 2021

Organizations don’t need to spend a lot of money to get data governance. They can improve data quality, security and risk management without the need for an expensive big-bang project. What organizations actually govern is data-consumer behavior, and not the data itself. Creates Shared Processes.

Data Governance 52

Data Governance Data-driven Data Processing Consulting 52

AWS Big Data

AUGUST 14, 2023

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. When do new data products get created, and who is allowed to create them?

Management 79

Management Risk Measurement Optimization 79

Andrew White

JANUARY 11, 2021

What is your vision for D&A for small and medium enterprises? We have specific research for midsize and small enterprises. See 3 Questions That Midsize Enterprises Should Ask About Data and Analytics and have an inquiry with Alan Duncan. Which industry, sector moves fast and successful with data-driven?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

MAY 9, 2024

Data pipelines can serve various purposes beyond ETL, such as real-time analytics, machine learning, and stream processing applications. ETL pipelines are designed to prepare data for analysis, reporting, or other business intelligence applications. What is an ETL pipeline? How is ELT different from ETL?

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52