DataRobot

AUGUST 18, 2021

Note that DataRobot also automatically runs Data Quality Assessments on the dataset to identify and remedy potential data quality issues. To request a fraud detection demo shown in this blog post, contact us and we’ll explore a proof of value together. Request a Demo. See DataRobot in Action.

Machine Learning 52

Machine Learning Data Quality Modeling Sales 52

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 Data Governance Key Performance Indicator Data Quality 111

Jet Global

APRIL 9, 2023

More than a quarter of professionals reported that incorrect data had been manually input into an enterprise system at their firms. This highlights the pressing need to automate and streamline processes to reduce manual data entry and mitigate risk of error. Increase security and reduce risk.

Reporting 52

Reporting Finance Risk Data Quality 52

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. Strengthen data security. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

APRIL 16, 2021

For a fully mature or “enhanced” data governance program, IT and the business need to take responsibility for selling the benefits of data governance across the enterprise and ensure all stakeholders are properly educated about it. Whatever your motivation, you need to identify it first and foremost to get a grip on data governance.

Data Governance 128

Data Governance Metadata Cost-Benefit Digital Transformation 128

Alation

AUGUST 9, 2022

But almost all industries across the world face the same challenge: they aren’t sure if their data is accurate and consistent, which means it’s not trustworthy. This can cause anything from day-to-day issues to significant business problems and risks. Many confuse data integrity with data quality.

Data Integration 52

Data Integration Data Quality Measurement Strategy 52

erwin

DECEMBER 3, 2020

Ultra Mobile recently shared how it uses erwin Data Intelligence (erwin DI) as part of a modern, ongoing approach to data governance and therefore control versus chaos. To manage not only risk but also to grow and compete effectively requires the ability to deal with both planned and unplanned change.

Metadata 141

Metadata Data Governance Data-driven Digital Transformation 141

erwin

JANUARY 11, 2019

It’s only when companies take their first stab at manually cataloging and documenting operational systems, processes and the associated data, both at rest and in motion, that they realize how time-consuming the entire data prepping and mapping effort is, and why that work is sure to be compounded by human error and data quality issues.

Data Governance 40

Data Governance Risk Metadata Management 40

Jet Global

MARCH 4, 2024

Moving data across siloed systems is time-consuming and prone to errors, hurting data quality and reliability. This eliminates the risk of errors associated with manual tagging, ensuring the accuracy and efficiency of your filings. Let us be your finger on the pulse.

Reporting 52

Reporting Data-driven Software Risk 52

Jet Global

MAY 9, 2024

ETL pipelines are commonly used in data warehousing and business intelligence environments, where data from multiple sources needs to be integrated, transformed, and stored for analysis and reporting. Data pipelines enable data integration from disparate healthcare systems, transforming and cleansing the data to improve data quality.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

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. Request a demo.

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

erwin

JULY 22, 2020

The company needed to help its data scientists and engineers improve their knowledge of the data, find the best data for use at the best time, and put the data in the most appropriate business context. Becoming a data-driven enterprise means making decisions based on facts. As an example, E.ON Avoiding Hurdles.

Data-driven 136

Data-driven Data Governance Digital Transformation Enterprise 136

DataRobot

JUNE 1, 2021

In an earlier post, I shared the four foundations of trusted performance in AI : data quality, accuracy, robustness and stability, and speed. You should first identify potential compliance risks, with each additional step again tested against risks. Request a Demo. AI You Can Trust.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

Laminar Security

DECEMBER 1, 2023

Cloud data security is one of the most critical, yet most challenging aspects of doing business in the age of cloud. As more organizations migrate their data to the cloud, they face an increasing range of risks and threats, including data breaches, data leakage, data loss, data misuse, data compliance violations, shadow data and more.

Modeling 52

Modeling Cost-Benefit Risk Data-driven 52

Alation

FEBRUARY 14, 2023

In this day and age, regardless of industry, keeping data protected and its uses understood is vital. No business wants to have the PR nightmare of a data leak or personal data being used without the correct permissions. This is where successful data governance programs can act as a savior to many organizations.

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. AI doesn’t fit that model.

Management 327

Management Machine Learning Experimentation Metrics 327

erwin

DECEMBER 12, 2019

Is it sensitive or are there any risks associated with it? The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Alation

NOVEMBER 11, 2021

This framework maintains compliance and democratizes data. It enables collaboration, even as your data landscape grows larger and more complex. Active data governance improves efficiency, minimizes security risks, and improves the quality and usability of data. Data Sovereignty and Cross?Border

Data Governance 52

Data Governance Data Quality Metrics Metadata 52

Jet Global

MAY 6, 2024

No more wrestling with codes or hunting for information – you can access data in clear terms, building towards a future where your team is empowered to leverage AI tools for tasks like automated reports, forecasting future trends, or identifying potential risks.

Data-driven 52

Data-driven Finance Data Quality Reporting 52

IBM Big Data Hub

DECEMBER 7, 2023

Slice-and-dice analysis : OLAP allows users to slice and dice data along various dimensions, isolating specific segments for in-depth analysis. Improved decision-making Strategic planning and forecasting : OLAP helps businesses identify trends, patterns and potential risks, enabling better strategic planning and forecasting.

OLAP 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

Alation

JUNE 23, 2023

This enhanced partnership allows users to gain a deeper comprehension of their data environment , enabling them to observe the fundamental modifications and transformations within their data, ultimately empowering them with invaluable data intelligence. Join us at Summit! When: Thursday, June 29, at 11:30 p.m.

Data-driven 52

Data-driven Data Processing Data Quality Enterprise 52

IBM Big Data Hub

JULY 27, 2023

Request a demo to see how watsonx can put AI to work There’s no AI, without IA AI is only as good as the data that informs it, and the need for the right data foundation has never been greater. This application can produce value for an enterprise, but it also poses risk.

Management 55

Management Enterprise Modeling Data Quality 55

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 77

Cost-Benefit Metadata Optimization Management 77

Alation

MARCH 14, 2023

Some business processes may need reviewing to include data analysis — even going as far as requiring specific data to make a business decision. Govern Data governance models should be flexible and dynamic while proactively addressing risk management and compliance with local and global regulations.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Alation

MARCH 28, 2023

Central to this is a uniform technology architecture, where individuals can access and interpret data for organisational benefit. Standardisation will also ensure easy reuse of data, by storing it consistently, with a single, authoritative source. Enduring data Data is an enduring asset and capability, not just a resource.

Metadata 52

Metadata Data Strategy Data Quality Strategy 52

Jet Global

OCTOBER 4, 2023

. • Finance teams may find it challenging to gain insights from disparate data sources, hindering their ability to identify trends, risks, and opportunities on time. Addressing these challenges often requires investing in data integration solutions or third-party data integration tools.

Finance 52

Finance Reporting Cost-Benefit Management 52

erwin

MARCH 4, 2021

Modern data governance is a strategic, ongoing and collaborative practice that enables organizations to discover and track their data, understand what it means within a business context, and maximize its security, quality and value. You can request a demo of erwin Data Intelligence here. Join us March 15 at 10 a.m.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Alation

JUNE 17, 2021

Lastly, active data governance simplifies stewardship tasks of all kinds. Tehnical stewards have the tools to monitor data quality, access, and access control. A compliance steward is empowered to monitor sensitive data and usage sharing policies at scale. Sign up for a weekly demo today.

Data Governance 98

Data Governance Data Lake Insurance Enterprise 98

Alation

MARCH 21, 2023

Data security The travel industry collects, transmits, processes, and stores a wide range of personally identifiable information (PII) from customers, which are of interest to bad actors, as cybercriminals target this valuable data. Otherwise, they risk a data privacy violation. Curious to see Alation in action?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 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. Request your own demo of erwin DI to see metadata-driven, automated data lineage in action.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Alation

OCTOBER 12, 2021

There are inconsistent definitions and inconsistent metrics, and a lack of trust in the data used in the metrics. The fourth challenge was around using the data. There was a real lack of confidence in using the data and the risk of using the wrong data. Time spent managing data. Set consistent data policies.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

erwin

APRIL 15, 2020

In our businesses, it is vital that we work to develop a deeper understanding of the sources, methods and quality of incoming third-party data. This deeper understanding will help us make better decisions about the risks and rewards of using that external data. Data Governance Methods for Data Distancing.

Data Governance 134

Data Governance Metadata Testing Reporting 134

erwin

DECEMBER 12, 2019

Is it sensitive or are there any risks associated with it? The Role of Metadata in Data Governance. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Jet Global

OCTOBER 27, 2020

For many organizations, exception reporting serves as a mechanism for alerting management when the organization is at risk of missing key performance targets. Data Quality. According to Gartner , poor data quality costs the average company about $15 million each year. That can lead to further data quality problems.

Reporting 52

Reporting Data Quality Cost-Benefit Sales 52

Alation

APRIL 27, 2022

Organizations that do not embrace data culture risk lost revenue and competitive disruption. Taken together, these findings show the revenue growth risk for enterprises that have not yet invested in building a data culture. Get the full report here: Q1 2022 State of Data Culture Report. Join a weekly live demo.

Reporting 52

Reporting Data-driven Digital Transformation Data Governance 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52