erwin

FEBRUARY 13, 2020

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. Data Governance Attitudes Are Shifting. Data Governance Attitudes Are Shifting.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 122

Data Governance Unstructured Data Metadata Data Lake 122

AWS Big Data

AUGUST 15, 2024

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.

Data Quality 111

Data Quality Visualization Metadata Key Performance Indicator 111

AWS Big Data

JANUARY 15, 2025

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

IoT 110

IoT Machine Learning Metadata Data-driven 110

Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

Octopai

JUNE 26, 2020

In order to figure out why the numbers in the two reports didn’t match, Steve needed to understand everything about the data that made up those reports – when the report was created, who created it, any changes made to it, which system it was created in, etc. Enterprise data governance. Metadata in data governance.

Metadata 98

Metadata Data Governance Enterprise Reporting 98

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

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

AWS Big Data

NOVEMBER 22, 2024

This setup supports agile data processing while taking advantage of the serverless architecture of Athena to keep operational costs low. Compliance and data governance – For organizations managing sensitive or regulated data, you can use Athena and the adapter to enforce data governance rules.

Data Lake 100

Data Lake Data Warehouse Cost-Benefit Data Transformation 100

David Menninger's Analyst Perspectives

JUNE 12, 2019

Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security.

Management 270

Management Data Quality Data Integration Data Lake 270

IBM Big Data Hub

JUNE 22, 2020

IBM Watson Knowledge Catalog (WKC) provides a modern machine learning (ML) catalog for data discovery, data cataloging, data quality, and data governance.

Machine Learning 97

Machine Learning Data Governance Data Quality Enterprise 97

IBM Big Data Hub

JANUARY 23, 2023

If you’re in charge of managing data at your organization, you know how important it is to have a system in place for ensuring that your data is accurate, up-to-date, and secure. That’s where data governance comes in. What exactly is data governance and why is it so important?

Data Governance 69

Data Governance Data Quality Management IT 69

IBM Big Data Hub

MAY 9, 2024

The healthcare industry faces arguably the highest stakes when it comes to data governance. For starters, healthcare organizations constantly encounter vast (and ever-increasing) amounts of highly regulated personal data. healthcare, managing the accuracy, quality and integrity of data is the focus of data governance.

Data Governance 66

Data Governance Data Quality Insurance Predictive Analytics 66

erwin

MARCH 8, 2019

GDPR) and to ensure peak business performance, organizations often bring consultants on board to help take stock of their data assets. This sort of data governance “stock check” is important but can be arduous without the right approach and technology. That’s where data governance comes in ….

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

Smart Data Collective

DECEMBER 21, 2022

Big data technology has helped businesses make more informed decisions. A growing number of companies are developing sophisticated business intelligence models, which wouldn’t be possible without intricate data storage infrastructures. One of the biggest issues pertains to data quality.

Business Analytics 130

Business Analytics Analytics Data Quality Big Data 130

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage).

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

JUNE 12, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

Data Quality 63

Data Quality Data Governance People Analytics Data-driven 63

Alation

AUGUST 5, 2021

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

Data Quality 52

Data Quality IT Data Governance Sales 52

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 109

Data Architecture Optimization Data Warehouse Metadata 109

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Analytics 52

IBM Big Data Hub

NOVEMBER 4, 2022

Data is the new oil and organizations of all stripes are tapping this resource to fuel growth. However, data quality and consistency are one of the top barriers faced by organizations in their quest to become more data-driven. Unlock quality data with IBM. and its leading data observability offerings.

Data Quality 56

Data Quality Metadata Data Governance Data-driven 56

AWS Big Data

DECEMBER 9, 2024

As organizations process vast amounts of data, maintaining an accurate historical record is crucial. History management in data systems is fundamental for compliance, business intelligence, data quality, and time-based analysis. Hes passionate about helping customers use Apache Iceberg for their data lakes on AWS.

Snapshot 64

Snapshot Data Warehouse Data Lake Data Quality 64

IBM Big Data Hub

AUGUST 2, 2023

However, analytics are only as good as the quality of the data, which aims to be error-free, trustworthy, and transparent. According to a Gartner report , poor data quality costs organizations an average of USD $12.9 What is data quality? Data quality is critical for data governance.

Data Quality 60

Data Quality Snapshot Data Governance Data-driven 60

CIO Business Intelligence

JUNE 24, 2024

These 10 strategies cover every critical aspect, from data integrity and development speed, to team expertise and executive buy-in. Data done right Neglect data quality and you’re doomed. It’s simple: your AI is only as good as the data it learns from. Big data is seductive, but more isn’t better if it’s garbage.

Data Quality 124

Data Quality ROI Data Integration Metrics 124

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

IBM Big Data Hub

AUGUST 23, 2023

Because of this, when we look to manage and govern the deployment of AI models, we must first focus on governing the data that the AI models are trained on. This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. and watsonx.data.

Data Governance 52

Data Governance Enterprise Modeling Risk 52

erwin

APRIL 11, 2019

Fortunately, whenever the time comes, the first point of call will always be data governance, so organizations can prepare. Effective compliance with new data protection regulations requires a robust understanding of the “what, where and who” in terms of data and the stakeholders with access to it (i.e., employees).

Data-driven 100

Data-driven Insurance Data Governance Metadata 100

IBM Big Data Hub

JANUARY 25, 2023

In our last blog , we introduced Data Governance: what it is and why it is so important. In this blog, we will explore the challenges that organizations face as they start their governance journey. Organizations have long struggled with data management and understanding data in a complex and ever-growing data landscape.

Data Governance 52

Data Governance Data-driven Strategy Data Architecture 52

AWS Big Data

AUGUST 15, 2024

This streamlined architecture approach offers several advantages: Single source of truth – The Central IT team acts as the custodian of the combined and curated data from all business units, thereby providing a unified and consistent dataset. Srividya Parthasarathy is a Senior Big Data Architect on the AWS Lake Formation team.

Data Lake 121

Data Lake Data Warehouse Data Governance Publishing 121

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 98

Data Lake Data Governance Data Architecture Machine Learning 98

erwin

MAY 27, 2020

They should automatically generate data models , providing a simple, graphical display to visualize a wide range of enterprise data sources based on a common repository of standard data assets through a single interface. Data siloes, of course, are the enemies of data governance.

Modeling 98

Modeling Metadata Data Governance Visualization 98

Alation

JULY 19, 2021

Chris Bulock, co-author of Knowledge and Dignity in the Era of “Big Data”. Every organization is swimming in data, which makes finding the right data a challenge. But there is a way to catalog and classify data that is mind blowing: it’s data…about data ! Why Is Metadata Important?

Metadata 105

Metadata Management Data Governance Machine Learning 105

IBM Big Data Hub

MARCH 25, 2022

There are many different approaches, but you’ll want an architecture that can be used regardless of your data estate. In other words, the obstacles of data access, data integration and data protection are minimized, rendering maximum flexibility to the end users. Protection is applied on each data pipeline.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104