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

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

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 81

Data Governance Business Objectives Strategy Data Quality 81

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 67

Data Quality Data Governance People Analytics Data-driven 67

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

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 57

Data Quality Metadata Data Governance Data-driven 57

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 64

Data Quality Snapshot Data Governance Data-driven 64

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 55

Data Governance Enterprise Modeling Risk 55

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 84

Metadata Data Governance Enterprise Reporting 84

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 Management 52

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management.

Management 320

Management Data Warehouse Data Quality Data Integration 320

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

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 109

Business Analytics Analytics Data Quality Big Data 109

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Octopai

JUNE 22, 2023

In the era of big data, organizations are grappling with the challenge of effectively managing and leveraging vast amounts of data. Two prominent approaches have emerged: self-service data management and centralized data management. This approach offers greater control and reduces the risk of data inconsistencies.

Management 52

Management Data-driven Data Quality Data Governance 52

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

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 83

Data Lake Data Governance Data Architecture Data Warehouse 83

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 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Here are a few common data management challenges: Regulatory compliance on data use.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

IBM Big Data Hub

NOVEMBER 28, 2022

Suppose that a new data asset becomes available but remains hidden from your data consumers because of improper or inadequate tagging. How do you keep pace with growing data volumes and increased demand from data consumers and deliver real-time data governance for trusted outcomes? Improve data discovery.

Metadata 57

Metadata Data Quality Data-driven Data Governance 57

CIO Business Intelligence

MARCH 27, 2024

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

Data Governance 52

Data Governance Data Lake Data Strategy Data-driven 52

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 52

Metadata Data Governance Digital Transformation Data Quality 52

IBM Big Data Hub

NOVEMBER 21, 2023

A schema registry is essentially an agreement of the structure of your data within your Kafka environment. Having a well-managed schema registry is not just a technical necessity but also contributes to the strategic goals of treating data as a valuable product and helps tremendously on your data-as-a-product journey.

Data Quality 105

Data Quality Metadata Data-driven Optimization 105

Laminar Security

DECEMBER 13, 2023

Deep learning, a subset of machine learning, involves training neural networks on large amounts of data and then using these networks to make predictions or decisions. Another trend is the increasing integration of AI with other technologies such as cloud computing and big data analytics.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

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. On top of this, we’re living through the age of big data , where more information is being processed and stored by organisations that also have to manage regulations.

Data Integration 52

Data Integration Data Quality Measurement Strategy 52

IBM Big Data Hub

JULY 6, 2022

Businesses of all sizes, in all industries are facing a data quality problem. 73% of business executives are unhappy with data quality and 61% of organizations are unable to harness data to create a sustained competitive advantage 1.

Metadata 57

Metadata Data Quality Snapshot Cost-Benefit 57

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

TDAN

FEBRUARY 4, 2020

More money, more fun, more pleasure, more accomplishment, more intelligence, and yes, more data. More, more, more! We are culturally conditioned to want more. There is an idea that if we get more, we will be happier and more successful. The need for more fuels consumerism and business.

Big Data 72

Big Data Marketing Data Quality Data Strategy 72

Alation

MAY 19, 2022

Gartner shared that organizations today are using active metadata to enable data fabric , identify data drift , and locate new categories of data. Leverage small data. It’s not just about big data anymore! So what should people struggling with low-quality data do? Data Governance.

Metadata 52

Metadata Data Analytics Analytics Data Governance 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).

Insurance 100

Insurance Data-driven Data Governance Metadata 100

Alation

FEBRUARY 13, 2020

The report was created to size and forecast software that is used in the processes of data governance, data quality management, and self-service data – each having become significant in this new era of digital transformation and complex regulatory restrictions. Can’t Stop, Won’t Stop.

Machine Learning 52

Machine Learning Big Data Data Governance Digital Transformation 52

IBM Big Data Hub

APRIL 10, 2023

To further the above, organizations should have the right foundation that consists of a modern data governance approach and data architecture. It’s becoming critical that organizations should adopt a data architecture that supports AI governance.

Strategy 93

Strategy Data Architecture Cost-Benefit Reporting 93

Alation

DECEMBER 6, 2022

At Informatica, he pioneered the concept of self-service data integration and data quality. He brings in decades of experience in data integration, as well as metadata management and data governance. He has also been instrumental in bootstrapping and steering major partnerships with IBM and AWS.

Metadata 52

Metadata Enterprise Data Integration Data Quality 52

Octopai

APRIL 19, 2021

BI teams will have a better handle on their data’s history, its current status, and any changes it may have undergone. Without organized metadata management, the validity of a company’s data is compromised and they won’t achieve adequate compliance, data governance, or generate correct insights. TDWI – David Loshin.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

Octopai

JANUARY 31, 2021

Specifically, when it comes to data lineage, experts in the field write about case studies and different approaches to this utilizing this tool. Among many topics, they explain how data lineage can help rectify bad data quality and improve data governance. . TDWI – Philip Russom. Malcolm Chisholm.

Data Governance 57

Data Governance Data Processing Data Quality Metadata 57

IBM Big Data Hub

JULY 13, 2022

This data proliferation has made it harder than ever before to trust your data: knowing where it came from, how it has changed, and who is using it. Data provenance is a complexity facing many clients engaged in data governance-related use cases.

Metadata 67

Metadata Data Governance Data Quality Data Integration 67

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 67

Data Quality Data Integration Metadata Cost-Benefit 67