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 84

Data Governance Business Objectives Strategy Data Quality 84

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

Alation

FEBRUARY 3, 2022

DataOps practices help organizations overcome challenges caused by fragmented teams and processes and delays in delivering data in consumable forms. So how does data governance relate to DataOps? Data governance is a key data management process. Continuous Improvement Applied to Data Governance.

Data Governance 98

Data Governance Measurement Metadata Testing 98

erwin

APRIL 16, 2021

Data governance is best defined as the strategic, ongoing and collaborative processes involved in managing data’s access, availability, usability, quality and security in line with established internal policies and relevant data regulations. Data Governance Is Business Transformation. Predictability.

Data Governance 128

Data Governance Metadata Cost-Benefit Digital Transformation 128

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 66

Data Quality Snapshot Data Governance Data-driven 66

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 69

Data Quality Data Governance People Analytics Data-driven 69

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 Quality 52

Data Quality Data Architecture Strategy Data Lake 52

Jim Harris

APRIL 20, 2021

OCDQ Radio is an audio podcast about data quality and its related disciplines, produced and hosted by Jim Harris. Why does no one care about poor data quality? tolerance for poor data quality). tolerance for poor data quality).

Data Quality 59

Data Quality Data Governance Data Processing Metrics 59

Alation

FEBRUARY 14, 2023

And a data breach poses more than just a PR risk — by violating regulations like GDPR , a data leak can impact your bottom line, too. This is where successful data governance programs can act as a savior to many organizations. This begs the question: What makes data governance successful? Where do you start?

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 52

Octopai

JULY 11, 2022

And when business users don’t complain, but you know the data isn’t good enough to make these types of calls wisely, that’s an even bigger problem. How are you, as a data quality evangelist (if you’re reading this post, that must describe you at least somewhat, right?), Tie data quality directly to business objectives.

Data Quality 79

Data Quality Strategy Business Objectives Sales 79

Anmut

MARCH 22, 2023

This ultimately allows for more effective goal-setting, with targets determined according to both your data maturity right now and the desired stage you want to attain in the future. Why do we need data maturity models? A data maturity model helps your company measure its data and business health.

Measurement 52

Measurement Modeling Data Quality Data Governance 52

erwin

MARCH 25, 2021

erwin recently hosted the second in its six-part webinar series on the practice of data governance and how to proactively deal with its complexities. Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, the second webinar focused on “ The Value of Data Governance & How to Quantify It.”.

Data Governance 109

Data Governance IT Cost-Benefit Risk 109

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

Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. So why are organizations not able to scale governance? Meet Governance Requirements.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CDW Research Hub

MAY 29, 2019

Data governance helps organizations manage their information and answer questions about business performance, allowing them to better understand data, and govern it to mitigate compliance risks and empower information stakeholders. Checklist: Building an Enterprise Data Governance Program.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

Jim Harris

DECEMBER 24, 2015

Have you ever experienced that sinking feeling, where you sense if you don’t find data quality, then data quality will find you? I hope that you enjoy reading this blog post, but most important, I hope you always remember: “Data are friends, not food.” Data Silos. You, Data-Dude, takin’ on the defects.

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Data Quality Enterprise Business Intelligence Data Governance 56

InsightOut

FEBRUARY 16, 2024

However, managing vast volumes of data, identifying inaccuracies, and ensuring data quality can be daunting tasks for these organizations. This bespoke approach ensures that every company maximizes the value of its data. Scalability for Growth: As mid-sized companies grow, so do their data needs.

Data Quality 52

Data Quality Data-driven Data Governance Measurement 52

InsightOut

FEBRUARY 16, 2024

However, managing vast volumes of data, identifying inaccuracies, and ensuring data quality can be daunting tasks for these organizations. This bespoke approach ensures that every company maximizes the value of its data. Scalability for Growth: As mid-sized companies grow, so do their data needs.

Data Quality 52

Data Quality Data-driven Data Governance Measurement 52

TDAN

JANUARY 18, 2022

Data Accuracy is one of the so-called “dimensions” of Data Quality. The goal for these dimensions, and it is a noble one, is so we can measure each of them, and should deficiencies be found then there should be a uniform set of best practices that we can implement.

Data Quality 98

Data Quality Measurement IT Data Strategy 98

Anmut

APRIL 6, 2023

What are the Benefits of Doing a Data Maturity Assessment? How do you do a Data Maturity Assessment? What does a Data Maturity Assessment Measure? What makes a Good Data Maturity Assessment? What is a Data Maturity Assessment? What does a Data Maturity Assessment Measure?

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 52

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

Octopai

JUNE 19, 2023

Including them in the design and implementation process ensures that the data catalog meets their needs, and requirements, and aligns with business goals. Establish Data Governance Policies A crucial part of implementing a data catalog is establishing robust data governance policies.

Metadata 88

Metadata Data Governance Measurement Risk Management 88

erwin

SEPTEMBER 13, 2022

Day one will feature presentations from industry experts and experienced data professionals on the initiatives and tactical measures being taken by data-driven enterprises to reap the benefits of data intelligence and governance. Learn how to maximize the business impact of your data.

Data Governance 52

Data Governance Data-driven Data Architecture Data Quality 52

Smart Data Collective

DECEMBER 21, 2022

This market is growing as more businesses discover the benefits of investing in big data to grow their businesses. One of the biggest issues pertains to data quality. Even the most sophisticated big data tools can’t make up for this problem. Data cleansing and its purpose.

Business Analytics 112

Business Analytics Analytics Data Quality Big Data 112

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 96

Strategy Data Architecture Cost-Benefit Reporting 96

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Alation

AUGUST 9, 2022

It is essential to consider data integrity when designing, implementing and using any system that stores, processes, and retrieves data. Many confuse data integrity with data quality. This strategy should also consider data security. Objective: a set of rules that determines what the data should look like.

Data Integration 52

Data Integration Data Quality Measurement Strategy 52

O'Reilly on Data

JULY 28, 2020

These measures are commonly referred to as guardrail metrics , and they ensure that the product analytics aren’t giving decision-makers the wrong signal about what’s actually important to the business. When a measure becomes a target, it ceases to be a good measure ( Goodhart’s Law ). Data Wrangling and Feature Engineering.

Marketing 362

Marketing Experimentation Metrics Testing 362

Laminar Security

DECEMBER 13, 2023

Navigating the challenges of AI in data discovery and classification In the complex and dynamic landscape of data security, AI has emerged as a powerful tool for data discovery and classification. One of the primary challenges is data quality. However, it’s not without its challenges.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

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 69

Data Quality Data Integration Metadata Cost-Benefit 69

FineReport

APRIL 9, 2024

By leveraging these insights, businesses can implement preemptive measures to mitigate risks effectively, safeguarding their operations against potential disruptions. Users should receive training on how to navigate the software, interpret data visualizations, and leverage advanced analytics capabilities to make informed decisions.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

CIO Business Intelligence

JUNE 14, 2023

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. The number of data analytics certs is expanding rapidly.

Big Data 127

Big Data Data Analytics Analytics Predictive Modeling 127

Andrew White

OCTOBER 23, 2020

Chief Data Officer/CDO 4. Chief Quality Officer 1. Director Data Mgt and Advanced Analytics 1. Data Governance 1. Data and Analytics Governance Requires a Comprehensive Range of Policy Types. Discusses the need to connect the disparate silos of data privacy, data security, and data quality etc.

IT 52

IT Digital Transformation Recreation/Entertainment Data Quality 52

Alation

MARCH 11, 2022

Tip 2: Let the data catalog do the heavy lifting. What data is useful? A data catalog with a Behavioral Analysis Engine will measure human behavior around data to locate your most valuable and actionable data. This data about data, AKA metadata , is an essential layer of your new meshy fabric.

Metadata 52

Metadata Data Governance ROI Data Quality 52

CIO Business Intelligence

JANUARY 4, 2023

This will help us address the carbon footprint of our applications as part of the software development lifecycle, by improving measurability and transparency, reducing unnecessary or excess cycles, and better leveraging our hardware,” she says. Data management, automation, analytics is critical to reviewing our progress in ESG,” she says. “As

IT 131

IT Internet of Things Reporting Cost-Benefit 131

Smarten

DECEMBER 3, 2023

‘Giving your team the right tools and a simple way to manage the overwhelming flow of data is crucial to business success.’ Accessible augmented analytics, allows you to transition your business users to the Citizen Data Scientist role to make better decisions, more quickly. So, what does all this mean to your business?

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40