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 Risk 52

Anmut

OCTOBER 29, 2020

Data governance - who's counting? The role of data governance. This large gap between reported figures raises tough questions on the reliability of COVID-19 tracking data. In dealing with situations like pandemic data, how important are aspects of data governance such as standardised definitions?

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52

FineReport

MAY 31, 2023

Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming. Data Quality and Consistency : Maintaining data quality and consistency is essential for reliable financial insights. Inaccurate or inconsistent data can lead to erroneous conclusions and decisions.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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 Metadata ROI 40

CIO Business Intelligence

JANUARY 24, 2024

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

Data Strategy 135

Data Strategy Strategy Unstructured Data Data Governance 135

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

Jim Harris

JANUARY 1, 2016

1 — Investigate Data quality is not exactly a riddle wrapped in a mystery inside an enigma. However, understanding your data is essential to using it effectively and improving its quality. In order for you to make sense of those data elements, you require business context.

Data Quality 61

Data Quality Data Governance Cost-Benefit ROI 61

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

CIO Business Intelligence

DECEMBER 19, 2023

Third, in the CDO Agenda: 2024: Navigating Data and Generative AI Frontiers , 57% of respondents haven’t changed their data environments to support generative AI. CIOs should look for other operational and risk management practices to complement transformation programs.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

Alation

JULY 15, 2022

I recently led an online session, Data Monetisation and Governance , looking at the evolution of data governance , defining data ethics (from the Turing Institute ), and touching on the balancing act between using data to monetise (by increasing revenue, decreasing spend, or mitigating risk) and meeting ethical obligations.

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

erwin

MARCH 30, 2020

These numerous data types and data sources most definitely weren’t designed to work together. As a result, the data may be compromised, rendering faulty analyses and insights. Unraveling Data Complexities with Metadata Management. Data profiling for data assessment, metadata discovery and data validation.

Metadata 122

Metadata IT Data Governance Data Quality 122

CIO Business Intelligence

MARCH 4, 2024

Harmonizing these data sets with centralized enterprise data faces increasing challenges as shifts to data definitions, schema, and architecture require constant central data team efforts. These domain data leaders often cite the diminishing returns and significant effort of central data team engagement.

Insurance 98

Insurance Strategy Data Governance Data Integration 98

Alation

JUNE 14, 2021

And third is what factors CIOs and CISOs should consider when evaluating a catalog – especially one used for data governance. The Role of the CISO in Data Governance and Security. They want CISOs putting in place the data governance needed to actively protect data. So CISOs must protect data.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Metadata 97

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 99

Data Quality Visualization Metadata Key Performance Indicator 99

Anmut

APRIL 6, 2023

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? The definition of a data maturity assessment is a measurement of the reliability, effectiveness, and efficiency of an organisation’s data management.

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 52

Cloudera

SEPTEMBER 15, 2022

What is a data fabric? Mark: Gartner states that a data fabric “enables frictionless access and sharing of data in a distributed data environment.” The data fabric provides direct support for the first element of the architecture — linking the distributed source data into the hybrid, multi-cloud environment. .

Data Lake 87

Data Lake Data Architecture Data-driven Data Warehouse 87

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Alation

MARCH 8, 2022

They either can’t wait for someone else to find it or can’t explain exactly what they need, so they set off to search and dig and waste time looking for that data needle in the proverbial haystack. But they then risk using the wrong data, pulling others away from more important jobs, or making bad decisions based on bad data.

Analytics 52

Analytics Data Governance Data-driven Data Science 52

CIO Business Intelligence

APRIL 29, 2022

The strategy should put formalized processes in place to quantify the value of different types of information, leveraging the skills of a chief data officer (CDO), who should form and chair a data governance committee. Prioritize your investments.

Digital Transformation 129

Digital Transformation Strategy Data-driven Data Strategy 129

Ontotext

MARCH 8, 2023

Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. A risk issue in one financial institution could result in a domino effect for many. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 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. The What: Data Governance Defined. Where is it?

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Alation

MAY 31, 2023

The state of data governance is evolving as organizations recognize the significance of managing and protecting their data. With stricter regulations and greater demand for data-driven insights, effective data governance frameworks are critical. What is a data architect?

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Alation

FEBRUARY 13, 2020

A Data Catalog is a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses. Benefits of a Data Catalog.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

Jet Global

JULY 2, 2019

Just like actual lakes, the long-term health of your organizational data lake depends on defending it from ‘pollution’—data governance is critical to ensure your data lake doesn’t become a data swamp.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 315

Enterprise Deep Learning Data Governance Risk 315

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). Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Cloudera

MARCH 14, 2023

They are being asked to deliver not just theoretical data strategies, but to roll up their sleeves and solve for the very real problems of disparate, heterogenous, and rapidly expanding data sources that make it a challenge to meet increasing business demand for data — and do it all while managing costs and ensuring security and data governance.

Cost-Benefit 84

Cost-Benefit Data-driven Risk Data Governance 84

Alation

JULY 28, 2022

The cloud is no longer synonymous with risk. There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. I am not interested in owning that risk internally.” What Are the Biggest Business Risks to Cloud Data Migration? Lower control.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Octopai

DECEMBER 12, 2021

Whenever you save the file, you create metadata about the current status of this data asset: The metadata displayed here includes data asset type, size of the asset, and time of the last change in the asset. Metadata stewardship tools are important for: Data governance Regulatory compliance Evaluating and improving data quality.

Metadata 98

Metadata Management Data Quality Data Governance 98

Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Ontotext

JUNE 29, 2023

This standardizes your data processing across different teams and departments, reducing manual effort and improving data quality. Building a KG requires collaboration between functional domain experts, data engineers, data modelers and key sponsors. At this point, most of the work has been done.

Cost-Benefit 59

Cost-Benefit Data-driven Data Quality Enterprise 59

erwin

OCTOBER 24, 2019

. • Harvesting data – Automate the collection of metadata from various data management silos and consolidate it into a single source. Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Grooper

AUGUST 19, 2019

The most important thing to understand is that ISL is a complete system of learning, not just a list of generic terms and definitions. ISL helps today's business leaders understand how data answers business questions. Master data management. Data governance. Scoring – i.e. profitability or risk. Algorithms.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Andrew White

JANUARY 9, 2022

Could you precise to which complementary research you mentioned when you talked about a data governance survey ? – Here is the one I mentioned during the webinar: The State of Data and Analytics Governance Is Worse Than You Think. – Data (and analytics) governance remains a challenge.

Analytics 64

Analytics Measurement Data-driven Modeling 64