Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 84

Data Architecture Risk Management Risk Management 84

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

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

Cloudera

OCTOBER 1, 2022

According to Gartner, by 2023 65% of the world’s population will have their personal data covered under modern privacy regulations. . As a result, growing global compliance and regulations for data are top of mind for enterprises that conduct business worldwide. – From a recent episode of the TWIML AI Podcast.

Data Governance 73

Data Governance Strategy Enterprise Machine Learning 73

erwin

JULY 12, 2019

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

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

erwin

SEPTEMBER 19, 2019

Data governance isn’t a one-off project with a defined endpoint. Data governance, today, comes back to the ability to understand critical enterprise data within a business context, track its physical existence and lineage, and maximize its value while ensuring quality and security. Slow Down, Ask Questions.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108

Cloudera

MAY 14, 2024

More than that, though, harnessing the potential of these technologies requires quality data—without it, the output from an AI implementation can end up inefficient or wholly inaccurate. Meaningful results, and a scalable, flexible data architecture demand a ‘true’ hybrid cloud approach to data management.

Data Architecture 97

Data Architecture Data Governance Unstructured Data Structured Data 97

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

Cloudera

NOVEMBER 21, 2024

As advanced analytics and AI continue to drive enterprise strategy, leaders are tasked with building flexible, resilient data pipelines that accelerate trusted insights. Powered by integrated platform services, Cloudera Data Engineering ensures data governance with robust data handling and automated lifecycle lineage tracking.

Cost-Benefit 66

Cost-Benefit Data Lake Interactive Enterprise 66

TDAN

JULY 2, 2019

The third and final part of the Non-Invasive Data Governance Framework details the breakdown of components by level, providing considerations for what must be included at the intersections. The squares are completed with nouns and verbs that provide direction for meaningful discussions about how the program will be set up and operate.

Data Governance 74

Data Governance Data Quality Data Architecture Metadata 74

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 85

Strategy Data Architecture Cost-Benefit Reporting 85

CIO Business Intelligence

MAY 15, 2024

The ability to leverage data to understand and plan for those behaviors is extremely important. How did you improve the organization’s data literacy? Once we set up a data architecture that provides data liquidity, where data can go everywhere, we had to teach people how to use it.

Cost-Benefit 95

Cost-Benefit Data Governance Data Architecture Reporting 95

erwin

SEPTEMBER 13, 2022

Come listen to data veterans in customer organizations as well as data best practices experts from IDC, Global Data Strategy, Ltd. Learn how to maximize the business impact of your data. The Real World Value of Data Intelligence – A Look Inside Data Management.

Data Governance 52

Data Governance Data-driven Data Architecture Data Quality 52

AWS Big Data

NOVEMBER 22, 2024

This enables you to extract insights from your data without the complexity of managing infrastructure. dbt has emerged as a leading framework, allowing data teams to transform and manage data pipelines effectively. With dbt, teams can define data quality checks and access controls as part of their transformation workflow.

Data Lake 59

Data Lake Data Warehouse Cost-Benefit Data Transformation 59

erwin

FEBRUARY 28, 2024

One of the key ingredients to ensure data is really embedded in an organization, and one of the key enablers to increase the strategic impact of data, is the setup of a successful data governance program. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool.

Metadata 52

Metadata Data Governance Data Quality Technology 52

Anmut

APRIL 6, 2023

By regularly conducting data maturity assessments, you can catch potential issues early and make proactive changes to supercharge your business’s success. Cost savings By identifying areas where data management processes can be optimised, organisations can reduce costs associated with data management and analysis.

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 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

TDAN

APRIL 16, 2019

The phrase “data architecture” often has different connotations across an organization depending on where their job role is. For instance, most of my earlier career roles were within IT, though throughout the last decade or so, has been primarily working with business line staff.

Data Architecture 40

Data Architecture IT Data Quality Data Governance 40

Smart Data Collective

FEBRUARY 23, 2021

To help you identify and resolve these mistakes, we’ve put together this guide on the various big data mistakes that marketers tend to make. Big Data Mistakes You Must Avoid. Here are some common big data mistakes you must avoid to ensure that your campaigns aren’t affected. Ignoring Data Quality.

Big Data 116

Big Data Visualization Data Quality Data-driven 116

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 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 79

Management Metadata Data Architecture Data Lake 79

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

CIO Business Intelligence

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity.

Data Architecture 108

Data Architecture Data Integration IoT Strategy 108

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises.

Metrics 83

Metrics Data Quality Data Lake Statistics 83

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

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 81

Data Lake Data Architecture Data-driven Data Warehouse 81

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 77

Data Strategy Strategy Data Warehouse Prescriptive Analytics 77

CIO Business Intelligence

JULY 22, 2024

We were trying to skip over some of the data governance aspect with the idea that we would come back and go after that later,” he says. “We But you have to do this to continue to be successful in the emerging world of data analytics, AI, generative AI, and all the things that will follow.

Data Governance 119

Data Governance Unstructured Data Technology Modeling 119

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 59

Metadata Management Business Intelligence Data Governance 59

TDAN

SEPTEMBER 4, 2024

There are many perennial issues with data: data quality, data access, data provenance, and data meaning. I will contend in this article that the central issue around which these others revolve is data complexity. It’s the complexity of data that creates and perpetuates these other problems.

Data Quality 52

Data Quality Data Architecture IT Data Governance 52

IBM Big Data Hub

JUNE 30, 2022

The diversity of data types, data processing, integration and consumption patterns used by organizations has grown exponentially. Extend data governance to foster trust in your data by creating transparency, eliminating bias and ensuring explainability for data and insights fueled by machine learning and AI.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

TDAN

MAY 17, 2022

One of the greatest contributions to the understanding of data quality and data quality management happened in the 1980s when Stuart Madnick and Rich Wang at MIT adapted the concept of Total Quality Management (TQM) from manufacturing to Information Systems reframing it as Total Data Quality Management (TDQM).

Data Quality 52

Data Quality Manufacturing Management IT 52

IBM Big Data Hub

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions provide new clients with affordable and high impact capabilities to expeditiously explore and validate the path to become a data-driven enterprise. IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

erwin

OCTOBER 24, 2019

The complexities of metadata management can be addressed with a strong data management strategy coupled with metadata management software to enable the data quality the business requires. Organizations then can take a data-driven approach to business transformation , speed to insights, and risk management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Alation

NOVEMBER 2, 2022

We had not seen that in the broader intelligence & data governance market.”. At Databricks, we’re focused on enabling customers to adopt the data lakehouse, and that’s an open data architecture that combines the best of the data warehouse and the data lake into one platform,” Ferguson says. “[The

Data Governance 98

Data Governance Marketing Finance Data Lake 98