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

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 94

Strategy Data Architecture Cost-Benefit Reporting 94

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Cloudera

MARCH 28, 2024

But, even with the backdrop of an AI-dominated future, many organizations still find themselves struggling with everything from managing data volumes and complexity to security concerns to rapidly proliferating data silos and governance challenges. The benefits are clear, and there’s plenty of potential that comes with AI adoption.

Data Architecture 89

Data Architecture Strategy Data Lake Data-driven 89

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. Improved data quality By assessing the organisation’s data quality management practices, the assessment can identify areas where data quality can be improved.

Cost-Benefit 52

Cost-Benefit Data Quality Data Governance Measurement 52

Ontotext

APRIL 10, 2024

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

CIO Business Intelligence

APRIL 24, 2024

Artificial Intelligence, Business Intelligence, Change Management, CIO, Data Architecture, Data Management, Data Quality, Digital Transformation, IT Leadership, IT Operations, IT Strategy

Digital Transformation 102

Digital Transformation Business Intelligence Unstructured Data Data Lake 102

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 79

Data Lake Data Architecture Data-driven Data Warehouse 79

erwin

SEPTEMBER 13, 2022

Learn how to maximize the business impact of your data. Discover how IT, data governance teams, and business users benefit from data intelligence initiatives through automated data cataloging, data quality, data literacy, and self-service data preparation.

Data Governance 52

Data Governance Data-driven Data Architecture Data Quality 52

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

JUNE 9, 2023

A few years ago, Gartner found that “organizations estimate the average cost of poor data quality at $12.8 million per year.’” Beyond lost revenue, data quality issues can also result in wasted resources and a damaged reputation. Learn more about data architectures in my article here.

Strategy 111

Strategy Management Key Performance Indicator ROI 111

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52

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 82

Metrics Data Quality Data Lake Statistics 82

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

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 68

Data Quality Data Integration Metadata Cost-Benefit 68

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance.

Data Governance 110

Data Governance Management Metadata Risk Management 110

TDAN

JUNE 18, 2019

The first step to fixing any problem is to understand that problem—this is a significant point of failure when it comes to data. Most organizations agree that they have data issues, categorized as data quality. However, this definition is […].

Data Quality 90

Data Quality Data Architecture IT Data Strategy 90

CIO Business Intelligence

JUNE 23, 2023

There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value. Of course, no set of imperatives for a data strategy would be complete without the need to consider people, process, and technology.

Data Strategy 111

Data Strategy Strategy Visualization Consulting 111

CIO Business Intelligence

MAY 20, 2022

Modernizing a utility’s data architecture. These capabilities allow us to reduce business risk as we move off of our monolithic, on-premise environments and provide cloud resiliency and scale,” the CIO says, noting National Grid also has a major data center consolidation under way as it moves more data to the cloud.

IT 103

IT Digital Transformation Internet of Things Data Architecture 103

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 83

Data Architecture Risk Management Risk Management 83

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. Data ingestion, whether real time or batch, forms the basis of any effective data analysis, enabling organizations to gather information from diverse sources and use it for insightful decision-making.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

IBM Big Data Hub

FEBRUARY 9, 2023

Realize that a data governance program cannot exist on its own – it must solve business problems and deliver outcomes. Start by identifying business objectives, desired outcomes, key stakeholders, and the data needed to deliver these objectives. So where are you in your data governance journey?

Data Governance 83

Data Governance Business Objectives Strategy Data Quality 83

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 80

Data Lake Data Governance Data Architecture Machine Learning 80

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Sisense

AUGUST 28, 2020

Uncomfortable truth incoming: Most people in your organization don’t think about the quality of their data from intake to production of insights. However, as a data team member, you know how important data integrity (and a whole host of other aspects of data management) is.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

TDAN

MARCH 17, 2020

Business has a fundamental problem with data quality. In some places it’s merely painful, in others it’s nearly catastrophic. Why is the problem so pervasive? Why does it never seem to get fixed? I believe we’ve been thinking about the problem wrong. It’s time for a fresh look.

Data Quality 59

Data Quality Data Architecture IT Metadata 59

CIO Business Intelligence

AUGUST 9, 2022

Data engineers and data scientists often work closely together but serve very different functions. Data engineers are responsible for developing, testing, and maintaining data pipelines and data architectures. Data engineer vs. data architect.

Analytics 128

Analytics Data Science Statistics Unstructured Data 128

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 57

Data Strategy Strategy Business Objectives Data-driven 57

IBM Big Data Hub

JANUARY 25, 2023

Breaking down these silos to encourage data access, data sharing and collaboration will be an important challenge for organizations in the coming years. The right data architecture to link and gain insight across silos requires the communication and coordination of a strategic data governance program.

Data Governance 52

Data Governance Data-driven Strategy Management 52

Cloudera

AUGUST 30, 2022

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Modern data architectures. Deploying modern data architectures. Forrester ).

Data Architecture 77

Data Architecture Data Lake Metadata Data Warehouse 77

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Why telco should consider modern data architecture. The challenges.

Data Architecture 84

Data Architecture Cost-Benefit Digital Transformation Business Driver 84

Octopai

APRIL 19, 2021

Her Twitter page is filled with interesting articles, webinars, reports, and current news surrounding data management. She tweets and retweets about topics such as data governance, data strategy, and data architecture. TDWI – David Loshin. It is published by Robert S. Seiner and produced by Dataversity.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

bridgei2i

JUNE 23, 2021

These include:lack of understanding of the business-centric use cases of AI, IT gaps,lack of skilled employees, issues in data quality, and resistance to incorporate new technologies into the framework. An AI Consulting Company provides support to organizations to build the right data strategy for AI implementation.

Consulting 52

Consulting Key Performance Indicator Business Objectives Data Strategy 52

IBM Big Data Hub

AUGUST 15, 2022

How does a data architecture impact your ability to build, scale and govern AI models? To be a responsible data scientist, there’s two key considerations when building a model pipeline: Bias: a model which makes predictions for people of different group (or race, gender ethnic group etc.)

Data mining 62

Data mining Risk Modeling Risk Management 62

AWS Big Data

APRIL 19, 2023

The goal of a data product is to solve the long-standing issue of data silos and data quality. Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights.

Technology 80

Technology Data-driven Machine Learning Sales 80

Ontotext

DECEMBER 1, 2023

Most organisations are missing this ability to connect all the data together. from Q&A with Tim Berners-Lee ) Finally, Sumit highlighted the importance of knowledge graphs to advance semantic data architecture models that allow unified data access and empower flexible data integration.

Metadata 78

Metadata Sales Consulting Enterprise 78

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52