DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. The communication between business units and data professionals is usually incomplete and inconsistent. DDD divides a system or model into smaller subsystems called domains.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

DECEMBER 11, 2024

Digital transformation started creating a digital presence of everything we do in our lives, and artificial intelligence (AI) and machine learning (ML) advancements in the past decade dramatically altered the data landscape. Thats free money given to cloud providers and creates significant issues in end-to-end value generation.

Management 111

Management Data Governance Data Science Reporting 111

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

AWS Big Data

OCTOBER 9, 2024

Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases. This takes away important person hours from the actual migration effort into building and maintaining a data parity framework.

Data Quality 96

Data Quality Data Lake Data Warehouse Metrics 96

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

Data Quality 104

Data Quality Data Governance Data Lake Testing 104

AWS Big Data

APRIL 8, 2025

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support. When combined with well-timed maintenance operations, these patterns help build resilient data pipelines that can handle concurrent writes reliably.

Snapshot 117

Snapshot Management Metadata Big Data 117

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. You can review code changes directly on the platform, facilitating efficient teamwork.

Data Lake 84

Data Lake Data Warehouse Cost-Benefit Data Transformation 84

AWS Big Data

JANUARY 15, 2025

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

IoT 101

IoT Machine Learning Metadata Data-driven 101

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

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. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. Use MLOps for scalability The development of machine learning (ML) models is notoriously error-prone and time-consuming.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

erwin

OCTOBER 24, 2019

. • Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards. Analyzing metadata – Understand how data relates to the business and what attributes it has. Addressing the Complexities of Metadata Management.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Cloudera

MAY 14, 2024

To attain that level of data quality, a majority of business and IT leaders have opted to take a hybrid approach to data management, moving data between cloud, on-premises -or a combination of the two – to where they can best use it for analytics or feeding AI models. What do we mean by ‘true’ hybrid?

Data Architecture 99

Data Architecture Data Governance Unstructured Data Structured Data 99

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

AWS Big Data

FEBRUARY 27, 2024

Machine learning analytics – Various business units, such as Servicing, Lending, Sales & Marketing, Finance, and Credit Risk, use machine learning analytics, which run on top of the dimensional model within the data lake and data warehouse. This enables data-driven decision-making across the organization.

Data-driven 106

Data-driven Data Lake Data Quality Data Governance 106

erwin

DECEMBER 6, 2019

Enterprise Data Management Methodology : DG is foundational to enterprise data management. metadata management, enterprise data architecture, data quality management), DG will be a struggle. The right tools can make or break your data governance initiatives.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

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 111

Data Architecture Data Integration IoT Data-driven 111

CIO Business Intelligence

NOVEMBER 7, 2023

Opting for a centralized data and reporting model rather than training and embedding analysts in individual departments has allowed us to stay nimble and responsive to meet urgent needs, and prevented us from spending valuable resources on low-value data projects which often had little organizational impact,” Higginson says.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

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

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

CIO Business Intelligence

FEBRUARY 28, 2024

However, getting into the more difficult types of implementations — the fine-tuned models, vector databases to provide context and up-to-date information to the AI systems, and APIs to integrate gen AI into workflows — is where problems might crop up. That’s fine, but language models are great for language. They need stability.

IT 131

IT Consulting Modeling Enterprise 131

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. A DataOps implementation project consists of three steps.

Testing 152

Testing Metadata Dashboards Statistics 152

Cloudera

JULY 20, 2021

Once companies are able to leverage their data they’re then able to fuel machine learning and analytics models, transforming their business by embedding AI into every aspect of their business. . Build your data strategy around the convergence of software and hardware. Airline schedules and pricing algorithms.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

CIO Business Intelligence

JUNE 9, 2023

Data d ependenc y Regardless of your industry, data is central to almost every business today. Leveraging that data, in AI models, for example, depends entirely on the accessibility, quality, granularity, and latency of your organization’s data. Learn more about data architectures in my article here.

Strategy 116

Strategy Management Key Performance Indicator Cost-Benefit 116

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 105

IT Internet of Things Digital Transformation Data Architecture 105

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 116

Data Strategy Strategy Visualization Consulting 116

Cloudera

JUNE 13, 2024

Only Cloudera has the ability to help organizations overcome the three barriers to trust in Enterprise AI: Readiness – Can you trust the safety of your proprietary data in public AI models? Reliability – Can you trust that your data quality will yield useful AI results?

Big Data 103

Big Data Machine Learning Contextual Data Data Lake 103

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 53

Modeling Metadata Data Quality Enterprise 53

CIO Business Intelligence

APRIL 24, 2024

In fact, AMA collects a huge amount of structured and unstructured data from bins, collection vehicles, facilities, and user reports, and until now, this data has remained disconnected, managed by disparate systems and interfaces, through Excel spreadsheets.

Digital Transformation 105

Digital Transformation Business Intelligence Unstructured Data Data Lake 105

erwin

SEPTEMBER 19, 2019

Click here to download our latest, best practice guide for Data Modeling for free. Historically, little attention has focused on what can literally make or break any data governance initiative — turning it from a launchpad for competitive advantage to a recipe for disaster. Passing the Data Governance Ball.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

CIO Business Intelligence

AUGUST 9, 2022

Data engineers and data scientists often work closely together but serve very different functions. 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.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

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

Cloudera

OCTOBER 1, 2022

Adam Wood, director of data governance and data quality at a financial services institution (FSI). As countries introduce privacy laws, similar to the European Union’s General Data Protection Regulation (GDPR), the way organizations obtain, store, and use data will be under increasing legal scrutiny.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 100

Data Warehouse KPI Optimization Cost-Benefit 100

CIO Business Intelligence

APRIL 29, 2022

From a policy perspective, the organization needs to mature beyond a basic awareness and definition of data compliance requirements (which typically holds that local operations make data “sovereign” by default) to a more refined, data-first model that incorporates corporate risk management, regulatory and reporting issues, and compliance frameworks.

Digital Transformation 132

Digital Transformation Data-driven Strategy Data Strategy 132