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

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. After all, you can’t manage or govern what you can’t see, much less use it to make smart decisions. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

DataKitchen

DECEMBER 13, 2021

Gartner – Top Trends and Data & Analytics for 2021: XOps. What is a Data Mesh? DataOps Data Architecture. DataOps is Not Just a DAG for Data. Data Observability and Monitoring with DataOps. DataOps is NOT Just DevOps for Data. Launch Your DataOps Journey with the DataOps Maturity Model.

Data Architecture 246

Data Architecture Data Governance Testing Modeling 246

AWS Big Data

JANUARY 15, 2025

Data landscape in EUROGATE and current challenges faced in data governance The EUROGATE Group is a conglomerate of container terminals and service providers, providing container handling, intermodal transports, maintenance and repair, and seaworthy packaging services. Eliminate centralized bottlenecks and complex data pipelines.

IoT 110

IoT Machine Learning Metadata Data-driven 110

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. Passing the Data Governance Ball.

Data Governance 108

Data Governance Cost-Benefit Enterprise Modeling 108

AWS Big Data

DECEMBER 19, 2024

Initially, the data inventories of different services were siloed within isolated environments, making data discovery and sharing across services manual and time-consuming for all teams involved. Implementing robust data governance is challenging. Oghosa Omorisiagbon is a Senior Data Engineer at HEMA.

Data Governance 52

Data Governance Publishing Data-driven Metadata 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. You can review code changes directly on the platform, facilitating efficient teamwork.

Data Lake 104

Data Lake Data Warehouse Cost-Benefit Data Transformation 104

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

Cloudera

JUNE 14, 2024

At a time when artificial intelligence (AI) and tools like generative AI (GenAI) and large language models (LLMs) have exploded in popularity, getting the most out of organizational data is critical to driving business value and carving out a competitive market advantage.

Data Governance 74

Data Governance Data-driven Insurance Enterprise 74

Cloudera

DECEMBER 17, 2024

The introduction of these faster, more powerful networks has triggered an explosion of data, which needs to be processed in real time to meet customer demands. Traditional data architectures struggle to handle these workloads, and without a robust, scalable hybrid data platform, the risk of falling behind is real.

Enterprise 62

Enterprise Data Architecture Data-driven Optimization 62

CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

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 75

Data Governance Strategy Enterprise Machine Learning 75

Cloudera

JUNE 27, 2023

The way to achieve this balance is by moving to a modern data architecture (MDA) that makes it easier to manage, integrate, and govern large volumes of distributed data. When you deploy a platform that supports MDA you can consolidate other systems, like legacy data mediation and disparate data storage solutions.

Data Architecture 62

Data Architecture Predictive Modeling Data Governance Data-driven 62

AWS Big Data

OCTOBER 10, 2023

Data governance is the process of ensuring the integrity, availability, usability, and security of an organization’s data. 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 Quality 110

Data Quality Data Governance Data Lake Testing 110

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

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

CIO Business Intelligence

SEPTEMBER 20, 2023

With the new strategy, instead of implementing corporate assets in countries so they’re managed locally, what we want, through the cloud model, is to develop an asset as a service that countries can use. The third pillar of our strategy is data. This change in platform also entails a data governance model and operational changes.

Modeling 98

Modeling Insurance IT Cost-Benefit 98

IBM Big Data Hub

JANUARY 5, 2023

Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few. But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Metadata 84

Metadata Data Lake Dashboards Interactive 84

CIO Business Intelligence

MARCH 19, 2025

Yet, while businesses increasingly rely on data-driven decision-making, the role of chief data officers (CDOs) in sustainability remains underdeveloped and underutilized. However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive.

IT 59

IT Data Governance Data-driven Metrics 59

IBM Big Data Hub

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. 5 common data governance mistakes 1.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

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 Unstructured Data Data Governance Structured Data 99

AWS Big Data

JANUARY 31, 2023

Data governance is the collection of policies, processes, and systems that organizations use to ensure the quality and appropriate handling of their data throughout its lifecycle for the purpose of generating business value.

Data Lake 98

Data Lake Data Governance Data Architecture Machine Learning 98

CIO Business Intelligence

MARCH 6, 2024

SAP announced today a host of new AI copilot and AI governance features for SAP Datasphere and SAP Analytics Cloud (SAC). The company is expanding its partnership with Collibra to integrate Collibra’s AI Governance platform with SAP data assets to facilitate data governance for non-SAP data assets in customer environments. “We

Unstructured Data 129

Unstructured Data Dashboards Business Intelligence Data Governance 129

Cloudera

OCTOBER 19, 2022

The telecommunications industry continues to develop hybrid data architectures to support data workload virtualization and cloud migration. Telco organizations are planning to move towards hybrid multi-cloud to manage data better and support their workforces in the near future. 2- AI capability drives data monetization.

Optimization 78

Optimization Data Architecture Data Governance B2B 78

CIO Business Intelligence

JUNE 19, 2023

No industry generates as much actionable data as the finance industry, and as AI enters the mainstream, user behaviour and corporate production and service models will all need to quickly adapt. Resilient infrastructure is the key to delivering on the promise of real-time transformation of data into decisions, Mr. Cao said.

Finance 98

Finance Unstructured Data Data Processing Data Architecture 98

CIO Business Intelligence

JUNE 15, 2023

No industry generates as much actionable data as the finance industry, and as AI enters the mainstream, user behaviour and corporate production and service models will all need to quickly adapt. Resilient infrastructure is the key to delivering on the promise of real-time transformation of data into decisions, Mr. Cao said.

Unstructured Data 98

Unstructured Data Finance Data Processing Data Architecture 98

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

erwin

SEPTEMBER 16, 2024

Continue to conquer data chaos and build your data landscape on a sturdy and standardized foundation with erwin® Data Modeler 14.0. The gold standard in data modeling solutions for more than 30 years continues to evolve with its latest release, highlighted by: PostgreSQL 16.x

Modeling 52

Modeling Visualization Data Governance Data Architecture 52

Cloudera

FEBRUARY 15, 2024

Financial institutions must demonstrate robust risk accountability and governance, as well as maintain consumer protections. Cultural shift and technology adoption: Traditional banks and insurance companies must adapt to the emergence of fintech firms and changing business models.

Insurance 88

Insurance Data Architecture Risk Management Risk 88

BI-Survey

AUGUST 21, 2020

The data landscape and the data integration tasks to be solved are often too complex. Leaders rely less on data mart deployment than on lean, flexible architectures and usable data based on cloud services, a complementary data lake, data governance, data hubs and data catalogs.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

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 110

Data-driven Data Lake Data Quality Data Governance 110

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

AWS Big Data

APRIL 28, 2023

The third post will show how end-users can consume data from their tool of choice, without compromising data governance. When building a scalable data architecture on AWS, giving autonomy and ownership to the data domains are crucial for the success of the platform.

Data Governance 71

Data Governance Management Data-driven Analytics 71

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

Cloudera

AUGUST 20, 2024

Whether it’s rapidly rising costs, an inefficient and outdated data infrastructure, or serious gaps in data governance, there are myriad reasons why organizations are struggling to move past adoption and achieve AI at scale in their enterprises. Ensuring data is trustworthy comes with its own complications.

Data Architecture 82

Data Architecture Data Lake Data Governance Data Warehouse 82