erwin

OCTOBER 8, 2020

That means your cloud data assets must be available for use by the right people for the right purposes to maximize their security, quality and value. Why You Need Cloud Data Governance. Regulatory compliance is also a major driver of data governance (e.g., GDPR, CCPA, HIPAA, SOX, PIC DSS).

Data Governance 145

Data Governance Metadata Testing Data Lake 145

erwin

JANUARY 30, 2020

I’m excited to share the results of our new study with Dataversity that examines how data governance attitudes and practices continue to evolve. Defining Data Governance: What Is Data Governance? . 1 reason to implement data governance. Most have only data governance operations.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

erwin

JANUARY 9, 2020

That’s because it’s the best way to visualize metadata , and metadata is now the heart of enterprise data management and data governance/ intelligence efforts. So here’s why data modeling is so critical to data governance. erwin Data Modeler: Where the Magic Happens.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 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. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

erwin

FEBRUARY 4, 2021

Better decision-making has now topped compliance as the primary driver of data governance. However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. Points of integration. Sources, like IoT.

Data Governance 89

Data Governance Metadata Data Quality IoT 89

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

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

David Menninger's Analyst Perspectives

OCTOBER 24, 2024

Data silos are a perennial data management problem for enterprises, with almost three-quarters (73%) of participants in ISG Research’s Data Governance Benchmark Research citing disparate data sources and systems as a data governance challenge.

Management 130

Management Data-driven Data Governance Data Lake 130

Data Virtualization

DECEMBER 21, 2023

Reading Time: 2 minutes Data mesh is a modern, distributed data architecture in which different domain based data products are owned by different groups within an organization. And data fabric is a self-service data layer that is supported in an orchestrated fashion to serve.

Data Governance 59

Data Governance Data Architecture Data Integration Management 59

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

CIO Business Intelligence

APRIL 29, 2022

Data-centric AI is evolving, and should include relevant data management disciplines, techniques, and skills, such as data quality, data integration, and data governance, which are foundational capabilities for scaling AI. Addressing the Challenge.

Data Governance 145

Data Governance IT Risk Data Lake 145

IBM Big Data Hub

AUGUST 24, 2022

The only question is, how do you ensure effective ways of breaking down data silos and bringing data together for self-service access? It starts by modernizing your data integration capabilities – ensuring disparate data sources and cloud environments can come together to deliver data in real time and fuel AI initiatives.

Data Integration 79

Data Integration Metadata Data-driven Data Architecture 79

erwin

JANUARY 24, 2019

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. Governing metadata.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

IBM Big Data Hub

APRIL 9, 2018

There’s a general need for next-gen executives to not only understand corporate regulations, but be able to adhere to and follow them using metadata solutions like data governance.

Data Governance 89

Data Governance Metadata Data Integration Analytics 89

IBM Big Data Hub

AUGUST 7, 2023

Transparency throughout the data lifecycle and the ability to demonstrate data integrity and consistency are critical factors for improvement. The ledger delivers tamper evidence, enabling the detection of any modifications made to the data, even if carried out by privileged users.

Data Governance 62

Data Governance Manufacturing Interactive IoT 62

Ontotext

JANUARY 10, 2024

And each of these gains requires data integration across business lines and divisions. Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

DataKitchen

AUGUST 16, 2024

At DataKitchen, we think of this is a ‘meta-orchestration’ of the code and tools acting upon the data. Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata.

Marketing 126

Marketing Data Quality Testing Metadata 126

IBM Big Data Hub

MARCH 25, 2022

A data fabric is an architectural approach that enables organizations to simplify data access and data governance across a hybrid multicloud landscape for better 360-degree views of the customer and enhanced MLOps and trustworthy AI. Protection is applied on each data pipeline.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

IBM Big Data Hub

SEPTEMBER 12, 2022

The journey starts with having a multimodal data governance framework that is underpinned by a robust data architecture like data fabric. What’s more, a data fabric can automate data governance and security by creating a governance layer across the lifecycle. Then intelligent automation begins.

Metadata 91

Metadata Data Governance Enterprise Data Architecture 91

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored.

Modeling 98

Modeling Metadata Data Governance Visualization 98

erwin

FEBRUARY 6, 2020

As organizations deal with managing ever more data, the need to automate data management becomes clear. Last week erwin issued its 2020 State of Data Governance and Automation (DGA) Report. One piece of the research that stuck with me is that 70% of respondents spend 10 or more hours per week on data-related activities.

Management 144

Management Data Governance Cost-Benefit Metadata 144

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. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. 11 May 2021. . 3 March 2022.

Management 79

Management Metadata Data Architecture Data Lake 79

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

O'Reilly on Data

JANUARY 29, 2019

These include data integration and extract, transform, and load (ETL) (60% of respondents indicated they were building or evaluating solutions), data preparation and cleaning (52%), data governance (31%), metadata analysis and management (28%), and data lineage management (21%).

Deep Learning 211

Deep Learning Machine Learning Data Science Metadata 211

CIO Business Intelligence

FEBRUARY 2, 2024

Developer, Professional Certification Mastering Data Management and Technology SAP Certified Application Associate – SAP Master Data Governance The Art of Service Master Data Management Certification The Art of Service Master Data Management Complete Certification Kit validates the candidate’s knowledge of specific methods, models, and tools in MDM.

Management 116

Management Data Governance Cost-Benefit Testing 116

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

Alation

DECEMBER 6, 2022

Diby Malakar joins as our new Vice President of Product Management, Cloud & Technical Metadata Platform and Jonathan Bruce is our new Vice President of Product Management, Catalog, Governance & Data Exploration Apps & Logical Metadata Platform. Oversee the connectors and lineage product areas.

Metadata 52

Metadata Enterprise Data Integration Data Quality 52

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

Jen Stirrup

MARCH 29, 2023

However, to turn data into a business problem, organizations need support to move away from technical issues to start getting value as quickly as possible. SAP Datasphere simplifies data integration, cataloging, semantic modeling, warehousing, federation, and virtualization through a unified interface. Why is this interesting?

Data Warehouse 121

Data Warehouse Metadata Data Integration Business Intelligence 121

IBM Big Data Hub

NOVEMBER 4, 2022

Data observability capability makes data quality checks upstream possible. Data Governance. Ensuring data quality is critical for data governance initiatives. IBM’s holistic approach to Data Quality.

Data Quality 56

Data Quality Metadata Data Governance Data-driven 56

AWS Big Data

JUNE 10, 2024

In this post, we delve into the key aspects of using Amazon EMR for modern data management, covering topics such as data governance, data mesh deployment, and streamlined data discovery. Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated.

Data Lake 90

Data Lake Metadata Data Warehouse Data Processing 90

IBM Big Data Hub

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

IBM Big Data Hub

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Data integration.

Data-driven 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

Alation

DECEMBER 15, 2022

March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

IBM Big Data Hub

JULY 6, 2022

With traditional approaches , data issues are reported by data users as they try to access and use the data and may take weeks to fix, if they’re found at all. starts at the data source, collecting data pipeline metadata across key solutions in the modern data stack like Airflow, dbt, Databricks and many more.

Metadata 56

Metadata Data Quality Snapshot Cost-Benefit 56