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.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

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. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

Smart Data Collective

JULY 15, 2021

A data catalog serves the same purpose. By using metadata (or short descriptions), data catalogs help companies gather, organize, retrieve, and manage information. You can think of a data catalog as an enhanced Access database or library card catalog system. What Does a Data Catalog Consist Of?

Metadata 128

Metadata IT Data-driven Data Quality 128

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. What is Data Modeling?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

IBM Big Data Hub

SEPTEMBER 20, 2022

Alongside the significant brand reputation risk, there’s also a growing set of data and AI regulations across the world and across industries — like the upcoming European Union AI Act — that companies must adhere to. It’s not just about granting proper access to data science teams.

Metadata 57

Metadata Machine Learning Data-driven Modeling 57

Octopai

JUNE 1, 2020

Data mapping is the cornerstone of many important business intelligence processes: Data Integration – Even if systems are compatible, combining two disparate data repositories still requires meticulous data mapping. Manual Metadata Management Hinders Compliance.

Metadata 52

Metadata Data Warehouse Data Integration Enterprise 52

erwin

APRIL 27, 2022

Read more about erwin® Data Intelligence by Quest. Best Data Modeling Solution (erwin Data Modeler). Extensive automation and collaboration functionality speed development cycles and minimize the risks of bugs and performance issues. Read more about Toad® for Oracle Developer Edition by Quest.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

CIO Business Intelligence

APRIL 27, 2022

All are ideally qualified to help their customers achieve and maintain the highest standards for data integrity, including absolute control over data access, transparency and visibility into the provider’s operation, the knowledge that their information is managed appropriately, and access to VMware’s growing ecosystem of sovereign cloud solutions.

Digital Transformation 107

Digital Transformation Metadata Risk Management 107

Cloudera

AUGUST 31, 2021

Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. Consideration of both data & metadata in the migration.

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

erwin

MAY 2, 2022

One must also capture the vast quantity of metadata around the OLTP business requirements that must be reflected. I’m not proposing that business logic be held in the database, but it needs to be documented in the data model even if it will be implemented in application code. Even more information about erwin Data Modeler.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Those days are long gone if they ever existed.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. This may also entail working with new data through methods like web scraping or uploading.

Enterprise 77

Enterprise Data Integration Data Quality Contextual Data 77

O'Reilly on Data

MARCH 20, 2019

Like many others, I’ve known for some time that machine learning models themselves could pose security risks. Data integrity constraints: Many databases don’t allow for strange or unrealistic combinations of input variables and this could potentially thwart watermarking attacks. Disparate impact analysis: see section 1.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. We bundle these events under the collective term “Risk and Opportunity Events” This post is part of Ontotext’s AI-in-Action initiative aimed to empower data, scientists, architects and engineers to leverage LLMs and other AI models.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

erwin

FEBRUARY 4, 2021

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. It uncovered a number of obstacles that organizations have to overcome to improve their data operations.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) This allows for a high degree of transparency and auditability.

Cost-Benefit 81

Cost-Benefit Metadata Data Governance Modeling 81

Ontotext

SEPTEMBER 2, 2020

The risk is that the organization creates a valuable asset with years of expertise and experience that is directly relevant to the organization and that valuable asset can one day cross the street to your competitors. Data is represented in a holistic, human-friendly and meaningful way. For efficient drug discovery, linked data is key.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Andrew White

JANUARY 9, 2022

Is there a good map that shows the connections between data, advanced analytics, digital, innovation, etc. I would have to admit that there are few documents that talk about all the connections across any set of topics. Much as the analytics world shifted to augmented analytics, the same is happening in data management.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Alation

FEBRUARY 10, 2022

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Identify data governed by GDPR &CCPA , HIPAA, PCI, SOX, and BCBS.

Data Governance 52

Data Governance Risk Insurance Strategy 52

erwin

NOVEMBER 6, 2020

To better explain our vision for automating data governance, let’s look at some of the different aspects of how the erwin Data Intelligence Suite (erwin DI) incorporates automation. Data Cataloging: Catalog and sync metadata with data management and governance artifacts according to business requirements in real time.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

erwin

JULY 17, 2019

EA and BP modeling squeeze risk out of the digital transformation process by helping organizations really understand their businesses as they are today. Your organization won’t be able to take complete advantage of analytics tools to become data-driven unless you establish a foundation for agile and complete data management.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 1, 2023

CEO Priorities Grow revenue and “hit the number” Manage costs and meet profitability goals Attract and retain talent Innovate and out-perform the competition Manage risk Connect the Dots Present embedded analytics as a way to differentiate from the competition and increase revenue. Present your business case.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

JUNE 9, 2022

Access to these updated views enables your teams to be more self-sufficient and lowers the risk associated with view regeneration. Angles Hub incorporates “Google-style” search technology that reveals and catalogs all metadata, including user-defined tags. To enable rapid and efficient response to business disruptions, version 22.1

Operational Reporting 52

Operational Reporting Reporting Data Warehouse Cost-Benefit 52