erwin

JANUARY 9, 2020

For decades, data modeling has been the optimal way to design and deploy new relational databases with high-quality data sources and support application development. Today’s data modeling is not your father’s data modeling software. So here’s why data modeling is so critical to data governance.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

erwin

OCTOBER 8, 2020

No less daunting, your next step is to re-point or even re-platform your data movement processes. And you can’t risk false starts or delayed ROI that reduces the confidence of the business and taint this transformational initiative. The metadata-driven suite automatically finds, models, ingests, catalogs and governs cloud data assets.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

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 127

Metadata IT Data-driven Data Quality 127

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

Octopai

FEBRUARY 26, 2024

A Strategic Approach to Data Cleansing With Octopai’s automated data lineage, data cleansing transcends its traditional role, becoming a strategic endeavor that drives efficiency, ensures data integrity, and unlocks business insights.

Metadata 52

Metadata ROI Optimization Data-driven 52

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

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

erwin

JANUARY 30, 2020

The results of our new research show that organizations are still trying to master data governance, including adjusting their strategies to address changing priorities and overcoming challenges related to data discovery, preparation, quality and traceability. And close to 50 percent have deployed data catalogs and business glossaries.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

CIO Business Intelligence

APRIL 29, 2022

Preparing for an artificial intelligence (AI)-fueled future, one where we can enjoy the clear benefits the technology brings while also the mitigating risks, requires more than one article. This first article emphasizes data as the ‘foundation-stone’ of AI-based initiatives. Establishing a Data Foundation. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

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 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. SQL or NoSQL?

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

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

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

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

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 70

Data Quality Data Integration Metadata Cost-Benefit 70

erwin

APRIL 27, 2022

Best Data Modeling Solution (erwin Data Modeler). Read more about erwin® Data Modeler by Quest. 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

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

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. By slowing down, and gathering intelligence about the data in a platform like Alation.

Data Warehouse 52

Data Warehouse Data-driven Digital Transformation Metadata 52

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

CIO Business Intelligence

DECEMBER 16, 2022

With a sovereign cloud, an organization can collect data to share securely with vetted research firms who can then study the data to uncover new trends and info. This trusted ecosystem can even be utilized by other trusted groups, such as sharing anonymized or encrypted data, without risking a privacy breach from foreign entities.

Cost-Benefit 52

Cost-Benefit Metadata Risk Enterprise 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 111

Digital Transformation Metadata Risk Management 111

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

erwin

MAY 2, 2022

Data modeling is a serious scientific method with many rules and best practices. One must also capture the vast quantity of metadata around the OLTP business requirements that must be reflected. However, it offers two extremely valuable business benefits: reducing data redundancy and improving data integrity.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

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 82

Enterprise Data Integration Data Quality Contextual Data 82

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

DataKitchen

SEPTEMBER 21, 2023

Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. There are multiple locations where problems can happen in a data and analytic system. What is Data in Use? ” For example, these tools may offer metadata-based notifications.

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

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. Automate code generation : Alleviate the need for developers to hand code connections from data sources to target schema.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89

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 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

AWS Big Data

NOVEMBER 29, 2023

With Redshift, we are able to view risk counterparts and data in near real time— instead of on an hourly basis. Amazon Redshift ML large language model (LLM) integration Amazon Redshift ML enables customers to create, train, and deploy machine learning models using familiar SQL commands.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

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

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.)

Cost-Benefit 85

Cost-Benefit Metadata Data Governance Modeling 85

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Then, you transform this data into a concise format.

Data Strategy 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Alation

JULY 28, 2022

The cloud is no longer synonymous with risk. There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. I am not interested in owning that risk internally.” What Are the Biggest Business Risks to Cloud Data Migration? Lower control.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

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. Ensuring the authenticity of data is crucial in preventing potential disputes over authorship in multi-party interactions.

Data Governance 70

Data Governance Manufacturing Interactive IoT 70

Ontotext

FEBRUARY 26, 2024

Each additional graph use case increases its derived value thanks to reducing costs, adding new capabilities, and minimizing risk. Bad Data Tax and the Data Bill of Rights So far, our discussion has been pretty theoretical, so we need a compelling business justification for moving in this direction. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

FEBRUARY 21, 2023

Loading complex multi-point datasets into a dimensional model, identifying issues, and validating data integrity of the aggregated and merged data points are the biggest challenges that clinical quality management systems face. And for data models that can be directly reported, a dimensional model can be developed.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63