Ontotext

NOVEMBER 23, 2023

If there are any inconsistencies, the shapes will be rejected and you will receive a violation report. Data engineers think about “shapes” and “data” separately and treating shapes as data is an implementation detail. However, all of this data is added to the same graph.

Data Quality 69

Data Quality Reporting Metadata IT 69

CIO Business Intelligence

MARCH 24, 2023

It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

DataKitchen

AUGUST 8, 2023

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.

Data Quality 130

Data Quality Testing Snapshot Reporting 130

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data. Data Governance.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

erwin

SEPTEMBER 17, 2020

According to erwin’s “2020 State of Data Governance and Automation” report , close to 70 percent of data professional respondents say they spend an average of 10 or more hours per week on data-related activities, and most of that time is spent searching for and preparing data.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

erwin

JANUARY 30, 2020

The 2020 State of Data Governance and Automation (DGA) report is a follow-up to an initial survey we commissioned two years ago to explore data governance ahead of the European Union’s General Data Protection Regulation (GDPR) going into effect. 1 reason to implement data governance.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130

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 Do?

Metadata 126

Metadata IT Data-driven Data Quality 126

Ontotext

MAY 2, 2024

These models are as important to companies as their frontline products and determine how data is managed, consumed, combined, joined, and analyzed. Data-centric approach In the data-centric approach, metadata serves as a layer of interoperability between the data sources.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document, first published in 2013, outlines best practices for global and domestic banks to identify, manage, and report risks, including credit, market, liquidity, and operational risks.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

Ontotext

MAY 22, 2023

At the heart of such tools is the extraction of fields from forms or specific attributes from documents. Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data. That’s something that LLMs cannot do.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Assess Data Quality.

Management 52

Management Data Quality Metadata Testing 52

DataRobot Blog

MAY 10, 2022

The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. This is confirmed by SR 11-7, which asserts that model risk arises from the “ adverse consequences from decisions based on incorrect or misused model outputs and reports.”

Risk 64

Risk Modeling Machine Learning Data Quality 64

Alation

MAY 17, 2022

An enterprise data catalog is one such key asset. The Data Analyst Workflow. The workflow of a data analyst consists of four key stages: Discovery. When a businessperson poses a question to an analyst, the analyst starts by trying to find the right data. 7 Steps that Benefit from a Data Catalog. Preparation.

Metadata 52

Metadata Data Quality Machine Learning Reporting 52

BI-Survey

FEBRUARY 23, 2023

Data knowledge is essential to data and analytics There is a clear understanding that data is an asset to the organization. Almost three quarters of respondents also state that they have recognized the need to invest in ways to access, link and understand metadata. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

AWS Big Data

MARCH 7, 2023

Sources Data can be loaded from multiple sources, such as systems of record, data generated from applications, operational data stores, enterprise-wide reference data and metadata, data from vendors and partners, machine-generated data, social sources, and web sources.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

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. So questions linger about whether transformed data can be trusted. Data Quality Obstacles.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

OCTOBER 5, 2021

Yet, so many companies today are still failing miserably in implementing data strategy and governance protocols. Why is your data governance strategy failing? Inconsistencies in expectations can create enormous negative issues regarding data quality and governance. Data governance and AI.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

erwin

APRIL 15, 2020

If we reflect on the coronavirus example, we can ask: How do individual countries report their data? Are asymptomatic infections reported? erwin Data Intelligence for Data Governance and Distancing. Do individual countries use the same testing protocols?

Data Governance 134

Data Governance Metadata Testing Reporting 134

Octopai

JUNE 24, 2019

Document classification and lifecycle management will help you deal with oversight of unstructured data. – Data management : As part of maintaining the integrity of your data, it will be necessary to track activities. This maintains a high priority in your data governance strategy.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

O'Reilly on Data

DECEMBER 19, 2018

Given that the results produced by any model will reflect the data used to create the model, how do you ensure your data collection process is fair, representative, and unbiased? This isn’t surprising; if you’re collecting data from several weather stations and one of them malfunctions, you would expect to see anomalous data.

Machine Learning 262

Machine Learning Software Metadata Testing 262

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. The RDF data model and the other standards in W3C’s Semantic Web stack (e.g.,

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

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

AWS Big Data

MARCH 1, 2024

The detail of each file is provided in the following list: credit_card_transaction_PCI_public – Contains credit card transactions categorized as public data and visible to principals who has access to public data. lob_risk_High_confidential_public – Contains business reports that are accessed or shared by public.

Data Lake 100

Data Lake Data Warehouse Management Risk 100

Sanjeev Mohan

FEBRUARY 6, 2019

Then in the middle of 2017, a realization set in that we were one year away from GDPR and needed to focus on data governance. I ended up writing two documents on data governance. To address client questions about cloud, I wrote a document on GCP. The post Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline?

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

CIO Business Intelligence

JANUARY 30, 2024

Corporate ESG reporting is getting real for companies around the globe. Enacted and proposed regulations in the EU, US, and beyond are deepening reporting requirements in an effort to change business behavior. The foundation for ESG reporting, of course, is data. The foundation for ESG reporting, of course, is data.

Reporting 103

Reporting Data Quality Strategy Data-driven 103

Ontotext

MARCH 8, 2023

Solution Outcomes: A semantic recommendation service that is beating accuracy benchmarks and replacing manual processes aggregating content – that is supporting higher-quality, more advanced, and targeted recommendations with clear reasons. Which financial institutions are behind on their risk reporting and filings this year?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

O'Reilly on Data

JULY 28, 2020

Many companies face a problem that’s even worse: no one knows which levers contribute to the metrics that impact business outcomes, or which metrics are important to the company (such as those reported to Wall Street by publicly-traded companies). Data Quality and Standardization. If the product isn’t “viable” (i.e.,

Marketing 362

Marketing Experimentation Metrics Testing 362

Domino Data Lab

JULY 21, 2019

how modern approaches can be used to obtain better quality data, and at a lower cost, to help support evidence-based policy decisions. unique challenges of sharing confidential government microdata and the importance of access in generating high quality inference. What am I talking about with the new types of data?

Metadata 65

Metadata Statistics Risk Machine Learning 65

erwin

OCTOBER 24, 2019

Untapped data, if mined, represents tremendous potential for your organization. While there has been a lot of talk about big data over the years, the real hero in unlocking the value of enterprise data is metadata , or the data about the data. Metadata Is the Heart of Data Intelligence.

Metadata 104

Metadata Management Data-driven Data Architecture 104

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. Data and analytics (and maybe AI) are getting very tired terms. Where the CDO reports.

Analytics 68

Analytics Metadata Data Governance Management 68

AWS Big Data

AUGUST 14, 2023

Trunk (core data products) – Core data products are those that are central to the organization’s ability to function, and from which the majority of other data products are derived. Organizational governance for these data products typically favors availability and data accuracy over agility.

Management 79

Management Risk Measurement Optimization 79

CIO Business Intelligence

JANUARY 15, 2024

With seven operating centers, nine research facilities, and more than 18,000 staff, the agency continually generates an overwhelming amount of data, which it stores in more than 30 science data repositories across five topical areas — astrophysics, heliophysics, biological science, physical science, earth science, and planetary science.

Informatics 120

Informatics Metadata Data mining Digital Transformation 120

erwin

FEBRUARY 4, 2021

So what’s holding organizations back from fully using their data to make better, smarter business decisions? Data Governance Bottlenecks. 1 bottleneck, according to 62 percent of respondents, was documenting complete data lineage. Overcoming Data Governance Bottlenecks.

Data Governance 89

Data Governance Metadata Data Quality Risk Management 89