erwin

JANUARY 9, 2020

It is a tried-and-true practice for lowering data management costs, reducing data-related risks, and improving the quality and agility of an organization’s overall data capability. 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.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

erwin

MARCH 30, 2020

These numerous data types and data sources most definitely weren’t designed to work together. Unraveling Data Complexities with Metadata Management. Metadata management will be critical to the process for cataloging data via automated scans. Data profiling for data assessment, metadata discovery and data validation.

Metadata 122

Metadata IT Data Governance Data Quality 122

Rocket-Powered Data Science

FEBRUARY 15, 2023

3) How do we get started, when, who will be involved, and what are the targeted benefits, results, outcomes, and consequences (including risks)? A business-disruptive ChatGPT implementation definitely fits into this category: focus first on the MVP or MLP. The latter is essential for Generative AI implementations.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

AWS Big Data

APRIL 19, 2023

Instead, we can use automation to speed up the process of migration and reduce heavy lifting tasks, costs, and risks. We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. Generate Spark SQL metadata Our batch job consists of Hive steps scheduled to run sequentially.

Metadata 83

Metadata Testing Data Lake Consulting 83

Octopai

MAY 31, 2022

A data catalog uses your data ecosystem’s metadata to build a complete picture of every data asset: definition, calculation, access level, stewardship roles, and previews. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics. Asset, here we come!

Management 52

Management Metadata Business Intelligence ROI 52

erwin

OCTOBER 31, 2019

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed. So being prepared means you can minimize your risk exposure and the damage to your reputation. No Hocus Pocus.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

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

Cloudera

AUGUST 3, 2021

Advanced analytics empower risk reduction . Advanced analytics and enterprise data are empowering several overarching initiatives in supply chain risk reduction – improved visibility and transparency into all aspects of the supply chain balanced with data governance and security. . Digital Transformation is not without Risk.

Analytics 110

Analytics Digital Transformation Forecasting Risk 110

CIO Business Intelligence

MARCH 4, 2024

Harmonizing these data sets with centralized enterprise data faces increasing challenges as shifts to data definitions, schema, and architecture require constant central data team efforts. To deliver a cohesive data strategy, seamless data access and sharing requires the breaking down of data silos.

Insurance 98

Insurance Strategy Data Governance Data Integration 98

Cloudera

JUNE 7, 2023

By now, almost everyone across the tech landscape has heard of the Zero Trust (ZT) security model, which assumes that every device, application, or user attempting to access a network is not to be trusted (see NIST definitions below). But as models go, the idea is easier than the execution.

Metadata 84

Metadata Data Lake Optimization Modeling 84

datapine

SEPTEMBER 29, 2022

What is the definition of data quality? It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports. This way, you make sure there is a common understanding of data definitions that are being used across the organization. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

CIO Business Intelligence

FEBRUARY 14, 2024

People aren’t going back and decluttering because there’s no cost to that — except in your risk profile and your decreased search performance,” says Buckley. The other problem is gen AI tools and users not seeing information that should be included because the metadata tagging and sensitivity labels haven’t been correctly applied to the data.

IT 143

IT Metadata Data-driven Management 143

erwin

AUGUST 6, 2020

Data Literacy Definition. It also provides a business glossary for the collaborative definition of enterprise data in business terms. Data Context & Enrichment: Put data in business context and enable stakeholders to share best practices and build communities by tagging/commenting on data assets, enriching the metadata.

Contextual Data 135

Contextual Data Data Governance Digital Transformation Metadata 135

Alation

APRIL 18, 2023

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. Definition and purpose of data profiling Data profiling is the process of analyzing and assessing the quality, structure, and content of data. What is data profiling?

IT 52

IT Metadata Data Quality Data Governance 52

erwin

APRIL 15, 2020

Does the definition (description, classification, allowable range of values, etc.) of incoming, individual data elements match our internal definitions of those data elements? This deeper understanding will help us make better decisions about the risks and rewards of using that external data. What formulas were used?

Data Governance 134

Data Governance Metadata Testing Reporting 134

Ontotext

DECEMBER 16, 2021

Many rich sources of information in the medical world are written documents with poor quality metadata. When dealing with that volume of data, manual processes run the risk of someone overlooking a critical piece of information and creating a liability for the company. Literature review . Regulatory reporting.

Metadata 98

Metadata Reporting Unstructured Data Risk 98

CIO Business Intelligence

APRIL 19, 2022

The European Union wishes to mitigate dependence and the risk of foreign access to critical data, also considering that cloud is the powerhouse of AI, and other essential technology. The amount of metadata that cloud providers are collecting is much greater than people realise. Sovereign cloud to ensure data sovereignty.

Metadata 58

Metadata Risk Data-driven Strategy 58

Smart Data Collective

JULY 27, 2021

Metazoa CEO Jennifer Mercer doesn’t think that either of those definitions is very helpful, especially when it comes to Salesforce. As such, when it starts generating piles of technical debt, customers are at risk of system failure. As with Salesforce’s APEX, SAP’s ABAP is what drives the CRM’s extremely complex ecosystem.

Big Data 131

Big Data Snapshot IT Dashboards 131

Alation

FEBRUARY 13, 2020

A Data Catalog is a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses. Figure 1 – Data Catalog Metadata Subjects. Conclusion.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

erwin

AUGUST 7, 2019

With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects. A data catalog benefits organizations in a myriad of ways.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Alation

OCTOBER 26, 2021

They need trusted data to drive reliable reporting, decision-making, and risk reduction. A business glossary helps an organization agree and align on internal definitions. Consistent, reliable reporting can then drive more positive outcomes for the entire business, including improved compliance, risk reduction, and increased revenue.

Finance 52

Finance Data Transformation Enterprise Metrics 52

Octopai

DECEMBER 11, 2022

Banks didn’t accurately assess their credit and operational risk and hold enough capital reserves, leading to the Great Recession of 2008-2009. Data lineage and financial risk data compliance. All these models need to be informed by data, with operational risk assessment mandating loss data that goes back 10 years. .

Insurance 52

Insurance Risk Metadata Reporting 52

Rita Sallam

APRIL 2, 2023

Qlik Key Findings: In the US alone, there’s $367 billion in agricultural commodities at risk to flooding in the US alone. A large part of under-developed Asian countries ranging from Bangladesh to Vietnam are at high risk of flooding events. million people at risk of catastrophic, flooding. In 2000, the Netherlands had 8.5

Optimization 52

Optimization Machine Learning Insurance Risk 52

Alation

SEPTEMBER 21, 2021

It is people, process, technology, and data — more importantly, metadata. Metadata provides technical and behavioral intelligence about data that can be used to decide where to start and how to plot a course to the destination, including who needs to be involved and who can offer assistance if roadblocks are encountered.

Metadata 52

Metadata Testing Recreation/Entertainment Data-driven 52

Cloudera

SEPTEMBER 15, 2022

” NetApp provides a more robust definition of data fabric as “an architecture and set of data services that provide consistent capabilities across hybrid, multi-cloud environments.” Luke: In your experience, what’s the most practical definition of data fabric for companies thinking about implementing it? What is a data fabric?

Data Lake 84

Data Lake Data Architecture Data-driven Data Warehouse 84

CDW Research Hub

MAY 29, 2019

Data governance helps organizations manage their information and answer questions about business performance, allowing them to better understand data, and govern it to mitigate compliance risks and empower information stakeholders. Agree on a definition of data governance for organization. Then, prioritize where you want to be.

Data Governance 40

Data Governance Data Quality ROI Metadata 40

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. What Is Metadata? Analyst firm Gartner defines metadata as “information that describes various facets of an information asset to improve its usability throughout its life cycle. It is metadata that turns information into an asset.”.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Octopai

DECEMBER 10, 2019

Let’s look at why: Companies need to utilize shared data to make informed decisions, but when data is sent from one department to another there is always the risk of miscommunication. It should go beyond just listing definitions to key terms. One of the best ways to solve this issue is to create a business glossary.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

Alation

JUNE 22, 2021

While this is an excellent working definition, we believe it’s helpful to think of data literacy by analogy to Maslow’s Hierarchy , where needs (or skills) are layered atop each other. Nowadays, sites like Wikipedia use metadata to reduce the risk of a less media-literate individual getting hoodwinked. What is Data Literacy?

Data Governance 64

Data Governance Data-driven Metadata Visualization 64

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

Cloudera

AUGUST 31, 2021

It has a consistent framework that secures and provides governance for all data and metadata on private clouds, multiple public clouds, or hybrid clouds. These schemas will be created based on its definitions in existing legacy data warehouses. Consideration of both data & metadata in the migration. All rights reserved.

Data Warehouse 84

Data Warehouse Cost-Benefit Metadata Data-driven 84

Domino Data Lab

APRIL 3, 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. Definition and Descriptions. We’ll start with standard definitions – the currently accepted wisdom in the industry. That definition plus the one-liner provide good starting points.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

JUNE 14, 2021

Do we know the business outcomes tied to data risk management? To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management. “Everything starts by answering basic questions,” says Wayne Anderson, Principal, Security Architect, Microsoft. What do we know?

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

erwin

OCTOBER 24, 2019

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. And to truly understand it , you need to be able to create and sustain an enterprise-wide view of and easy access to underlying metadata. This isn’t an easy task.

Metadata 104

Metadata Management Data-driven Data Architecture 104

erwin

DECEMBER 20, 2018

Whether implemented as preventative measures (risk management and regulation) or proactive endeavors (value creation and ROI), the benefits of a data governance initiative is becoming more apparent. But to ensure the collaborative take on data governance is implemented properly, an organization must settle on a common definition.

Data Governance 40

Data Governance ROI Risk Management Metadata 40

erwin

MAY 2, 2022

One must also capture the vast quantity of metadata around the OLTP business requirements that must be reflected. It’s not very hard at all once you know the definition and have some rather simple visual examples. Video: Empower 2021: Mitigating the risk associated with sensitive data across the enterprise.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

Anmut

OCTOBER 29, 2020

In dealing with situations like pandemic data, how important are aspects of data governance such as standardised definitions? These clarify how to certify COVID-19 as a cause of death, where it should be recorded, what terminology to use, how to code COVID-19 for mortality, and what variables and metadata are to be submitted to WHO.

Data Governance 52

Data Governance Data Collection Data-driven Statistics 52