DataRobot Blog

MAY 10, 2022

Addressing the Key Mandates of a Modern Model Risk Management Framework (MRM) When Leveraging Machine Learning . The regulatory guidance presented in these documents laid the foundation for evaluating and managing model risk for financial institutions across the United States. To reference SR 11-7: .

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Risk Modeling Machine Learning Data Quality 64

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 in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

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Metadata Data Governance Digital Transformation Data Quality 52

Octopai

MARCH 23, 2022

If today, federal inspections and authorizations of meatpacking plants are made with some level of reliance on data systems (and they almost certainly are), then dirty data could even lead directly to dirty meat. Data lineage tools give you exactly that kind of transparent, x-ray vision into your data quality.

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Data Quality Reporting Modeling Interactive 91

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

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Data Governance Management Metadata Data Quality 142

AWS Big Data

FEBRUARY 29, 2024

Implement data privacy policies. Implement data quality by data type and source. Let’s look at some of the key changes in the data pipelines namely, data cataloging, data quality, and vector embedding security in more detail. Link structured and unstructured datasets.

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Data Governance Unstructured Data Metadata Data Lake 94

DataKitchen

OCTOBER 20, 2023

Deploying a Data Journey Instance unique to each customer’s payload is vital to fill this gap. Such an instance answers the critical question of ‘Dude, Where is my data?’ ’ while maintaining operational efficiency and ensuring data quality—thus preserving customer satisfaction and the team’s credibility.

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Insurance Metadata Data-driven Data Quality 176

erwin

MARCH 30, 2020

To marry the epidemiological data to the population data it will require a tremendous amount of data intelligence about the: Source of the data; Currency of the data; Quality of the data; and. Unraveling Data Complexities with Metadata Management. Data lineage to support impact analysis.

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Metadata IT Data Governance Data Quality 122

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Find Trusted Data.

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erwin

DECEMBER 3, 2020

Ultra Mobile recently shared how it uses erwin Data Intelligence (erwin DI) as part of a modern, ongoing approach to data governance and therefore control versus chaos. To manage not only risk but also to grow and compete effectively requires the ability to deal with both planned and unplanned change.

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Metadata Data Governance Data-driven Digital Transformation 141

Octopai

JUNE 19, 2023

Data Catalogs also allow for Improved Collaboration by serving as a central repository for enterprise data, a data catalog facilitates collaboration among different teams. Everyone has access to the same data and the same understanding of what the data represents, reducing miscommunications and discrepancies.

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Metadata Data Governance Measurement Risk Management 88

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.

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Metadata Data Quality Data-driven Data Governance 52

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?

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Metadata IT Data-driven Data Quality 125

erwin

APRIL 29, 2020

An understanding of the data’s origins and history helps answer questions about the origin of data in a Key Performance Indicator (KPI) reports, including: How the report tables and columns are defined in the metadata? Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

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Metadata Data Governance Key Performance Indicator Data Quality 111

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.

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IT Data Quality Metadata Data Governance 52

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.

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Data Governance Risk Metadata Management 40

Cloudera

MARCH 3, 2022

In 2017, Anthem reported a data breach that exposed thousands of its Medicare members. The medical insurance company wasn’t hacked, but its customers’ data was compromised through a third-party vendor’s employee. 86% of Experian survey respondents’, for instance, are prioritizing moving their data to the cloud in 2022.

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Data Governance Enterprise Data Quality Metadata 95

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance. Strengthen data security. How erwin Can Help.

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Data Governance Management Metadata Risk Management 110

IBM Big Data Hub

APRIL 20, 2023

When consumers lose trust in a bank’s ability to manage risk, the system stops working. Banks and their employees place trust in their risk models to help ensure the bank maintains liquidity even in the worst of times. This can ensure that the decisions made are reliable and of high quality.

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Risk Risk Management Reporting Metadata 72

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)? Love thy data: data are never perfect, but all the data may produce value, though not immediately. The latter is essential for Generative AI implementations.

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Strategy Experimentation Uncertainty Machine Learning 289

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.

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Metadata Risk Management Business Intelligence Data Governance 61

CIO Business Intelligence

NOVEMBER 22, 2022

As a result, a growing number of IT leaders are looking for data strategies that will allow them to manage the massive amounts of disparate data located in silos without introducing new risk and compliance challenges. The fabric, especially at the active metadata level, is important, Saibene notes.

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Data Strategy Strategy Enterprise Consulting 145

Ontotext

FEBRUARY 12, 2024

Domain teams should continually monitor for data errors with data validation checks and incorporate data lineage to track usage. Establish and enforce data governance by ensuring all data used is accurate, complete, and compliant with regulations. For instance, JPMorgan Chase & Co.

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Data Quality Data-driven Data Lake Data Governance 69

CIO Business Intelligence

MARCH 4, 2024

To deliver a cohesive data strategy, seamless data access and sharing requires the breaking down of data silos. This is where data fabric tools with their focus on orchestration, contextual layering, and metadata management are important elements to add to the equation.

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Insurance Strategy Data Governance Data Integration 98

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 93

Strategy Data Architecture Cost-Benefit Reporting 93

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. Most have only data governance operations.

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Data Governance Metadata Digital Transformation Cost-Benefit 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.

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Data Governance IT Risk Data Lake 145

erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. 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.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Octopai

MAY 31, 2022

The ultimate data organizational tool, letting any data user in your organization easily see what data assets you have and all the pertinent details about them, is a data catalog. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

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Management Metadata Business Intelligence ROI 52

Octopai

JANUARY 21, 2020

How much time has your BI team wasted on finding data and creating metadata management reports? BI groups spend more than 50% of their time and effort manually searching for metadata. In fact, BI projects used to take many months to complete and require huge numbers of IT professionals to extract data. Cube to the rescue.

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OLAP Metadata Online Analytical Processing Data Quality 56

Alation

MARCH 14, 2023

All critical data elements (CDEs) should be collated and inventoried with relevant metadata, then classified into relevant categories and curated as we further define below. Store Where individual departments have their own databases for metadata management, data will be siloed, meaning it can’t be shared and used business-wide.

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

erwin

MARCH 8, 2019

A number of best practices and technology solutions were used to establish the data required for managing the registration and classification of data feeds: The underlying metadata is harvested followed by an initial quality check. Then the metadata is classified against a semantic model held in a business glossary.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

Ontotext

JULY 6, 2023

This shift of both a technical and an outcome mindset allows them to establish a centralized metadata hub for their data assets and effortlessly access information from diverse systems that previously had limited interaction. There are four groups of data that are naturally siloed: Structured data (e.g.,

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Cost-Benefit Metadata Experimentation Risk 52

Alation

MAY 19, 2022

Gartner Data & Analytics Summit 2022: Keynote Highlights. A Gartner survey found that 57% of Boards of Directors have increased their risk appetites, and data & analytics are fueling more risky (and potentially rewarding) projects. Leaders agree: Data needs to drive business results. Establish what data you have.

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Metadata Data Analytics Analytics Data Governance 52

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. So, how can you quickly take advantage of the DataOps opportunity while avoiding the risk and costs of DIY?

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. Figure 1 – Data Catalog Metadata Subjects.

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Metadata Data Lake Recreation/Entertainment Big Data 64

Ontotext

APRIL 21, 2021

The problem was the left hand had no way of knowing the systemic issues around data governance, risk management and compliance framework. Manage Regulation, Manage Risk. Through rich metadata and automated reasoning , it is possible to express the complexity of assets and their relationships. Conclusion.

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Metadata Finance Cost-Benefit Risk 59

erwin

APRIL 16, 2021

For a fully mature or “enhanced” data governance program, IT and the business need to take responsibility for selling the benefits of data governance across the enterprise and ensure all stakeholders are properly educated about it. Whatever your motivation, you need to identify it first and foremost to get a grip on data governance.

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