AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

Data Governance 93

Data Governance Unstructured Data Metadata Data Lake 93

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

Ontotext

MAY 26, 2021

In natural language processing (NLP) and computational linguistics the Gold Standard typically represents a corpus of text or a set of documents, annotated or tagged with the desired results for the analysis – be it designation of the corresponding part of speech, syntactic parsing, concept or relationship.

Data Quality 87

Data Quality Machine Learning Measurement Metadata 87

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.

Metadata 111

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.

IT 52

IT Data Quality Metadata Data Governance 52

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. This calls for additional planning, documentation, and testing.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

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 125

Metadata IT Data-driven Data Quality 125

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

Rocket-Powered Data Science

FEBRUARY 15, 2023

Since ChatGPT is built from large language models that are trained against massive data sets (mostly business documents, internal text repositories, and similar resources) within your organization, consequently attention must be given to the stability, accessibility, and reliability of those resources.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

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. Top Five: Benefits of An Automation Framework for Data Governance.

Data Governance 145

Data Governance Metadata Digital Transformation Cost-Benefit 145

erwin

SEPTEMBER 17, 2020

For example, automatically importing mappings from developers’ Excel sheets, flat files, Access and ETL tools into a comprehensive mappings inventory, complete with auto generated and meaningful documentation of the mappings, is a powerful way to support overall data governance. Data quality is crucial to every organization.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

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

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

erwin

JULY 12, 2019

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

FEBRUARY 7, 2023

The product collected an impressive amount of metadata, from the user interface to the database structure. It then translated all that metadata into an image resembling a spider’s web. That was my earliest taste of data lineage. They sought documentation to help them locate the source of the data from the warehouse.

Metadata 52

Metadata Data Warehouse Visualization Data Quality 52

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

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. The first step would be to make sure that the data used at the beginning of the model development process is thoroughly vetted, so that it is appropriate for the use case at hand.

Risk 64

Risk Modeling Machine Learning Data Quality 64

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

FEBRUARY 3, 2022

These target commitments,expressed as policies and standards, should define completeness, quality, accuracy, timeliness, usage, access, and classifications for both metadata and data. These documents were, for the most part, overlooked, which is why traditional governance failed. Monitor and Measure Curation.

Data Governance 98

Data Governance Measurement Metadata Testing 98

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

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.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

erwin

JANUARY 17, 2019

The tools and processes for this should automatically generate “pre-ETL” source-to-target mapping to minimize human errors that can occur while manually compiling and interpreting a multitude of Excel-based data mappings that exist across the organization. Data Governance and the System Development Lifecycle. Governing metadata.

Metadata 63

Metadata Data Governance Data Quality Data-driven 63

AWS Big Data

NOVEMBER 6, 2023

The following graph describes a simple data quality check pipeline using setup and teardown tasks. To learn more about Setup and Teardown tasks, refer to the Apache Airflow documentation. For a complete list of installed packages and their versions, refer to this MWAA documentation.

Metrics 100

Metrics Metadata Snapshot Management 100

Alation

MAY 17, 2022

Those algorithms draw on metadata, or data about the data, that the catalog scrapes from source systems, along with behavioral metadata, which the catalog gathers based on human data usage. Beyond sampling, analysts must take care to validate data in other ways.

Metadata 52

Metadata Data Quality Machine Learning Reporting 52

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

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 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

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 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 69

Analytics Data Warehouse Data Lake Metadata 69

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

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

Alation

MARCH 11, 2022

A data catalog with a Behavioral Analysis Engine will measure human behavior around data to locate your most valuable and actionable data. This data about data, AKA metadata , is an essential layer of your new meshy fabric.

Metadata 52

Metadata Data Governance ROI Data Quality 52

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. That’s where the bulk of my time was spent.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

Alation

OCTOBER 5, 2021

It’s on Data Governance Leaders to identify the issues with the business process that causes users to act in these ways. Inconsistencies in expectations can create enormous negative issues regarding data quality and governance. Data governance and AI. Picking the Right Data Governance Tools.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

erwin

APRIL 15, 2020

Establish data-sharing training programs so all data stakeholders understand associated security considerations, contextual meaning, and when and when not to share and/or ingest third-party data. erwin Data Intelligence for Data Governance and Distancing.

Data Governance 134

Data Governance Metadata Testing Reporting 134

Alation

JUNE 2, 2022

Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches. These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. However, governance processes are equally important. Conclusion.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Andrew White

JULY 5, 2023

And guess what – there are other names that we have collectively invented over the years that tend to mean the same thing: Glossary Business metadata, and Master data. Those are the things business business folks would care about, since they use that data every day. They WOULD have some opportunity to govern the glossary!

Metrics 52

Metrics Metadata Modeling Data Quality 52

Ontotext

MARCH 18, 2020

To access this knowledge, enterprises need tools to help them integrate the data scattered across the organization. The third challenge is how to combine data management with analytics. In today’s business climate, data quality and governance are no longer enough.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59