AWS Big Data

JULY 29, 2024

It addresses many of the shortcomings of traditional data lakes by providing features such as ACID transactions, schema evolution, row-level updates and deletes, and time travel. In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

Alation

JULY 19, 2021

What Is Metadata? Metadata is information about data. A clothing catalog or dictionary are both examples of metadata repositories. Indeed, a popular online catalog, like Amazon, offers rich metadata around products to guide shoppers: ratings, reviews, and product details are all examples of metadata.

Metadata 105

Metadata Management Data Governance Machine Learning 105

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

Ontotext

JUNE 10, 2021

Not Every Graph is a Knowledge Graph: Schemas and Semantic Metadata Matter. To be able to automate these operations and maintain sufficient data quality, enterprises have started implementing the so-called data fabrics , that employ diverse metadata sourced from different systems. Such examples are provenance (e.g.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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

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 290

Strategy Experimentation Uncertainty Machine Learning 290

Smart Data Collective

SEPTEMBER 26, 2021

A NoSQl database can use documents for the storage and retrieval of data. The central concept is the idea of a document. Documents encompass and encode data (or information) in a standard format. A document is susceptible to change. The documents can be in PDF format. Speaking of which.

Metadata 130

Metadata Visualization Unstructured Data Data mining 130

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

CIO Business Intelligence

SEPTEMBER 19, 2024

It will do this, it said, with bidirectional integration between its platform and Salesforce’s to seamlessly delivers data governance and end-to-end lineage within Salesforce Data Cloud. Additional to that, we are also allowing the metadata inside of Alation to be read into these agents.”

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

O'Reilly on Data

DECEMBER 19, 2018

Anomaly detection is well-known in the financial industry, where it’s frequently used to detect fraudulent transactions, but it can also be used to catch and fix data quality issues automatically. If you suddenly see unexpected patterns in your social data, that may mean adversaries are attempting to poison your data sources.

Machine Learning 279

Machine Learning Software Metadata Testing 279

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 Cost-Benefit Digital Transformation 145

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.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

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

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 133

Metadata IT Data-driven Data Quality 133

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 124

Data Governance Unstructured Data Metadata Data Lake 124

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

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 131

Informatics Metadata Data mining Digital Transformation 131

erwin

JANUARY 3, 2020

As organizations become data-driven and awash in an overwhelming amount of data from multiple data sources (AI, IoT, ML, etc.), they will find new ways to get a handle on data quality and focus on data management processes and best practices.

Data Governance 139

Data Governance Digital Transformation IoT Metadata 139

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

erwin

OCTOBER 29, 2020

Earlier this year, erwin conducted a research project in partnership with Dataversity, the 2020 State of Data Governance and Automation. We asked participants to “talk to us about data value chain bottlenecks.” Data quality and accuracy are recurring themes as well.

Data Governance 105

Data Governance Metadata Digital Transformation ROI 105

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

erwin

FEBRUARY 6, 2020

How to Automate Data Management. Here are our eight recommendations for how to transition from manual to automated data management: 1) Put Data Quality First: Automating and matching business terms with data assets and documenting lineage down to the column level are critical to good decision making.

Management 144

Management Data Governance Cost-Benefit Metadata 144

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

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 89

Metadata Risk Management Business Intelligence Data Governance 89

erwin

JULY 17, 2019

Your organization won’t be able to take complete advantage of analytics tools to become data-driven unless you establish a foundation for agile and complete data management. You need automated data mapping and cataloging through the integration lifecycle process, inclusive of data at rest and data in motion.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored.

Modeling 98

Modeling Metadata Data Governance Visualization 98

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 111

Data Architecture Optimization Data Warehouse Metadata 111

CIO Business Intelligence

JUNE 12, 2024

Most enterprise data is unstructured and semi-structured documents and code, as well as images and video. For example, gen AI can be used to extract metadata from documents, create indexes of information and knowledge graphs, and to query, summarize, and analyze this data.

Modeling 140

Modeling Testing Cost-Benefit Metadata 140

erwin

FEBRUARY 4, 2021

It uncovered a number of obstacles that organizations have to overcome to improve their data operations. 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

erwin

MARCH 21, 2019

Organizations also can use a BPM tool to identify the staff who function as “unofficial data repositories.” Organizations can document employee processes to ensure vital information isn’t lost should an employee choose to leave. The lack of a central metadata repository is a far too common thorn in an organization’s side.

Modeling 75

Modeling Metadata Data Governance IT 75

Alation

OCTOBER 18, 2022

In the modern data stack, dbt is a key tool to make data ready for analysis. Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Conclusion.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

Ontotext

NOVEMBER 23, 2023

This technique can be especially useful in data integration projects where you are combining related, potentially overlapping data from multiple sources. Remember to set up your shapes graph in a repository that has been configured from the beginning to support SHACL, as described in our documentation.

Data Quality 69

Data Quality Reporting Metadata IT 69

erwin

MARCH 14, 2019

(BFSI, PHARMA, INSURANCE AND NON-PROFIT) CASE STUDIES FOR AUTOMATED METADATA-DRIVEN AUTOMATION. As well as introducing greater efficiency to the data governance process, automated data mapping tools enable data to be auto-documented from XML that builds mappings for the target repository or reporting structure.

Metadata 81

Metadata Data Governance Data-driven Digital Transformation 81

Ontotext

NOVEMBER 9, 2023

While everyone may subscribe to the same design decisions and agree on an ontology, there may be differences in the data quality. In such situations, data must be validated. Instead, they provide metadata about the shapes. Sometimes there is no room for error. So stay tuned! Ontotext’s GraphDB Give it a try today!

Data Quality 64

Data Quality Testing Reporting Metadata 64

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. DataBrew is an excellent tool for data quality and preprocessing. For Matching conditions , choose Match all conditions.

Metadata 114

Metadata Sales Data Lake Big Data 114

Ontotext

JANUARY 10, 2024

Limiting growth by (data integration) complexity Most operational IT systems in an enterprise have been developed to serve a single business function and they use the simplest possible model for this. In both cases, semantic metadata is the glue that turns knowledge graphs into hubs of data, metadata, and content.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72