AWS Big Data

APRIL 8, 2025

Concurrent UPDATE/DELETE on overlapping partitions When multiple processes attempt to modify the same partition simultaneously, data conflicts can arise. For example, imagine a data quality process updating customer records with corrected addresses while another process is deleting outdated customer records.

Snapshot 116

Snapshot Management Metadata Big Data 116

Rocket-Powered Data Science

MARCH 20, 2023

This is where we dispel an old “big data” notion (heard a decade ago) that was expressed like this: “we need our data to run at the speed of business.” Instead, what we really need is for our business to run at the speed of data. Datasphere is not just for data managers.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

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? Analyze metadata.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

erwin

FEBRUARY 13, 2020

When an organization’s data governance and metadata management programs work in harmony, then everything is easier. Data governance is a complex but critical practice. There’s always more data to handle, much of it unstructured; more data sources, like IoT, more points of integration, and more regulatory compliance requirements.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

Octopai

OCTOBER 18, 2021

First, what active metadata management isn’t : “Okay, you metadata! Now, what active metadata management is (well, kind of): “Okay, you metadata! Data assets are tools. Metadata are the details on those tools: what they are, what to use them for, what to use them with. . Quit lounging around!

Metadata 98

Metadata Management IT Data Quality 98

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

Ontotext

JUNE 10, 2021

With graph databases the representation of relationships as data make it possible to better represent data in real time, addressing newly discovered types of data and relationships. This is a graph of millions of edges and vertices – in enterprise data management terms it is a giant piece of master/reference data.

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

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. They don’t know exactly what data they have or even where some of it is. Metadata Is the Heart of Data Intelligence.

Metadata 104

Metadata Management Data-driven Data Architecture 104

AWS Big Data

JULY 29, 2024

In the era of big data, data lakes have emerged as a cornerstone for storing vast amounts of raw data in its native format. They support structured, semi-structured, and unstructured data, offering a flexible and scalable environment for data ingestion from multiple sources.

Metadata 118

Metadata Snapshot Data Lake Metrics 118

AWS Big Data

AUGUST 15, 2024

Data quality is crucial in data pipelines because it directly impacts the validity of the business insights derived from the data. Today, many organizations use AWS Glue Data Quality to define and enforce data quality rules on their data at rest and in transit.

Data Quality 106

Data Quality Visualization Metadata Key Performance Indicator 106

Octopai

DECEMBER 12, 2021

A data asset is only an asset if you can use it to help your organization. What enables you to use all those gigabytes and terabytes of data you’ve collected? Metadata is the pertinent, practical details about data assets: what they are, what to use them for, what to use them with. Where does metadata come from?

Metadata 98

Metadata Management Data Quality Data Governance 98

AWS Big Data

DECEMBER 4, 2024

In today’s rapidly evolving financial landscape, data is the bedrock of innovation, enhancing customer and employee experiences and securing a competitive edge. Like many large financial institutions, ANZ Institutional Division operated with siloed data practices and centralized data management teams.

Metadata 93

Metadata Data Governance Data Quality Data-driven 93

AWS Big Data

APRIL 3, 2024

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Additionally, Amazon DataZone now offers APIs for importing data quality scores from external systems.

Data Quality 103

Data Quality Visualization Metadata Metrics 103

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.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

erwin

MARCH 30, 2020

Shirley Ann Jackson, president of RPI, states that “because this is a global pandemic, there is a huge amount of epidemiological data that has to be folded in to understand the disease globally, to be able to understand populations and how it can effect populations differently.”. Answering these questions is at the heart of data intelligence.

Metadata 122

Metadata IT Data Governance Data Quality 122

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 26, 2020

In order to figure out why the numbers in the two reports didn’t match, Steve needed to understand everything about the data that made up those reports – when the report was created, who created it, any changes made to it, which system it was created in, etc. Enterprise data governance. Metadata in data governance.

Metadata 98

Metadata Data Governance Enterprise Reporting 98

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. Remember that dark data is the data you have but don’t understand. So how do you find your dark data? Analyze your metadata.

IT 135

IT Metadata Data-driven Data Governance 135

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. A data discovery tool moves beyond simple searches.

Metadata 133

Metadata IT Data-driven Data Quality 133

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 347

Enterprise Deep Learning Data Governance Risk 347

Smarten

NOVEMBER 26, 2024

But too much data can also create issues. If the data is not easily gathered, managed and analyzed, it can overwhelm and complicate decision-makers. By some estimates, bad data costs global organizations more than five trillion USD annually. Tools that support data insight include numerous data quality management techniques.

Machine Learning 64

Machine Learning Data Quality Predictive Modeling Metadata 64

AWS Big Data

DECEMBER 4, 2024

They’re taking data they’ve historically used for analytics or business reporting and putting it to work in machine learning (ML) models and AI-powered applications. Data teams struggle to find a unified approach that enables effortless discovery, understanding, and assurance of data quality and security across various sources.

Data Analytics 85

Data Analytics Analytics Data Lake Data Quality 85

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. Recently, EUROGATE has developed a digital twin for its container terminal Hamburg (CTH), generating millions of data points every second from Internet of Things (IoT)devices attached to its container handling equipment (CHE).

IoT 100

IoT Machine Learning Metadata Data-driven 100

AWS Big Data

DECEMBER 4, 2024

These formats, exemplified by Apache Iceberg, Apache Hudi, and Delta Lake, addresses persistent challenges in traditional data lake structures by offering an advanced combination of flexibility, performance, and governance capabilities. These are useful for flexible data lifecycle management. Apache Iceberg highlights AWS Glue 5.0

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

AWS Big Data

OCTOBER 9, 2024

Data parity can help build confidence and trust with business users on the quality of migrated data. Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases.

Data Quality 95

Data Quality Data Lake Data Warehouse Metrics 95

O'Reilly on Data

DECEMBER 19, 2018

are only starting to exist; one big task over the next two years is developing the IDEs for machine learning, plus other tools for data management, pipeline management, data cleaning, data provenance, and data lineage. GitHub is an excellent tool for managing code, but we need to think about [code+data].

Machine Learning 279

Machine Learning Software Metadata Testing 279

TDAN

AUGUST 31, 2021

Data is everywhere! But can you find the data you need? What can be done to ensure the quality of the data? How can you show the value of investing in data? Can you trust it when you get it? These are not new questions, but many people still do not know how to practically […].

Data Quality 105

Data Quality IT Metadata Data Governance 105

Octopai

MARCH 23, 2022

While Sinclair’s famous 1906 novel was intended to expose the plight of employees with horrific working conditions, the American public heard and reacted to a message about food safety and quality. Dirty Meat… and Dirty Data. What caused the atrocious quality issues in the meatpacking industry pre-1906? Cleaning Up Dirty Data.

Data Quality 98

Data Quality Reporting Modeling Interactive 98

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Data Centricity. There is evidence to suggest that there is a blind spot when it comes to data in the AI context.

Data Governance 145

Data Governance IT Data Lake Risk 145

Rocket-Powered Data Science

FEBRUARY 15, 2023

Know thy data: understand what it is (formats, types, sampling, who, what, when, where, why), encourage the use of data across the enterprise, and enrich your datasets with searchable (semantic and content-based) metadata (labels, annotations, tags). Think strategically, but act tactically: think big, start small, learn fast.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

erwin

DECEMBER 9, 2024

When it comes to using AI and machine learning across your organization, there are many good reasons to provide your data and analytics community with an intelligent data foundation. For instance, Large Language Models (LLMs) are known to ultimately perform better when data is structured.

Metadata 52

Metadata Data Quality Sales Modeling 52

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. By 2025, it’s estimated we’ll have 463 million terabytes of data created every day,” says Lisa Thee, data for good sector lead at Launch Consulting Group in Seattle.

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

CIO Business Intelligence

SEPTEMBER 19, 2024

Data intelligence platform vendor Alation has partnered with Salesforce to deliver trusted, governed data across the enterprise. 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.

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

IBM Big Data Hub

NOVEMBER 28, 2022

Metadata management performs a critical role within the modern data management stack. It helps blur data silos, and empowers data and analytics teams to better understand the context and quality of data. This, in turn, builds trust in data and the decision-making to follow. Improve data discovery.

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

O'Reilly on Data

JUNE 19, 2019

Versioning (of models, feature vectors , data) and the ability to roll out, roll back, or have multiple live versions. Metadata and artifacts needed for a full audit trail. A dashboard that provides custom views for all principals (operations, ML engineers, data scientists, business owners).

Modeling 257

Modeling Machine Learning Testing Metrics 257

CIO Business Intelligence

MARCH 24, 2023

Data governance definition Data governance is a system for defining who within an organization has authority and control over data assets and how those data assets may be used. It encompasses the people, processes, and technologies required to manage and protect data assets.

Data Governance 142

Data Governance Management Metadata Data Quality 142