AWS Big Data

JULY 29, 2024

As data volumes grow, the complexity of maintaining operational excellence also increases. Monitoring and tracking issues in the data management lifecycle are essential for achieving operational excellence in data lakes. This is where Apache Iceberg comes into play, offering a new approach to data lake management.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

Ontotext

JUNE 10, 2021

For instance, the analysis of M&A transactions in order to derive investment insights requires the raw transaction data, in addition to the information on relationships of the companies involved in these transactions, e.g. subsidiaries, joint ventures, investors or competitors. open-world vs. closed-world assumptions).

Metadata 119

Metadata Cost-Benefit OLAP Modeling 119

CIO Business Intelligence

FEBRUARY 27, 2025

A high hurdle many enterprises have yet to overcome is accessing mainframe data via the cloud. Mainframes hold an enormous amount of critical and sensitive business data including transactional information, healthcare records, customer data, and inventory metrics.

Metadata 98

Metadata Data Lake Cost-Benefit Forecasting 98

AWS Big Data

JANUARY 15, 2025

Their terminal operations rely heavily on seamless data flows and the management of vast volumes of data. With the addition of these technologies alongside existing systems like terminal operating systems (TOS) and SAP, the number of data producers has grown substantially. This process is shown in the following figure.

IoT 111

IoT Machine Learning Metadata Data-driven 111

O'Reilly on Data

JANUARY 29, 2019

The current generation of AI and ML methods and technologies rely on large amounts of data—specifically, labeled training data. In order to have a longstanding AI and ML practice, companies need to have data infrastructure in place to collect, transform, store, and manage data.

Deep Learning 271

Deep Learning Machine Learning Data Science Metadata 271

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

erwin

FEBRUARY 6, 2020

As organizations deal with managing ever more data, the need to automate data management becomes clear. Last week erwin issued its 2020 State of Data Governance and Automation (DGA) Report. Searching for data was the biggest time-sinking culprit followed by managing, analyzing and preparing data.

Management 144

Management Data Governance Cost-Benefit Metadata 144

Rocket-Powered Data Science

JULY 6, 2021

The key to success is to start enhancing and augmenting content management systems (CMS) with additional features: semantic content and context. This is accomplished through tags, annotations, and metadata (TAM). TAM management, like content management, begins with business strategy. Collect, curate, and catalog (i.e.,

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

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

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

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

David Menninger's Analyst Perspectives

OCTOBER 24, 2024

Data fabric refers to technology products that can be used to integrate, manage and govern data across distributed environments, supporting the cultural and organizational data ownership and access goals of data mesh.

Management 130

Management Data-driven Data Governance Data Lake 130

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

CIO Business Intelligence

APRIL 8, 2025

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

AWS Big Data

OCTOBER 21, 2024

Let’s briefly describe the capabilities of the AWS services we referred above: AWS Glue is a fully managed, serverless, and scalable extract, transform, and load (ETL) service that simplifies the process of discovering, preparing, and loading data for analytics. As stated earlier, the first step involves data ingestion.

Sales 115

Sales Data-driven Data Processing Key Performance Indicator 115

Octopai

JANUARY 31, 2022

If you’re a mystery lover, I’m sure you’ve read that classic tale: Sherlock Holmes and the Case of the Deceptive Data, and you know how a metadata catalog was a key plot element. In The Case of the Deceptive Data, Holmes is approached by B.I. He goes on to explain: Reasons for inaccurate data. Big data is BIG.

Metadata 97

Metadata IT Unstructured Data IoT 97

CIO Business Intelligence

JUNE 9, 2022

A data management platform (DMP) is a group of tools designed to help organizations collect and manage data from a wide array of sources and to create reports that help explain what is happening in those data streams. Deploying a DMP can be a great way for companies to navigate a business world dominated by data.

Management 144

Management Advertising Data Lake Sales 144

AWS Big Data

DECEMBER 17, 2024

We have enhanced data sharing performance with improved metadata handling, resulting in data sharing first query execution that is up to four times faster when the data sharing producers data is being updated. You can also create new data lake tables using Redshift Managed Storage (RMS) as a native storage option.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

Data Virtualization

DECEMBER 8, 2022

Nowadays, we no longer use the term DD/DS, but “data catalog” or simply “metadata system”. The post Metadata, the Neglected Stepchild of IT appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. It was written by L.

Metadata 69

Metadata IT Publishing Data Integration 69

CIO Business Intelligence

JULY 18, 2024

Emerging technologies are transforming organizations of all sizes, but with the seemingly endless possibilities they bring, they also come with new challenges surrounding data management that IT departments must solve. IT teams need to capture metadata to know where their data comes from, allowing them to map out its lineage and flow.

Management 111

Management Internet of Things IoT Metadata 111

AWS Big Data

FEBRUARY 6, 2023

For data lake customers who need to discover petabytes of data, AWS Glue crawlers are a popular way to discover and catalog data in the background. This allows users to search and find relevant data from multiple data sources. MongoDB Atlas is a developer data service from AWS technology partner MongoDB, Inc.

Metadata 98

Metadata Data Lake Machine Learning Big Data 98

O'Reilly on Data

DECEMBER 19, 2018

We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure.

Machine Learning 279

Machine Learning Software Metadata Testing 279

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. After all, you can’t manage or govern what you can’t see, much less use it to make smart decisions. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

AWS Big Data

APRIL 29, 2024

In the realm of big data, securing data on cloud applications is crucial. This post explores the deployment of Apache Ranger for permission management within the Hadoop ecosystem on Amazon EKS. Apache Ranger is a comprehensive framework designed for data governance and security in Hadoop ecosystems.

Management 116

Management Big Data Data Warehouse Metadata 116

O'Reilly on Data

MAY 21, 2019

and managed services in the cloud. Not surprisingly, data integration and ETL were among the top responses, with 60% currently building or evaluating solutions in this area. and Verta.AI) make ML development easier for companies to manage. Metadata and artifacts needed for audits.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

IBM Big Data Hub

AUGUST 24, 2022

The only question is, how do you ensure effective ways of breaking down data silos and bringing data together for self-service access? It starts by modernizing your data integration capabilities – ensuring disparate data sources and cloud environments can come together to deliver data in real time and fuel AI initiatives.

Data Integration 79

Data Integration Metadata Data-driven Data Architecture 79

AWS Big Data

DECEMBER 16, 2024

Third, some services require you to set up and manage compute resources used for federated connectivity, and capabilities like connection testing and data preview arent available in all services. This approach simplifies your data journey and helps you meet your security requirements. Choose Add data.

Visualization 93

Visualization Data Processing Testing Publishing 93

AWS Big Data

DECEMBER 4, 2024

Ask questions in plain English to find the right datasets, automatically generate SQL queries, or create data pipelines without writing code. 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 104

Data Analytics Analytics Data Lake Data Quality 104

Data Virtualization

DECEMBER 20, 2024

The post My Reflections on the Gartner Hype Cycle for Data Management, 2024 appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information. Gartner Hype Cycle methodology provides a view of how.

Management 52

Management Data Integration Technology Data Architecture 52

Data Virtualization

JULY 28, 2023

Reading Time: 2 minutes As the volume, variety, and velocity of data continue to surge, organizations still struggle to gain meaningful insights. This is where active metadata comes in. Listen to “Why is Active Metadata Management Essential?” What is Active Metadata? ” on Spreaker.

Metadata 52

Metadata Data Integration Management Data Science 52

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 79

Management Metadata Data Architecture Data Lake 79

CIO Business Intelligence

FEBRUARY 2, 2024

As data and analytics become the beating heart of the enterprise, it’s increasingly critical for the business to have access to consistent, high-quality data assets. Master data management (MDM) is required to ensure the enterprise’s data is consistent, accurate, and controlled. for 180 days access.

Management 116

Management Data Governance Cost-Benefit Testing 116

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. And close to 50 percent have deployed data catalogs and business glossaries.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

erwin

OCTOBER 8, 2020

So if you’re going to move from your data from on-premise legacy data stores and warehouse systems to the cloud, you should do it right the first time. With all these diverse metadata sources, it is difficult to understand the complicated web they form much less get a simple visual flow of data lineage and impact analysis.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

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. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

AWS Big Data

APRIL 17, 2024

In this post, we discuss how the reimagined data flow works with OR1 instances and how it can provide high indexing throughput and durability using a new physical replication protocol. We also dive deep into some of the challenges we solved to maintain correctness and data integrity.

Optimization 128

Optimization Snapshot Metadata Cost-Benefit 128