CIO Business Intelligence

SEPTEMBER 6, 2024

As artificial intelligence (AI) and machine learning (ML) continue to reshape industries, robust data management has become essential for organizations of all sizes. Let’s dive into what that looks like, what workarounds some IT teams use today, and why metadata management is the key to success.

Metadata 116

Metadata Enterprise Management Cost-Benefit 116

AWS Big Data

JULY 29, 2024

Data lakes provide a unified repository for organizations to store and use large volumes of data. This enables more informed decision-making and innovative insights through various analytics and machine learning applications.

Metadata 126

Metadata Snapshot Data Lake Metrics 126

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. Data poisoning attacks. Inversion by surrogate models.

Modeling 278

Modeling Machine Learning Predictive Modeling Consulting 278

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

DECEMBER 4, 2024

Our customers are telling us that they are seeing their analytics and AI workloads increasingly converge around a lot of the same data, and this is changing how they are using analytics tools with their data. Having confidence in your data is key. They aren’t using analytics and AI tools in isolation.

Data Analytics 104

Data Analytics Analytics Data Lake Data Quality 104

AWS Big Data

FEBRUARY 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. MongoDB Atlas is a developer data service from AWS technology partner MongoDB, Inc.

Metadata 98

Metadata Data Lake Machine Learning Big Data 98

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. Amazon Athena is used to query, and explore the data.

Sales 115

Sales Data-driven Data Processing Key Performance Indicator 115

AWS Big Data

DECEMBER 17, 2024

Today, Amazon Redshift is used by customers across all industries for a variety of use cases, including data warehouse migration and modernization, near real-time analytics, self-service analytics, data lake analytics, machine learning (ML), and data monetization.

Data Lake 98

Data Lake Data Warehouse Data-driven Optimization 98

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

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

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

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. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity.

Visualization 95

Visualization Data Processing Testing Publishing 95

AWS Big Data

APRIL 3, 2024

Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time. Apache Iceberg offers integrations with popular data processing frameworks such as Apache Spark, Apache Flink, Apache Hive, Presto, and more.

Data Lake 128

Data Lake Snapshot Metadata Data Architecture 128

AWS Big Data

JUNE 7, 2023

This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. For this, Cargotec built an Amazon Simple Storage Service (Amazon S3) data lake and cataloged the data assets in AWS Glue Data Catalog.

Metadata 58

Metadata Data Lake Machine Learning Big Data 58

CIO Business Intelligence

MARCH 24, 2023

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata.

Data Governance 142

Data Governance Management Metadata Data Quality 142

IBM Big Data Hub

MARCH 25, 2022

A data fabric is an architectural approach that enables organizations to simplify data access and data governance across a hybrid multicloud landscape for better 360-degree views of the customer and enhanced MLOps and trustworthy AI. The post What is a data fabric architecture? appeared first on Journey to AI Blog.

Metadata 104

Metadata Data Quality Data Governance Data Integration 104

David Menninger's Analyst Perspectives

MAY 8, 2025

Many longstanding providers of data management products, such as Informatica, have adopted DataOps capabilities and methodologies, adapting product portfolios to cloud-based consumption and automated, collaborative and agile processes. Informatica is still closely associated with data integration.

Data Quality 130

Data Quality Data Governance Data Integration Software 130

AWS Big Data

JUNE 10, 2024

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used. Here is where it can get complicated.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Introducing the next generation of Amazon SageMaker AWS announces the next generation of Amazon SageMaker, a unified platform for data, analytics, and AI. S3 Metadata is designed to automatically capture metadata from objects as they are uploaded into a bucket, and to make that metadata queryable in a read-only table.

Analytics 62

Analytics Data Lake Metadata Data Warehouse 62

erwin

NOVEMBER 6, 2020

The clear benefit is that data stewards spend less time building and populating the data governance framework and more time realizing value and ROI from it. . Industry analysts and other people who write about data governance and automation define it narrowly, with an emphasis on artificial intelligence (AI) and machine learning (ML).

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

AWS Big Data

NOVEMBER 29, 2023

This cloud service was a significant leap from the traditional data warehousing solutions, which were expensive, not elastic, and required significant expertise to tune and operate. Here’s a couple of highlights from this week and for the full list, see below.

Data Warehouse 130

Data Warehouse Analytics Data Lake Machine Learning 130

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 110

Metadata Data Lake Visualization Data Transformation 110

Ontotext

JANUARY 10, 2024

And each of these gains requires data integration across business lines and divisions. 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. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

DataKitchen

SEPTEMBER 21, 2023

These applications are where the rubber meets the road and often where customers first encounter data quality issues. Problems can manifest in various ways, such as Model Prediction Errors in machine learning applications, empty dashboards in BI tools, or row counts in exported data falling short of expectations.

Testing 173

Testing Data Quality Predictive Modeling Metrics 173

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. Further, data management activities don’t end once the AI model has been developed. era is upon us.

Data Governance 145

Data Governance IT Risk Data Lake 145

AWS Big Data

DECEMBER 18, 2023

Customers use Amazon Redshift as a key component of their data architecture to drive use cases from typical dashboarding to self-service analytics, real-time analytics, machine learning (ML), data sharing and monetization, and more.

Data Warehouse 110

Data Warehouse Machine Learning Data-driven Data Lake 110

Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

Metadata 92

Metadata Data Architecture Machine Learning Cost-Benefit 92

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. What’s a data mesh? 11 May 2021. .

Management 79

Management Metadata Data Architecture Data Lake 79

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Data discoverability Unlike structured data, which is managed in well-defined rows and columns, unstructured data is stored as objects.

Data Governance 123

Data Governance Unstructured Data Metadata Data Lake 123

AWS Big Data

JUNE 10, 2024

Organizations have multiple Hive data warehouses across EMR clusters, where the metadata gets generated. To address this challenge, organizations can deploy a data mesh using AWS Lake Formation that connects the multiple EMR clusters. An entity can act both as a producer of data assets and as a consumer of data assets.

Data Lake 117

Data Lake Metadata Data Warehouse Data Processing 117

AWS Big Data

NOVEMBER 22, 2023

Many AWS customers adopted Apache Hudi on their data lakes built on top of Amazon S3 using AWS Glue , a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development.

Data Lake 115

Data Lake Snapshot Metadata Optimization 115

AWS Big Data

SEPTEMBER 11, 2024

AWS Transfer Family seamlessly integrates with other AWS services, automates transfer, and makes sure data is protected with encryption and access controls. Each file arrives as a pair with a tail metadata file in CSV format containing the size and name of the file. 2 GB into the landing zone daily.

Data Architecture 110

Data Architecture Optimization Data Warehouse Metadata 110

AWS Big Data

JUNE 25, 2024

In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights. It provides secure, real-time access to Redshift data without copying, keeping enterprise data in place.

Data Lake 121

Data Lake Cost-Benefit Data-driven Data Warehouse 121

AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

Management 115

Management Big Data Data Warehouse Metadata 115

Ontotext

DECEMBER 1, 2023

So, KGF 2023 proved to be a breath of fresh air for anyone interested in topics like data mesh and data fabric , knowledge graphs, text analysis , large language model (LLM) integrations, retrieval augmented generation (RAG), chatbots, semantic data integration , and ontology building.

Metadata 78

Metadata Sales Machine Learning Consulting 78

Cloudera

JUNE 25, 2019

Cloudera shared a comprehensive overview and demonstration of the all-new Cloudera Data Platform (CDP). Hybrid and multi-cloud – provides choice to manage, analyze and experiment with data in any public cloud and in private data centers for maximum choice and flexibility.

Enterprise 87

Enterprise Machine Learning Recreation/Entertainment IoT 87

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. We keep feeding the monster data.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84