O'Reilly on Data

MAY 21, 2019

Not surprisingly, data integration and ETL were among the top responses, with 60% currently building or evaluating solutions in this area. In an age of data-hungry algorithms, everything really begins with collecting and aggregating data. Metadata and artifacts needed for audits. and managed services in the cloud.

Machine Learning 279

Machine Learning Technology Deep Learning Data Science 279

DataKitchen

SEPTEMBER 21, 2023

In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets. Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

DataKitchen

AUGUST 16, 2024

Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata. This capability includes monitoring, logging, and business-rule detection.

Marketing 124

Marketing Data Quality Testing Metadata 124

erwin

DECEMBER 9, 2024

And if it isnt changing, its likely not being used within our organizations, so why would we use stagnant data to facilitate our use of AI? The key is understanding not IF, but HOW, our data fluctuates, and data observability can help us do just that.

Metadata 52

Metadata Data Quality Sales Modeling 52

DataKitchen

OCTOBER 20, 2023

Example 2: The Data Engineering Team Has Many Small, Valuable Files Where They Need Individual Source File Tracking In a typical data processing workflow, tracking individual files as they progress through various stages—from file delivery to data ingestion—is crucial.

Insurance 169

Insurance Metadata Data-driven Data Quality 169

Wayne Yaddow

FEBRUARY 18, 2025

Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis. However, these two processes are essentially distinct, and their testing needs differ in manyways.

Testing 52

Testing Data Transformation Data-driven Data Quality 52

AWS Big Data

DECEMBER 16, 2024

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. This approach simplifies your data journey and helps you meet your security requirements.

Visualization 71

Visualization Data Processing Testing Publishing 71

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.

Data Lake 81

Data Lake Data Warehouse Data-driven Optimization 81

AWS Big Data

JUNE 10, 2024

Many of the tests to check performance and volumes of data scanned have used Athena because it provides a simple to use, fully serverless, cost effective, interface without the need to setup infrastructure. When evolving such a partition definition, the data in the table prior to the change is unaffected, as is its metadata.

Data Lake 121

Data Lake Metadata Snapshot Analytics 121

Wayne Yaddow

MARCH 5, 2025

In this post, well see the fundamental procedures, tools, and techniques that data engineers, data scientists, and QA/testing teams use to ensure high-quality data as soon as its deployed. First, we look at how unit and integration tests uncover transformation errors at an early stage. PyTest, JUnit,NUnit).

Testing 52

Testing Data Transformation Statistics Metadata 52

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

AWS Big Data

OCTOBER 3, 2023

In-place data upgrade In an in-place data migration strategy, existing datasets are upgraded to Apache Iceberg format without first reprocessing or restating existing data. In this method, the metadata are recreated in an isolated environment and colocated with the existing data files. This can save time.

Data Lake 116

Data Lake Metadata Snapshot Recreation/Entertainment 116

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

AWS Big Data

SEPTEMBER 7, 2023

We will partition and format the server access logs with Amazon Web Services (AWS) Glue , a serverless data integration service, to generate a catalog for access logs and create dashboards for insights. Both the user data and logs buckets must be in the same AWS Region and owned by the same account.

Metadata 111

Metadata Dashboards Metrics Visualization 111

AWS Big Data

FEBRUARY 26, 2025

S3 Tables integration with the AWS Glue Data Catalog is in preview, allowing you to stream, query, and visualize dataincluding Amazon S3 Metadata tablesusing AWS analytics services such as Amazon Data Firehose , Amazon Athena , Amazon Redshift, Amazon EMR, and Amazon QuickSight. With AWS Glue 5.0, With AWS Glue 5.0,

Analytics 59

Analytics Data Lake Metadata Data Warehouse 59

erwin

NOVEMBER 6, 2020

To better explain our vision for automating data governance, let’s look at some of the different aspects of how the erwin Data Intelligence Suite (erwin DI) incorporates automation. Data Cataloging: Catalog and sync metadata with data management and governance artifacts according to business requirements in real time.

Data Governance 97

Data Governance Metadata Data-driven Visualization 97

erwin

JANUARY 24, 2019

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. With an automation framework, data professionals can meet these needs at a fraction of the cost of the traditional manual way. Governing metadata.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

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 101

Metadata Data Lake Visualization Data Quality 101

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Data and Metadata: Data inputs and data outputs produced based on the application logic.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

CIO Business Intelligence

OCTOBER 26, 2023

To earn your CBIP certification, you’ll need two or more years of full-time experience in CIS, data modeling, data planning, data definitions, metadata systems development, enterprise resource planning, systems analysis, application development, and programming or IT management.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

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. Test access using Athena queries in the consumer account.

Data Lake 96

Data Lake Metadata Data Warehouse Data Processing 96

CIO Business Intelligence

FEBRUARY 2, 2024

The Art of Service recommends candidates spend a minimum of 18 hours on the course to pass the certification test. It consists of three separate, 90-minute exams: the Information Systems (IS) Core exam, the Data Management Core exam, and the Specialty exam. How to prepare: The fee includes an online training program and PDF textbook.

Management 116

Management Data Governance Cost-Benefit Testing 116

Ontotext

NOVEMBER 4, 2021

As we’ve said again and again, we believe that knowledge graphs are the next generation tool for helping businesses make critical decisions, based on harmonized knowledge models and data derived from siloed source systems. But these tasks are only part of the story. standard to fully support all significant graph path search use cases.

Metadata 98

Metadata Visualization Modeling Enterprise 98

Ontotext

JUNE 27, 2019

Ontotext’s GraphDB is an enterprise-ready semantic graph database (also called RDF triplestore as it stores data in RDF triples). It provides the core infrastructure for solutions where modeling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical.

Metadata 40

Metadata Management Enterprise Publishing 40

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. Knowledge Graphs are the Warp and Weft of a Data Fabric.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

AWS Big Data

JUNE 25, 2024

It provides secure, real-time access to Redshift data without copying, keeping enterprise data in place. This eliminates replication overhead and ensures access to current information, enhancing data integration while maintaining data integrity and efficiency.

Data Lake 111

Data Lake Cost-Benefit Data-driven Data Warehouse 111

CIO Business Intelligence

JUNE 9, 2022

Its Integrated Process Designer is a visual tool to create data flows that integrate data to produce concise reports. Along the way, metadata is collected, organized, and maintained to help debug and ensure data integrity. Agencies and ad buyers for large clients turn to Simpli.fi Survey CTO.

Management 144

Management Advertising Data Lake Sales 144

Cloudera

JUNE 6, 2019

While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Now the admins need to synchronize multiple copies of the data and metadata and ensure that users across the many clusters are not viewing stale information.

Metadata 86

Metadata Data Lake Optimization Strategy 86

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 96

Data Architecture Optimization Data Warehouse Metadata 96

Smarten

JANUARY 30, 2024

Business users cannot even hope to prepare data for analytics – at least not without the right tools. Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation?

Analytics 69

Analytics Visualization Data Quality Metadata 69

AWS Big Data

MAY 16, 2024

With the new REST API, you can now invoke DAG runs, manage datasets, or get the status of Airflow’s metadata database, trigger, and scheduler—all without relying on the Airflow web UI or CLI. Trigger auto scaling programmatically After you configure auto scaling, you might want to test how it behaves under simulated conditions.

Testing 103

Testing Metrics Interactive Management 103

AWS Big Data

NOVEMBER 29, 2023

Amazon Redshift Serverless, generally available since 2021, allows you to run and scale analytics without having to provision and manage the data warehouse. Amazon Redshift ML large language model (LLM) integration Amazon Redshift ML enables customers to create, train, and deploy machine learning models using familiar SQL commands.

Data Warehouse 112

Data Warehouse Analytics Data Lake Machine Learning 112

Wayne Yaddow

MARCH 14, 2025

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

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. Smart DwH Mover helps in accelerating data warehouse migration.

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

Alation

JANUARY 25, 2022

As a reminder, here’s Gartner’s definition of data fabric: “A design concept that serves as an integrated layer (fabric) of data and connecting processes. In this blog, we will focus on the “integrated layer” part of this definition by examining each of the key layers of a comprehensive data fabric in more detail.

Metadata 52

Metadata IT Data-driven Metrics 52

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. 05:34:22 Connection test: [OK connection ok] 05:34:22 All checks passed!

Data Lake 116

Data Lake Management Metrics Data Warehouse 116

Ontotext

FEBRUARY 23, 2023

The engines must facilitate the advanced data integration and metadata data management scenarios where an EKG is used for data fabrics or otherwise serves as a data hub between diverse data and content management systems. GraphDB was audited to perform 12 operations/second on an AWS r6id.8xlarge

Publishing 52

Publishing Metadata Optimization Testing 52