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

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 Optimization 40

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

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

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 89

Testing Interactive Metrics Management 89

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

Ontotext

JANUARY 26, 2023

The catalog stores the asset’s metadata in RDF. This allows keeping a well-defined representation of the metadata of each asset and enables using a SPARQL endpoint to query it. Towards that end authors introduce a system for integrity checks for building automation applications and using more reliable data for data analytics processes.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

Ontotext

JULY 13, 2023

For example, offering more of the same product or content instead of complementary items Analytics tools that don’t really support decision making Chatbots that fail the Alan Turing test You name it! Enterprises generate an enormous amount of data and content every minute.

Enterprise 52

Enterprise Metadata Digital Transformation Software 52

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

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? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

IBM Big Data Hub

SEPTEMBER 20, 2022

This is where technology such as IBM FactSheets , can help by reducing the manual labor needed to capture metadata and other facts about a model across stages of the AI lifecycle. Similarly, facts can be collected while the model is in the testing and validation stages.

Metadata 56

Metadata Machine Learning Data-driven Modeling 56

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

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 83

Data Warehouse Cost-Benefit Metadata Data-driven 83

AWS Big Data

AUGUST 15, 2023

Some examples include AWS data analytics services such as AWS Glue for data integration, Amazon QuickSight for business intelligence (BI), as well as third-party software and services from AWS Marketplace. This post demonstrates how to use Athena to run queries on Parquet or CSV files in a GCS bucket.

Recreation/Entertainment 88

Recreation/Entertainment Unstructured Data Business Intelligence Data-driven 88

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

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

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. Those days are long gone if they ever existed.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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 100

Metadata Dashboards Metrics Visualization 100

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 114

Management Data Governance Cost-Benefit Testing 114

AWS Big Data

FEBRUARY 1, 2023

We also used AWS Lambda for data processing. To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. Clients access this data store with an API’s.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

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 Metrics Data-driven 52

Ontotext

MAY 16, 2024

This includes defining the underlying drivers (cost containment, process automation, flexible query, regulatory compliance, governance simplification) and prioritizing use cases (data integration, digitalization, enterprise search, lineage traceability, cybersecurity, access control).

Enterprise 52

Enterprise Data-driven Cost-Benefit Digital Transformation 52

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 106

Metadata Data Quality Data Governance Data Integration 106

AWS Big Data

JUNE 12, 2023

Acting as a bridge between producer and consumer apps, it enforces the schema, reduces the data footprint in transit, and safeguards against malformed data. AWS Glue is an ideal solution for running stream consumer applications, discovering, extracting, transforming, loading, and integrating data from multiple sources.

Management 80

Management Metadata Testing Internet of Things 80

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

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 101

Data Warehouse Data Lake Analytics Machine Learning 101

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 87

Metadata Data Lake Optimization Strategy 87

CIO Business Intelligence

SEPTEMBER 22, 2023

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. Of course, marketing also works.

Management 104

Management Advertising Data Lake Sales 104

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 143

Management Advertising Data Lake Sales 143

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 68

Data Lake Metadata Snapshot Analytics 68

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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 238

Machine Learning Technology Deep Learning Data Science 238

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 125

Metadata Cost-Benefit Enterprise Interactive 125

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 103

Data Lake Management Metrics Data Warehouse 103

O'Reilly on Data

DECEMBER 19, 2018

have a large body of tools to choose from: IDEs, CI/CD tools, automated testing tools, and so on. 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.

Machine Learning 262

Machine Learning Software Metadata Testing 262

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

DataKitchen

JANUARY 23, 2023

DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data testing is an essential aspect of DataOps Observability; it helps to ensure that data is accurate, complete, and consistent with its specifications, documentation, and end-user requirements.

Testing 130

Testing Data Governance Data Quality Data-driven 130