erwin

NOVEMBER 6, 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. And this time, you guessed it – we’re focusing on data automation and how it could impact metadata management and data governance.

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

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

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 are these rampant and often uncontrolled projects to collect metadata properly motivated? What Is Metadata?

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). So, there must be a strategy regarding who, what, when, where, why, and how is the organization’s content to be indexed, stored, accessed, delivered, used, and documented. Smart content includes labeled (tagged, annotated) metadata (TAM).

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

Ontotext

NOVEMBER 11, 2024

Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. This often leaves business insights and opportunities lost among a tangled complexity of meaningless, siloed data and content.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52

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 120

Optimization Snapshot Metadata Cost-Benefit 120

CIO Business Intelligence

MARCH 24, 2023

It must be clear to all participants and auditors how and when data-related decisions and controls were introduced into the processes. Data-related decisions, processes, and controls subject to data governance must be auditable. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

JULY 10, 2024

With data privacy and security becoming an increased concern, Sovereign cloud is turning from an optional, like-to-have, to an essential requirement, especially for highly protected markets like Government, Healthcare, Financial Services, Legal, etc. This local presence is crucial for maintaining data integrity and security.

Metadata 98

Metadata Data-driven Marketing Measurement 98

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 106

Metadata Dashboards Metrics Visualization 106

Ontotext

JULY 12, 2024

We offer two different PowerPacks – Agile Data Integration and High-Performance Tagging. The High-Performance Tagging PowerPack bundle The High-Performance Tagging PowerPack is designed to satisfy taxonomy and metadata management needs by allowing enterprise tagging at a scale.

Enterprise 59

Enterprise Cost-Benefit Metadata Data Integration 59

Ontotext

JULY 11, 2019

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

Statistics 40

Statistics Modeling Metadata Enterprise 40

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 governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 102

Data Governance Unstructured Data Metadata Data Lake 102

erwin

OCTOBER 8, 2020

But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. 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

erwin

MAY 27, 2020

What, then, should users look for in a data modeling product to support their governance/intelligence requirements in the data-driven enterprise? Nine Steps to Data Modeling. Provide metadata and schema visualization regardless of where data is stored. naming and database standards, formatting options, and so on.

Modeling 98

Modeling Metadata Data Governance Visualization 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

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

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. What Does a Data Catalog Consist Of?

Metadata 130

Metadata IT Data-driven Data Quality 130

CIO Business Intelligence

MARCH 6, 2024

“SAP is executing on a roadmap that brings an important semantic layer to enterprise data, and creates the critical foundation for implementing AI-based use cases,” said analyst Robert Parker, SVP of industry, software, and services research at IDC. We are also seeing customers bringing in other data assets from other apps or data sources.

Unstructured Data 129

Unstructured Data Dashboards Business Intelligence Data Governance 129

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

erwin

MAY 13, 2020

The role of data modeling (DM) has expanded to support enterprise data management, including data governance and intelligence efforts. Metadata management is the key to managing and governing your data and drawing intelligence from it. Types of Data Models: Conceptual, Logical and Physical.

Data Governance 93

Data Governance Enterprise Modeling Management 93

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Who are the data owners? Data lineage offers proof that the data provided is reflected accurately.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

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 89

Data Architecture Optimization Data Warehouse Metadata 89

AWS Big Data

MAY 21, 2024

Following the best practices section of the OpenSearch Service Developer Guide, AVB selected an optimal cluster configuration with three dedicated cluster manager nodes and six data nodes, across three Availability Zones , while keeping shard size between 10–30 GiB.

Manufacturing 102

Manufacturing Sales Optimization Data Processing 102

erwin

JANUARY 17, 2020

Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise. What is Data Modeling?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

erwin

FEBRUARY 4, 2021

It uncovered a number of obstacles that organizations have to overcome to improve their data operations. 1 bottleneck, according to 62 percent of respondents, was documenting complete data lineage. Automate code generation : Alleviate the need for developers to hand code connections from data sources to target schema.

Data Governance 89

Data Governance Metadata Data Quality IoT 89

erwin

FEBRUARY 6, 2020

Here are our eight recommendations for how to transition from manual to automated data management: 1) Put Data Quality First: Automating and matching business terms with data assets and documenting lineage down to the column level are critical to good decision making.

Management 144

Management Data Governance Cost-Benefit Metadata 144

Ontotext

JULY 29, 2021

KGs bring the Semantic Web paradigm to the enterprises, by introducing semantic metadata to drive data management and content management to new levels of efficiency and breaking silos to let them synergize with various forms of knowledge management. Take this restaurant, for example. Enterprise Knowledge Graphs and the Semantic Web.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) This allows for a high degree of transparency and auditability.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

erwin

JANUARY 17, 2019

It assists in successfully meeting increasingly strict compliance requirements, such as those in the General Data Protection Regulation (GDPR). A mature and sustainable data governance initiative must include data integration. Data Governance and the System Development Lifecycle. Governing metadata.

Metadata 63

Metadata Data Governance Data Quality Data-driven 63

Octopai

JUNE 9, 2024

Accurate data lineage rebuilt trust among decision-makers. HealthCo’s leadership could confidently rely on data-driven insights, knowing the data’s journey was well-documented and reliable. This trust empowered them to deploy new data products without fear of inaccuracies, driving innovation and operational improvements.

IT 52

IT Data-driven Predictive Analytics Metadata 52

Octopai

JUNE 1, 2020

Data mapping is the cornerstone of many important business intelligence processes: Data Integration – Even if systems are compatible, combining two disparate data repositories still requires meticulous data mapping. Manual Metadata Management Hinders Compliance. This becomes even riskier as the stakes rise.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

Ontotext

JANUARY 6, 2021

That means removing errors, filling in missing information and harmonizing the various data sources so that there is consistency. Once that is done, data can be transformed and enriched with metadata to facilitate analysis. Knowledge graphs help with data analysis in a number of ways.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

Ontotext

AUGUST 5, 2020

Each of the four FAIR principles calls for data and metadata to be easily found, accessed, understood, exchanged and reused. FAIR data is data that is: Findable is such data in which data and metadata are assigned a globally unique and persistent identifier so that computers can easily find it.

Metadata 52

Metadata Insurance Manufacturing Data Integration 52

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. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

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.

Publishing 52

Publishing Metadata Optimization Testing 52

O'Reilly on Data

MARCH 20, 2019

Data integrity constraints: Many databases don’t allow for strange or unrealistic combinations of input variables and this could potentially thwart watermarking attacks. Applying data integrity constraints on live, incoming data streams could have the same benefits. Disparate impact analysis: see section 1.

Modeling 226

Modeling Machine Learning Predictive Modeling Consulting 226

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. Consideration of both data & metadata in the migration.

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80