AWS Big Data

DECEMBER 4, 2024

With this launch, you can query data regardless of where it is stored with support for a wide range of use cases, including analytics, ad-hoc querying, data science, machine learning, and generative AI. We’ve simplified data architectures, saving you time and costs on unnecessary data movement, data duplication, and custom solutions.

Data Analytics 86

Data Analytics Analytics Data Lake Data Quality 86

AWS Big Data

SEPTEMBER 11, 2024

This complex process involves suppliers, logistics, quality control, and delivery. This post describes how HPE Aruba automated their Supply Chain management pipeline, and re-architected and deployed their data solution by adopting a modern data architecture on AWS.

Data Architecture 97

Data Architecture Optimization Data Warehouse Metadata 97

AWS Big Data

JANUARY 15, 2025

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

IoT 101

IoT Machine Learning Metadata Data-driven 101

Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

Cloudera

AUGUST 30, 2022

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Modern data architectures. Deploying modern data architectures. Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

AWS Big Data

OCTOBER 9, 2024

Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases. This takes away important person hours from the actual migration effort into building and maintaining a data parity framework.

Data Quality 96

Data Quality Data Lake Data Warehouse Metrics 96

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

Data Governance 142

Data Governance Management Metadata Data Quality 142

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. Data quality Data quality is essentially the measure of data integrity.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance. Five Steps to GDPR/CCPA Compliance.

Data Governance 110

Data Governance Management Metadata Risk Management 110

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 52

Metadata Data Governance Digital Transformation Data Quality 52

Octopai

APRIL 19, 2021

Aptly named, metadata management is the process in which BI and Analytics teams manage metadata, which is the data that describes other data. In other words, data is the context and metadata is the content. Without metadata, BI teams are unable to understand the data’s full story.

Metadata 59

Metadata Management Business Intelligence Data Governance 59

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. Monitoring Job Metadata. Adding Tests to Reduce Stress.

Testing 152

Testing Metadata Dashboards Statistics 152

erwin

DECEMBER 6, 2019

As a foundational component of enterprise data management, DG would reside in such a group. Enterprise Data Management Methodology : DG is foundational to enterprise data management. metadata management, enterprise data architecture, data quality management), DG will be a struggle.

Data Governance 145

Data Governance Metadata Enterprise Data-driven 145

AWS Big Data

DECEMBER 4, 2024

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures.

Data Integration 98

Data Integration Data Lake Statistics Data-driven 98

erwin

SEPTEMBER 17, 2020

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry. Automating data capture frees up resources to focus on more strategic and useful tasks.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

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

IBM Big Data Hub

APRIL 10, 2023

A well-designed data architecture should support business intelligence and analysis, automation, and AI—all of which can help organizations to quickly seize market opportunities, build customer value, drive major efficiencies, and respond to risks such as supply chain disruptions.

Strategy 85

Strategy Data Architecture Cost-Benefit Reporting 85

Cloudera

JULY 20, 2021

Invest in maturing and improving your enterprise business metrics and metadata repositories, a multitiered data architecture, continuously improving data quality, and managing data acquisitions. Then back this up by embedding compliance and security protocols throughout the insights generation cycle.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

Alation

MAY 31, 2023

This means that specialized roles such as data architects, which focus on modernizing data architecture to help meet business goals, are increasingly important to support data governance. What is a data architect? Their broad range of responsibilities include: Design and implement data architecture.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

AWS Big Data

DECEMBER 19, 2024

Data has become an invaluable asset for businesses, offering critical insights to drive strategic decision-making and operational optimization. The business end-users were given a tool to discover data assets produced within the mesh and seamlessly self-serve on their data sharing needs.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

erwin

APRIL 16, 2024

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 94

Data Lake Analytics Snapshot Data Quality 94

AWS Big Data

JULY 25, 2024

Amazon DataZone provides rich functionality to help a data platform team distribute ownership of tasks so that these teams can choose to operate less like gatekeepers. In Amazon DataZone, data owners can publish their data and its business catalog (metadata) to ATPCO’s DataZone domain. Choose Next.

Data Lake 106

Data Lake Metadata Sales Publishing 106

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

Reporting 115

Reporting Data Quality Strategy Data-driven 115

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

Ontotext

JANUARY 10, 2024

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. In both cases, semantic metadata is the glue that turns knowledge graphs into hubs of data, metadata, and content.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. It also helps capture and connect data based on business or domains.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Ontotext

APRIL 10, 2024

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Ontotext

MAY 30, 2019

And before we move on and look at these three in the context of the techniques Linked Data provides, here is an important reminder in case we are wondering if Linked Data is too good to be true: Linked Data is no silver bullet. 6 Linked Data, Structured Data on the Web. Linked Data and Information Retrieval.

Cost-Benefit 87

Cost-Benefit Big Data Technology Metadata 87

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 90

Data Lake Data Governance Data Architecture Machine Learning 90

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Machine Learning Consulting 78

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data. Then, you transform this data into a concise format.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

AWS Big Data

APRIL 19, 2023

The goal of a data product is to solve the long-standing issue of data silos and data quality. Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights.

Technology 93

Technology Data-driven Machine Learning Sales 93

erwin

FEBRUARY 28, 2024

While the essence of success in data governance is people and not technology, having the right tools at your fingertips is crucial. Technology is an enabler, and for data governance this is essentially having an excellent metadata management tool. Next to data governance, data architecture is really embedded in our DNA.

Metadata 52

Metadata Data Governance Data Quality Technology 52