TDAN

MAY 31, 2022

The main goal of creating an enterprise data fabric is not new. It is the ability to deliver the right data at the right time, in the right shape, and to the right data consumer, irrespective of how and where it is stored. Data fabric is the common “net” that stitches integrated data from multiple data […].

Metadata 98

Metadata Enterprise IT Data Architecture 98

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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 Modeling Enterprise Management 93

Ontotext

APRIL 10, 2024

Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience. Drowning in Data, Thirsting for Context We’ve heard the saying, “Data, data everywhere. ” As more data accumulates, context gets diluted and lost.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Alation

AUGUST 18, 2022

The complex challenge here is to have the lineage be intelligently updated as the data landscape and processing dynamically bubbles and changes daily across an enterprise. Active metadata will play a critical role in automating such updates as they arise. Get the latest data cataloging news and trends in your inbox.

Metadata 69

Metadata Visualization Statistics Data Architecture 69

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 52

Metadata Management Business Intelligence Data Governance 52

CIO Business Intelligence

MARCH 24, 2023

Whereas data governance is about the roles, responsibilities, and processes for ensuring accountability for and ownership of data assets, DAMA defines data management as “an overarching term that describes the processes used to plan, specify, enable, create, acquire, maintain, use, archive, retrieve, control, and purge data.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

APRIL 29, 2024

Based on this example and considering your enterprise requirements, it becomes feasible and flexible to manage permissions in the data warehouse effectively. About the Authors Yuzhu Xiao is a Senior Data Development Engineer at Amber Group with extensive experience in cloud data platform architecture.

Management 89

Management Big Data Metadata Data Warehouse 89

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. CCPA vs. GDPR: Key Differences.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

AWS Big Data

OCTOBER 3, 2023

Over the years, data lakes on Amazon Simple Storage Service (Amazon S3) have become the default repository for enterprise data and are a common choice for a large set of users who query data for a variety of analytics and machine leaning use cases. Note that the migrate procedure isn’t supported in AWS Glue Data Catalog.

Data Lake 100

Data Lake Metadata Snapshot Recreation/Entertainment 100

Ontotext

DECEMBER 1, 2023

It enriched their understanding of the full spectrum of knowledge graph business applications and the technology partner ecosystem needed to turn data into a competitive advantage. Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises.

Metadata 78

Metadata Sales Consulting Enterprise 78

erwin

JULY 12, 2019

With all the advance notice and significant chatter for GDPR/CCPA, why aren’t organizations more prepared to deal with data regulations? The complexity of regulatory requirements in and of themselves is aggravated by the complexity of the business and data landscapes within most enterprises. Complexity. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

JANUARY 9, 2023

Another agency later also published a legally binding standard to strengthen risk management for financial institutions with specific language related to data architecture and IT infrastructure. In other words, the business process must define data as an input and output of each process step.

Risk Management 52

Risk Management Risk Management Metadata 52

Ontotext

NOVEMBER 16, 2023

Clarifying what data mesh is and how it works is important, but even more so is starting with the why. Why Organizations Need A Data Mesh The data mesh paradigm aims to address some of the biggest pain points for most organizations. This becomes particularly problematic when dealing with veracity of data.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Cloudera

JUNE 7, 2022

Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors. Companies can now capitalize on the value in all their data, by delivering a hybrid data platform for modern data architectures with data anywhere.

IT 106

IT Data Architecture Unstructured Data Big Data 106

CIO Business Intelligence

JUNE 23, 2022

Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors. Companies can now capitalize on the value in all their data, by delivering a hybrid data platform for modern data architectures with data anywhere. Jonathan Takiff / IDG.

IT 97

IT Data Architecture Unstructured Data Big Data 97

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 75

Enterprise Management Strategy Data Lake 75

Alation

FEBRUARY 13, 2020

Following a very successful year of growth in Alation’s business, this announcement marks a milestone for Alation and the enterprise data catalog market. What started six years ago as one startup trying to improve the way people work with data has become a full-blown market category – Machine Learning Data Catalogs.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

AWS Big Data

APRIL 26, 2023

Having an accurate and up-to-date inventory of all technical assets helps an organization ensure it can keep track of all its resources with metadata information such as their assigned oners, last updated date, used by whom, how frequently and more. This is a guest blog post co-written with Corey Johnson from Huron.

Metadata 52

Metadata Dashboards Visualization Consulting 52

Alation

MARCH 31, 2023

Ehtisham Zaidi, Gartner’s VP of data management, and Robert Thanaraj, Gartner’s director of data management, gave an update on the fabric versus mesh debate in light of what they call the “active metadata era” we’re currently in. The foundations of successful data governance The state of data governance was also top of mind.

Data Analytics 52

Data Analytics Analytics Metadata Data Governance 52

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 111

Data Lake Analytics Dashboards Metrics 111

erwin

OCTOBER 16, 2020

There’s a common denominator in what they’re all missing, and that is data intelligence. The result is an automated, real-time, high-quality data pipeline from which accurate insights can be derived. 1 of erwin Insights 2020, our virtual conference on enterprise modeling and data governance/intelligence.

Internet of Things 145

Internet of Things Data-driven Uncertainty Data Governance 145

Cloudera

JANUARY 5, 2023

What is certain is that having an enterprise data strategy aligned to the organization’s cloud strategy and business priorities will help the organization drive greater business value by improving operational efficiencies and unlocking new revenue streams. Find out more about CDP for modern data architectures here.

Cost-Benefit 52

Cost-Benefit Business Objectives Machine Learning Data Architecture 52

erwin

SEPTEMBER 17, 2020

It’s paramount that organizations understand the benefits of automating end-to-end data lineage. Critically, it makes it easier to get a clear view of how information is created and flows into, across and outside an enterprise. The importance of end-to-end data lineage is widely understood and ignoring it is risky business.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Alation

FEBRUARY 20, 2020

Since we launched the company, Alation has delivered a unique way to catalog data for the enterprise. to catalog enterprise data by observing analyst behaviors. Our approach was contrasted with the traditional manual wiki of notes and documentation and labeled as a modern data catalog. Can I trust this data?

Metadata 52

Metadata Enterprise Data Processing Data Architecture 52

Alation

APRIL 19, 2021

The cloud supports this new workforce, connecting remote workers to vital data, no matter their location. Today, enterprises are migrating to the cloud at a brisk pace. Data Cloud Migration Challenges and Solutions. Cloud migration is the process of moving enterprise data and infrastructure from on premise to off premise.

Cost-Benefit 111

Cost-Benefit Strategy Enterprise Data Strategy 111

Ontotext

APRIL 15, 2020

Their ability to derive new knowledge out of existing facts and uncover hidden relationships make them best suited to analyze rapidly changing data from disparate sources. Ontotext’s policy is to donate licences for the GraphDB Enterprise Edition to such projects as well as support and maintenance services.

Publishing 105

Publishing Metadata Data mining Technology 105

AWS Big Data

APRIL 19, 2023

However, when a data producer shares data products on a data mesh self-serve web portal, it’s neither intuitive nor easy for a data consumer to know which data products they can join to create new insights. This is especially true in a large enterprise with thousands of data products.

Technology 80

Technology Data-driven Machine Learning Sales 80

Cloudera

OCTOBER 11, 2022

You also need to continually feed models new data to keep them up to date. Most AI apps and ML models need different types of data – real-time data from devices, equipment, and assets and traditional enterprise data – operational, customer, service records. . Data needs to be prepared and analyzed.

Snapshot 89

Snapshot Data Science Digital Transformation Metadata 89

IBM Big Data Hub

JUNE 30, 2022

As ecosystems transformed over the last few years and simultaneously increased the opportunities to improve results driven by data, a few main contributing factors drove major change in how you should think about your data strategy: The reality of hybrid multicloud and its accelerated adoption has created new possibilities and challenges.

Data Strategy 57

Data Strategy Strategy Business Objectives Data-driven 57

CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Octopai

JUNE 15, 2020

With the insurance company’s current data architecture, the process would have no chance of being completed in time for the change. Faced with these data limitations, the insurance company reached out to Octopai. With the implementation of these data lineage tools, the process was streamlined. Yup, you read that right.

Insurance 52

Insurance Metadata Business Intelligence Data Warehouse 52

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 59

Management Enterprise Strategy IT 59

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Sentry Hive / HDFS ACL sync is not included in CDP-DC 7.1 (on

Testing 130

Testing Metadata Risk Data Science 130

Data Virtualization

MARCH 3, 2021

Data is the fuel of the digital economy, so data-centric organizations have a distinct advantage. To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is.

Management 52

Management Enterprise Strategy IT 52

AWS Big Data

MARCH 10, 2023

Apache Iceberg overview Iceberg is an open-source table format that brings the power of SQL tables to big data files. It enables ACID transactions on tables, allowing for concurrent data ingestion, updates, and queries, all while using familiar SQL. Data can be organized into three different zones, as shown in the following figure.

Data Lake 100

Data Lake Sales Data Warehouse Snapshot 100