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

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

Cloudera

SEPTEMBER 29, 2022

Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem. Data teams are confused as to whether they should get on the bandwagon of just one of these trends or pick a combination. Data mesh defined. Data mesh conceptual hierarchy.

Data Architecture 73

Data Architecture Metadata Data Warehouse Sales 73

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

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

erwin

JULY 12, 2019

In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. for alleged violations of the European Union’s General Data Protection Regulation (GDPR). Manage policies and rules. Five Steps to GDPR/CCPA Compliance.

Data Governance 110

Data Governance Management Metadata Risk Management 110

Alation

JANUARY 9, 2023

But data leaders must work quickly, and use the right tools, to understand, manage, and protect data while complying with related regulations and standards. The Increasing Focus On Data Risk Management. From DCAM To Data Catalog. Download the complete white paper now. Download the complete white paper now.

Risk Management 52

Risk Management Risk Management Metadata 52

Ontotext

JANUARY 10, 2024

In Computer Science, we are trained to use the Okham razor – the simplest model of reality that can get the job done is the best one. Next, I will explain how knowledge graphs help them to get a unified view to data derived from multiple sources and get richer insights in less time. We call this the Bad Data Tax.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

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. Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

MARCH 6, 2024

SAP unveiled Datasphere a year ago as a comprehensive data service, built on SAP Business Technology Platform (BTP), to provide a unified experience for data integration, data cataloging, semantic modeling, data warehousing, data federation, and data virtualization.

Unstructured Data 120

Unstructured Data Dashboards Business Intelligence Data Governance 120

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. In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Ontotext

AUGUST 4, 2023

Working across data islands leads to siloed thinking and the inability to implement critical business initiatives such as Customer, Product, or Asset 360. As data is generated, stored, and used across data centers, edge, and cloud providers, managing a distributed storage environment is complex with no map to guide technology professionals.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

CIO Business Intelligence

AUGUST 3, 2023

But reaching all these goals, as well as using enterprise data for generative AI to streamline the business and develop new services, requires a proper foundation. That hard, ongoing work includes integrating siloed data, modeling, and understanding it, as well as maintaining and securing it over time.

Analytics 96

Analytics Data Lake Metadata Cost-Benefit 96

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 94

Strategy Data Architecture Cost-Benefit Reporting 94

Cloudera

FEBRUARY 22, 2022

Over the past decade, the successful deployment of large scale data platforms at our customers has acted as a big data flywheel driving demand to bring in even more data, apply more sophisticated analytics, and on-board many new data practitioners from business analysts to data scientists. Key Design Goals .

Snapshot 105

Snapshot Metadata Cost-Benefit Data Architecture 105

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. 1: Multi-function analytics . 2: Open formats. 3: Open Performance.

Metadata 88

Metadata Data Architecture Machine Learning Cost-Benefit 88

Cloudera

JUNE 7, 2022

The cause is hybrid data – the massive amounts of data created everywhere businesses operate – in clouds, on-prem, and at the edge. Only a fraction of data created is actually stored and managed, with analysts estimating it to be between 4 – 6 ZB in 2020. Today, we are leading the way in hybrid data.

IT 108

IT Data Architecture Unstructured Data Big Data 108

Ontotext

FEBRUARY 7, 2024

This also results in the information loss I’ve already mentioned and severely impacts our insight creation and monetizing the data. The first element we need for such an architecture is to set our terminology management. Besides a vague understanding, there is little support from management for a real breakthrough.

Metadata 52

Metadata Data Integration Measurement Data-driven 52

Jen Stirrup

MARCH 29, 2023

Data as a product as well as a foundation The data foundation is critical for all types of reporting and analytics. Data needs to be respected in the same way as building a product. There’s a new trend for people to talk about data products, bringing a product management mindset to the production of data assets.

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

TDAN

AUGUST 18, 2020

Standards exist for naming conventions, abbreviations and other pertinent metadata properties. Consistent business meaning is important because distinctions between business terms are not typically well defined or documented. What are the standards for writing […].

Management 96

Management Metadata Data Architecture IT 96

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

CIO Business Intelligence

JUNE 23, 2022

The cause is hybrid data – the massive amounts of data created everywhere businesses operate – in clouds, on-prem, and at the edge. Only a fraction of data created is actually stored and managed, with analysts estimating it to be between 4 – 6 ZB in 2020. It has evolved into something new – hybrid data.

IT 86

IT Data Architecture Unstructured Data Big Data 86

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

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Overview of the BMW Cloud Data Hub At the BMW Group, Cloud Data Hub (CDH) is the central platform for managing company-wide data and data solutions.

Dashboards 99

Dashboards Analytics Metadata Data Warehouse 99

Ontotext

NOVEMBER 16, 2023

Think of data mesh as an operational mode for organizations with a domain-driven, decentralized data architecture. By pushing the ownership to the product owners of the data, it can better serve the consumers, changing the way data projects are managed within organizations.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

DataKitchen

AUGUST 8, 2023

However, the market for Data Observability is fragmented and lacks a standard accepted definition, leading to confusion and tool adoption issues. She sees Data Observability as an emerging technology in data engineering and management. Are problems with data tests? Let’s start with a scenario. When did it last run?

Data Quality 130

Data Quality Testing Snapshot Reporting 130

AWS Big Data

JULY 14, 2023

Consumers prioritized data discoverability, fast data access, low latency, and high accuracy of data. Producers prioritized ownership, governance, access management, and reuse of their datasets. These inputs reinforced the need of a unified data strategy across the FinOps teams.

Finance 86

Finance Metadata Big Data Recreation/Entertainment 86

AWS Big Data

MARCH 26, 2024

AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud. Streaming data with low latency needs is stored in Amazon Kinesis Data Streams for real-time consumption.

Data Strategy 72

Data Strategy Strategy Data Warehouse Prescriptive Analytics 72

Cloudera

OCTOBER 7, 2021

The need for a decentralized data mesh architecture stems from the challenges organizations faced when implementing more centralized data management architectures – challenges that can attributed to both technology (e.g., difficulty to achieve cross-organizational governance model).

Metadata 122

Metadata Cost-Benefit Enterprise Interactive 122

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. Monitoring Job Metadata. Using Version Control.

Testing 152

Testing Metadata Dashboards Statistics 152

Cloudera

OCTOBER 11, 2022

Because that is how models learn. 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. .

Snapshot 90

Snapshot Data Science Digital Transformation Metadata 90

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. Enables a hub-and-spoke model for Data Access in multiple AWS accounts in a data mesh fashion.

Metadata 52

Metadata Dashboards Visualization Consulting 52

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 84

Data Lake Data Architecture Metadata Data Warehouse 84

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 85

Data Lake Data Governance Data Architecture Machine Learning 85

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 95

Data Lake Unstructured Data Management Modeling 95

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 89

Enterprise Data Warehouse Data Lake Optimization 89

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. Moreover, running advanced analytics and ML on disparate data sources proved challenging. To overcome these issues, Orca decided to build a data lake.

Data Lake 90

Data Lake Analytics Snapshot Optimization 90