Cloudera

SEPTEMBER 29, 2022

They are being bombarded with literature about seemingly independent new trends like data mesh and data fabric while dealing with the reality of having to work with hybrid architectures. Each of these trends claim to be complete models for their data architectures to solve the “everything everywhere all at once” problem.

Architecture 74

Architecture Data Architecture Metadata Data Warehouse 74

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

Metadata 84

Metadata BI Data Lake Business Intelligence 84

Data Engineering Podcast

JULY 3, 2022

Summary The ecosystem for data tools has been going through rapid and constant evolution over the past several years. These technological shifts have brought about corresponding changes in data and platform architectures for managing data and analytical workflows. Atlan is the metadata hub for your data ecosystem.

Architecture 100

Architecture Metadata MongoDB MySQL 100

Cloudera

AUGUST 6, 2024

Over the past several years, data leaders asked many questions about where they should keep their data and what architecture they should implement to serve an incredible breadth of analytic use cases. The future for most data teams will be multi-cloud and hybrid. It no longer matters where the data is.

Metadata 82

Metadata Government Datasets Architecture 82

Precisely

JUNE 6, 2023

At Precisely’s Trust ’23 conference, Chief Operating Officer Eric Yau hosted an expert panel discussion on modern data architectures. The group kicked off the session by exchanging ideas about what it means to have a modern data architecture.

Data Architecture 52

Data Architecture Architecture Metadata Data Lake 52

Cloudera

DECEMBER 6, 2024

The AI Forecast: Data and AI in the Cloud Era , sponsored by Cloudera, aims to take an objective look at the impact of AI on business, industry, and the world at large. AI is only as successful as the data behind it. It could be metadata that you weren’t capturing before. That’s context, that’s location.

Manufacturing 82

Manufacturing Retail Finance Metadata 82

Monte Carlo

FEBRUARY 21, 2023

Despite its prevalence, data can be messy, siloed, ungovernable, and inaccessible—especially to the non-technical employees who rely on it. Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. Table of Contents What is a data fabric?

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

Despite its prevalence, data can be messy, siloed, ungovernable, and inaccessible—especially to the non-technical employees who rely on it. Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. Table of Contents What is a data fabric?

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Data Engineering Podcast

JUNE 16, 2024

Your host is Tobias Macey and today I'm interviewing Kevin Liu about his use of Trino and Iceberg for Stripe's data lakehouse Interview Introduction How did you get involved in the area of data management? Can you describe what role Trino and Iceberg play in Stripe's data architecture?

Data Lake 147

Data Lake High Quality Data Metadata Machine Learning 147

phData: Data Engineering

NOVEMBER 1, 2024

Data Governance and Modern Data Management AI and machine learning (AI/ML) applications emerged as the leading trend in data management, significantly shaping organizations’ data platform strategies. Quotes GenAI and LLM will impact data platforms as they need a bigger amount of data to better train the models.

Government 52

Government Data Governance Finance Metadata 52

Data Engineering Podcast

JUNE 17, 2023

Summary Architectural decisions are all based on certain constraints and a desire to optimize for different outcomes. In data systems one of the core architectural exercises is data modeling, which can have significant impacts on what is and is not possible for downstream use cases. ML, reverse ETL, etc.)

Data Lake 130

Data Lake Machine Learning Metadata Data Architecture 130

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.

Metadata 110

Metadata Datasets BI SQL 110

Cloudera

JUNE 7, 2022

In our very own Enterprise Data Maturity research surveying over 3,000 IT and senior business leaders, we found that 40% of organizations are currently running hybrid but mostly on-premises, and 36% of respondents expect to shift to hybrid multi-cloud in the next 18 months. Where data flows, ideas follow.

IT 112

IT Unstructured Data Data Architecture Government 112

Snowflake

JUNE 21, 2024

Snowflake is now making it even easier for customers to bring the platform’s usability, performance, governance and many workloads to more data with Iceberg tables (now generally available), unlocking full storage interoperability. Get better Iceberg ecosystem interoperability with Primary Key information added to Iceberg table metadata.

Data Lake 124

Data Lake BI Business Intelligence Metadata 124

Precisely

DECEMBER 9, 2024

To name a few: privacy and security considerations compliance demands interest in emerging data management architectures like data mesh and data fabric increased AI adoption The findings show that data governance is the most-cited data challenge inhibiting progress toward AI initiatives (62%).

Data Governance 63

Data Governance Government Data Integration Architecture 63

Data Engineering Weekly

FEBRUARY 23, 2025

It covers nine categories: storage systems, data lake platforms, processing, integration, orchestration, infrastructure, ML/AI, metadata management, and analytics. It allows different data platforms to access and share the same underlying data without copying, treating OTFs as a storage-layer abstraction.

Data Engineering 62

Data Engineering Data Engineer Engineering Kafka 62

Cloudera

MAY 2, 2022

There are many reasons to deploy a hybrid cloud architecture — not least cost, performance, reliability, security, and control of infrastructure. But increasingly at Cloudera, our clients are looking for a hybrid cloud architecture in order to manage compliance requirements.

Cloud 104

Cloud Government Healthcare Metadata 104

Data Engineering Podcast

SEPTEMBER 23, 2018

Can you walk through the stages of an ideal lifecycle for data within the context of an organizations uses for it? What are some of the common mistakes that are made when designing a data architecture and how do they lead to failure?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Each of these architectures has its own unique strengths and tradeoffs.

Data Lake 113

Data Lake Data Warehouse Cloud Unstructured Data 113

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 . 3: Open Performance.

Metadata 92

Metadata Data Architecture BI Machine Learning 92

Cloudyard

MARCH 4, 2023

Read Time: 5 Minute, 16 Second As we know Snowflake has introduced latest badge “Data Cloud Deployment Framework” which helps to understand knowledge in designing, deploying, and managing the Snowflake landscape. Respective Cloud would consume/Store the data in bucket or containers. Snowpipe to automate the ingestion process.

Architecture 52

Architecture Cloud Metadata Data Ingestion 52

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.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Architecture 98

Netflix Tech

NOVEMBER 14, 2023

Psyberg automates our data loads, making it suitable for various data processing needs, including intraday pipeline use cases. It leverages Iceberg metadata to facilitate processing incremental and batch-based data pipelines. Psyberg: The Game Changer! This is mainly used to identify new changes since the last update.

Data Engineering 110

Data Engineering Data Engineer Engineering Metadata 110

AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Cloudera

SEPTEMBER 28, 2020

Cloudera has found that customers have spent many years investing in their big data assets and want to continue to build on that investment by moving towards a more modern architecture that helps leverage the multiple form factors. This has a great architectural insight into Hive on Tez. Background: . on roadmap).

Cloud 132

Cloud Kafka Professional Services Metadata 132

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 88

Data Lake Business Intelligence Metadata Data Warehouse 88

Monte Carlo

FEBRUARY 9, 2023

Over the past several years, data warehouses have evolved dramatically, but that doesn’t mean the fundamentals underpinning sound data architecture needs to be thrown out the window. While data vault has many benefits, it is a sophisticated and complex methodology that can present challenges to data quality.

Architecture 52

Architecture Raw Data Metadata Data Warehouse 52

Data Engineering Podcast

JULY 28, 2019

In this episode Tim Ward, CEO of CluedIn, explains the idea of eventual connectivity as a new paradigm for data integration. Rather than manually defining all of the mappings ahead of time, we can rely on the power of graph databases and some strategic metadata to allow connections to occur as the data becomes available.

Data Integration 100

Data Integration Metadata Architecture Media 100

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Traditional data warehouse platform architecture. Data lake architecture example.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Databand.ai

AUGUST 30, 2023

DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Snowflake

DECEMBER 12, 2023

To give customers flexibility for how they fit Snowflake into their data architecture, Iceberg Tables can be configured to use either Snowflake or an external service such as AWS Glue as the table’s catalog to track metadata, with an easy, one-line SQL command to convert the table’s catalog to Snowflake in a metadata-only operation.

Metadata 114

Metadata Python Government AWS 114

Data Engineering Podcast

AUGUST 5, 2019

We have partnered with organizations such as O’Reilly Media, Dataversity, the Open Data Science Conference, and Corinium Intelligence. Upcoming events include the O’Reilly AI Conference, the Strata Data Conference, and the combined events of the Data Architecture Summit and Graphorum.

PostgreSQL 100

PostgreSQL MongoDB Metadata Media 100

ProjectPro

JANUARY 31, 2022

This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Its analytical skills enable companies to gain significant insights from their data and make better decisions.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Towards Data Science

OCTOBER 25, 2023

Not too long ago, almost all data architectures and data team structures followed a centralized approach. As a data or analytics engineer, you knew where to find all the transformation logic and models because they were all in the same codebase. Your organization may be undergoing the decentralization of data.

Data Pipeline 98

Data Pipeline SQL Data Architecture Data 98

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.

Retail 106

Retail Telecommunication Manufacturing Insurance 106

Towards Data Science

FEBRUARY 15, 2023

In this context, data management in an organization is a key point for the success of its projects involving data. One of the main aspects of correct data management is the definition of a data architecture. The Lakehouse architecture was one of them. show() The history object is a Spark Data Frame.

Data Lake 98

Data Lake Data Warehouse Hadoop Architecture 98

Rockset

JULY 21, 2020

Metadata services used for service discovery are close to the bottom of that stack and they need to provide 1 or 2 orders of magnitude higher reliability than any service built on top of that. In your application stack, assume for every level you have in your stack, you will lose one 9 in your application’s reliability.

Data Architecture 40

Data Architecture Architecture Building Data 40