Hevo

SEPTEMBER 17, 2024

Organizations have begun to built data warehouses and lakes to analyze large amounts of data for insights and business reports. Often time they bring data from multiple data silos into their data lake and also have data stored in particular data stores like NoSQL databases to support different use cases.

Data Architecture 40

Data Architecture Architecture NoSQL Data Lake 40

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures. Lack of sharing hinders the elimination of fraud, waste, and abuse. Forrester ).

Data Architecture 79

Data Architecture Architecture Data Lake NoSQL 79

Data Engineering Podcast

DECEMBER 8, 2019

Summary Data warehouses have gone through many transformations, from standard relational databases on powerful hardware, to column oriented storage engines, to the current generation of cloud-native analytical engines. If you are evaluating your options for building or migrating a data platform, then this is definitely worth a listen.

Data Warehouse 100

Data Warehouse Cloud AWS Relational Database 100

Data Engineering Podcast

OCTOBER 14, 2019

Summary Managing a data warehouse can be challenging, especially when trying to maintain a common set of patterns. We have partnered with organizations such as O’Reilly Media, Dataversity, Corinium Global Intelligence, Alluxio, and Data Council.

Data Warehouse 100

Data Warehouse PostgreSQL AWS Programming Language 100

Acceldata

DECEMBER 19, 2022

Avoid these three data pitfalls when attempting to modernize your data architecture with a data lake or data warehouse.

Data Lake 52

Data Lake Data Warehouse Data Architecture Data 52

Data Engineering Podcast

JULY 8, 2019

Summary The market for data warehouse platforms is large and varied, with options for every use case. We have partnered with organizations such as O’Reilly Media, Dataversity, and the Open Data Science Conference. Coming up this fall is the combined events of Graphorum and the Data Architecture Summit.

Data Warehouse 100

Data Warehouse MySQL Hadoop Data Lake 100

Monte Carlo

APRIL 16, 2022

The data warehouse is the foundation of the modern data stack, so it caught our attention when we saw Convoy head of data Chad Sanderson declare, “ the data warehouse is broken ” on LinkedIn. Treating data like an API. Immutable data warehouses have challenges too.

Data Warehouse 52

Data Warehouse Architecture Data Data Architect 52

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. First, we describe how data mesh and data fabric could be related.

Architecture 74

Architecture Data Architecture Metadata Data Warehouse 74

Snowflake

JULY 27, 2023

Over the course of this journey, HomeToGo’s data needs have evolved considerably. It also came with other advantages such as independence of cloud infrastructure providers, data recovery features such as Time Travel , and zero copy cloning which made setting up several environments — such as dev, stage or production — way more efficient.

Data Architecture 52

Data Architecture Architecture Building Structured Data 52

Confluent

OCTOBER 30, 2020

A fundamental challenge with today’s “data explosion” is finding the best answer to the question, “So where do I put my data?” while avoiding the longer-term problem of data warehouses, […].

Data Architecture 119

Data Architecture Architecture Kafka Building 119

Data Engineering Weekly

AUGUST 6, 2024

CDC tools fuel analytical apps and mission-critical data feeds in banking and regulated industries, with use cases ranging from data synchronization, managing risk, and preventing fraud to driving personalization. This approach simplifies data architecture and enhances performance by reducing data movement and latency.

Data Lake 125

Data Lake Data Warehouse Database Data Architecture 125

Towards Data Science

JANUARY 16, 2024

When I heard the words ‘decentralised data architecture’, I was left utterly confused at first! In my then limited experience as a Data Engineer, I had only come across centralised data architectures and they seemed to be working very well. Result: Data warehouse was born. So what was missing?

Data Warehouse 64

Data Warehouse Data Architecture Relational Database NoSQL 64

Snowflake

JANUARY 30, 2023

By running data warehouse and data engineering workloads on Snowflake’s Data Cloud Ramp improves performance and user experience, while delivering powerful insights to customers quickly. How do you scale seamlessly, without worrying about keeping the lights on?

Data Architecture 52

Data Architecture Architecture Management Datasets 52

Towards Data Science

DECEMBER 4, 2023

Anyways, I wasn’t paying enough attention during university classes, and today I’ll walk you through data layers using —  guess what  —  an example. Business Scenario & Data Architecture Imagine this: next year, a new team on the grid, Red Thunder Racing, will call us (yes, me and you) to set up their new data infrastructure.

Data Engineer 82

Data Engineer Data Engineering Engineering Data Lake 82

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Understanding the essential components of data pipelines is crucial for designing efficient and effective data architectures.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Data Engineering Podcast

JUNE 17, 2023

Sign up free at dataengineeringpodcast.com/rudderstack - Your host is Tobias Macey and today I'm interviewing Satish Jayanthi about the practice and promise of building a column-aware data architecture through intentional modeling Interview Introduction How did you get involved in the area of data management?

Data Lake 130

Data Lake Machine Learning Metadata Data Architecture 130

RandomTrees

SEPTEMBER 27, 2024

Data Factory, Data Activator, Power BI, Synapse Real-Time Analytics, Synapse Data Engineering, Synapse Data Science, and Synapse Data Warehouse are some of them. With One Lake serving as a primary multi-cloud repository, Fabric is designed with an open, lake-centric architecture.

Database-centric 52

Database-centric Pipeline-centric IT BI 52

Cloudera

AUGUST 21, 2024

The root of the problem comes down to trusted data. Pockets and siloes of disparate data can accumulate across an enterprise or legacy data warehouses may not be equipped to properly manage a sea of structured and unstructured data at scale.

Unstructured Data 65

Unstructured Data Business Intelligence Data Architecture Data Warehouse 65

Simon Späti

NOVEMBER 28, 2018

However, this is still not common in the Data Warehouse (DWH) field. In my recent blog, I researched OLAP technologies, for this post I chose some open-source technologies and used them together to build a full data architecture for a Data Warehouse system. These days, everyone talks about open-source.

Data Warehouse 130

Data Warehouse Data Storage Data Architecture Architecture 130

Scott Logic

APRIL 18, 2024

In this episode, Oliver Cronk, Andrew Carr and David Hope talk about the ever-changing world of data, with conversations moving from data warehouse to data lake, and data mesh to data fabric.

Data Lake 59

Data Lake Data Warehouse Data Architecture Architecture 59

Knowledge Hut

MARCH 28, 2024

They work together with stakeholders to get business requirements and develop scalable and efficient data architectures. Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

Cloudera

AUGUST 20, 2024

Trusted data is what makes the outputs of AI not just accurate, but impactful in decision making. Ensuring data is trustworthy comes with its own complications. Cloudera’s State of Enterprise AI and Modern Data Architecture survey identified several challenges when it comes to data.

Data Lake 78

Data Lake Government Data Governance Data Architecture 78

Data Engineering Podcast

APRIL 3, 2022

Summary The flexibility of software oriented data workflows is useful for fulfilling complex requirements, but for simple and repetitious use cases it adds significant complexity. Coalesce is a platform designed to reduce repetitive work for common workflows by adopting a visual pipeline builder to support your data warehouse transformations.

Data Warehouse 100

Data Warehouse Data Workflow Data Architecture SQL 100

Data Engineering Podcast

JULY 3, 2022

Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

Architecture 100

Architecture Metadata MongoDB MySQL 100

phData: Data Engineering

NOVEMBER 8, 2024

Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data. Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. FAQs What is a Data Lakehouse?

Architecture 52

Architecture Systems Data Lake Google Cloud 52

ProjectPro

JULY 22, 2016

For the same cost, organizations can now store 50 times as much data as in a Hadoop data lake than in a data warehouse. Data lake is gaining momentum across various organizations and everyone wants to know how to implement a data lake and why.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

Data Engineering Podcast

SEPTEMBER 23, 2018

This includes modeling the lifecycle of your information as a pipeline from the raw, messy, loosely structured records in your data lake, through a series of transformations and ultimately to your data warehouse. Can you walk through the stages of an ideal lifecycle for data within the context of an organizations uses for it?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Monte Carlo

MARCH 6, 2024

Table of Contents Supporting Multi-Database Architectures Keep An Eye On This Space Supporting Multi-Database Architectures We’ve been aggressively adding these integrations to better support complex data architectures. End-to-end data lineage then helps trace these issues to their point of origin.

Database 52

Database MySQL Data Warehouse Architecture 52

Data Engineering Weekly

DECEMBER 2, 2023

Revisiting The Current State of Data Infrastructure Let’s revisit the current state of the data infrastructure before discussing the S3 Express. There are two critical properties of data warehouse access patterns. Data freshness matters a lot—the more recent the data, the more frequently it is accessed.

IT 85

IT BI AWS Kafka 85

Monte Carlo

OCTOBER 31, 2024

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Data Storage Solutions As we all know, data can be stored in a variety of ways.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 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 93

Data Lake Data Warehouse BI SQL 93

Striim

AUGUST 20, 2024

One powerful way to achieve this transformation is by modernizing data architecture and migrating to the cloud. For retailers, modernizing data architecture is not just about upgrading technology—it’s about empowering teams with better, faster access to data while future-proofing their infrastructure.

Retail 52

Retail Cloud Google Cloud Data Architecture 52

Precisely

JULY 18, 2024

Key Takeaways Data Fabric is a modern data architecture that facilitates seamless data access, sharing, and management across an organization. Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata.

Data Management 52

Data Management Management Metadata Database-centric 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. The past decades of enterprise data platform architectures can be summarized in 69 words. Introduction to Data Mesh. Source: Thoughtworks.

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Architecture 98

Monte Carlo

APRIL 27, 2023

Empowered by the rise of the modern data stack , leading companies like Warner Music Group , Chime and Petsmart are now turning to the Composable CDP to unlock a modular customer data architecture that centers on the cloud data warehouse. Why not build one single store of customer data to activate from centrally?

Data Warehouse 72

Data Warehouse Data Collection Architecture Data Storage 72

Data Engineering Weekly

DECEMBER 29, 2022

era of Data Catalog Let’s call the pre-modern era; as the state of Data Warehouses before the explosion of big data and subsequent cloud data warehouse adoption. Applications deployed in a large monolithic web server with all the data warehouse changes go through a central data architecture team.

Metadata 62

Metadata Data Warehouse ETL Tools Data Workflow 62

Monte Carlo

AUGUST 30, 2024

It’s our goal at Monte Carlo to provide data observability and quality across the enterprise by monitoring every system vital in the delivery of data from source to consumption. We started with popular modern data warehouses and quickly expanded our support as data lakes became data lakehouses.

SQL 40

SQL Engineering Data Lake High Quality Data 40