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

Data Engineering Podcast

OCTOBER 15, 2021

Summary The binding element of all data work is the metadata graph that is generated by all of the workflows that produce the assets used by teams across the organization. The DataHub project was created as a way to bring order to the scale of LinkedIn’s data needs. No more scripts, just SQL.

Metadata 100

Metadata BI Data Warehouse Government 100

Netflix Tech

DECEMBER 21, 2020

By Anupom Syam Background At Netflix, our current data warehouse contains hundreds of Petabytes of data stored in AWS S3 , and each day we ingest and create additional Petabytes. Some of the optimizations are prerequisites for a high-performance data warehouse.

Data Warehouse 83

Data Warehouse Metadata Algorithm Data 83

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 104

Architecture Metadata Machine Learning Unstructured Data 104

Monte Carlo

AUGUST 25, 2023

Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

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 77

Architecture Data Architecture Metadata Data Warehouse 77

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

Data Warehouse 99

Data Warehouse Cloud Consulting SQL 99

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 81

Data Architecture Architecture Data Lake NoSQL 81

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

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

Data Engineering Podcast

FEBRUARY 5, 2023

Sign up now for early access to Materialize and get started with the power of streaming data with the same simplicity and low implementation cost as batch cloud data warehouses. Go to [dataengineeringpodcast.com/materialize]([link] Support Data Engineering Podcast

Data Engineer 147

Data Engineer Data Engineering Engineering PostgreSQL 147

AltexSoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Data warehouse vs. data lake in a nutshell.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

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? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

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

Netflix Tech

OCTOBER 27, 2020

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The processed data is typically stored as data warehouse tables in AWS S3.

Data Warehouse 99

Data Warehouse Datasets Data Big Data 99

Data Engineering Podcast

AUGUST 13, 2022

Select Star’s data discovery platform solves that out of the box, with an automated catalog that includes lineage from where the data originated, all the way to which dashboards rely on it and who is viewing them every day.

Metadata 100

Metadata MongoDB Scala MySQL 100

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse 72

Data Warehouse Cloud Kafka Cloud Storage 72

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

DECEMBER 3, 2024

For decades, they have been struggling with scale, speed, and correctness required to derive timely, meaningful, and actionable insights from vast and diverse big data environments. Despite various architectural patterns and paradigms, they still end up with perpetual “data puddles” and silos in many non-interoperable data formats.

Metadata 52

Metadata SQL Database Data Warehouse 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

AltexSoft

AUGUST 22, 2022

In this post, we’ll attempt to explain the idea behind a data fabric, its architectural building blocks, the benefits it brings, and ways to approach its implementation. What is data fabric? to provide a unified view of all enterprise data. Data fabric architecture example. Data fabric vs data mesh.

Architecture 52

Architecture Metadata Data Lake Machine Learning 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

Rockset

APRIL 26, 2023

We’ve noticed many common patterns across streaming data architectures and we’ll be sharing a blueprint for three of the most popular: anomaly detection, IoT, and recommendations. The majority of anomaly detectors require streaming data, real-time data and historical data in order to generate inferences.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Cloudera

OCTOBER 10, 2024

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

IT 87

IT Data Lake Metadata Data Warehouse 87

Precisely

JUNE 24, 2024

His key takeaways from the conversation were that “ data leaders are under tremendous pressure to collaborate within the C-Suite on projects that deliver true business value. Explore the key topics and insights from this event below, and get inspired to apply these takeaways for success in your own data-driven journey.

Food 94

Food Data Analytics Pharmaceutical Consulting 94

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Data Engineering Podcast

NOVEMBER 20, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it.

Systems 130

Systems Metadata Data Pipeline MongoDB 130

Uber Engineering

AUGUST 3, 2018

Data powers Uber’s global marketplace, enabling more reliable and seamless user experiences across our products for riders, … The post Databook: Turning Big Data into Knowledge with Metadata at Uber appeared first on Uber Engineering Blog.

Metadata 110

Metadata Big Data Transportation Data 110

ThoughtSpot

MAY 31, 2023

The architecture is designed to be resilient against new-age attacks against LLMs like prompt injection and prompt leaks. Architecture Let's start with the big picture and tackle how we adjusted our cloud architecture with additional internal and external interfaces to integrate LLM.

Data Security 98

Data Security Metadata Transportation Data Warehouse 98

Rockset

APRIL 11, 2023

Rockset hosted a tech talk on its new cloud architecture that separates storage-compute and compute-compute for real-time analytics. With compute-compute separation in the cloud, users can allocate multiple, isolated clusters for ingest compute or query compute while sharing the same real-time data.

Architecture 52

Architecture Cloud Bytes Metadata 52

Monte Carlo

JANUARY 25, 2023

When it comes to the question of building or buying your data stack, there’s never a one-size-fits-all solution for every data team—or every component of your data stack. Data storage and compute are very much the foundation of your data platform. Let’s jump in! So, let’s take a look at each in a bit more detail.

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Cloudera

NOVEMBER 15, 2024

Read on to discover the issues that cyber defenders face leveraging data, analytics, and AI to do their jobs, how Cloudera’s open data lakehouse mitigates those issues, and how this architecture is crucial for successfully navigating the complexities of the modern cybersecurity landscape.

Metadata 87

Metadata Unstructured Data Data Lake Government 87

Data Engineering Podcast

DECEMBER 19, 2021

Summary Building a well managed data ecosystem for your organization requires a holistic view of all of the producers, consumers, and processors of information. The team at Metaphor are building a fully connected metadata layer to provide both technical and social intelligence about your data. No more scripts, just SQL.

Systems 100

Systems Building Metadata Data Warehouse 100

Christophe Blefari

JANUARY 20, 2024

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. My advice on this point is to learn from others.

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52