Lyft Engineering

NOVEMBER 29, 2023

Introduction At Lyft, we have used systems like Apache ClickHouse and Apache Druid for near real-time and sub-second analytics. Sub-second query systems allow for near real-time data explorations and low latency, high throughput queries, which are particularly well-suited for handling time-series data.

Kafka 104

Kafka Data Ingestion Datasets Architecture 104

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Rockset

JANUARY 30, 2024

In 2023, Rockset announced a new cloud architecture for search and analytics that separates compute-storage and compute-compute. With this architecture, users can separate ingestion compute from query compute, all while accessing the same real-time data. This is a game changer in disaggregated, real-time architectures.

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

Cloudera

NOVEMBER 1, 2023

And so we are thrilled to introduce our latest applied ML prototype (AMP) — a large language model (LLM) chatbot customized with website data using Meta’s Llama2 LLM and Pinecone’s vector database. High-level overview of real-time data ingest with Cloudera DataFlow to Pinecone vector database.

Machine Learning 105

Machine Learning Data Ingestion Database Architecture 105

Data Engineering Weekly

MARCH 17, 2024

It defines AI broadly, including any machine-based system influencing physical or virtual environments, and categorizes AI applications by risk, from banned "Unacceptable Risk AI Systems" to scrutinized "High-Risk AI Systems." Examining the advantages and drawbacks associated with different approaches to embedding analytics. -

Data Engineering 70

Data Engineering Data Engineer Engineering Data Governance 70

Data Engineering Podcast

AUGUST 21, 2022

The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Sifflet also offers a 2-week free trial.

Lambda Architecture 100

Lambda Architecture MongoDB Scala MySQL 100

Knowledge Hut

APRIL 23, 2024

It is designed to support business intelligence (BI) and reporting activities, providing a consolidated and consistent view of enterprise data. Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Christophe Blefari

JANUARY 20, 2024

What is data engineering As I said it before data engineering is still a young discipline with many different definitions. Still, we can have a common ground when mixing software engineering, DevOps principles, Cloud — or on-prem — systems understanding and data literacy.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Data Engineering Podcast

SEPTEMBER 25, 2022

Summary Data integration from source systems to their downstream destinations is the foundational step for any data product. With the increasing expecation for information to be instantly accessible, it drives the need for reliable change data capture. That’s where our friends at Ascend.io

Food 100

Food MongoDB Scala MySQL 100

Zalando Engineering

JUNE 26, 2017

Information Retrieval (IR) systems are a vital component in the core of successful modern web platforms, and Zalando understand their importance incredibly well. The main goal of IR systems is to provide a communication layer that enables customers to establish a retrieval dialogue with underlying data.

Architecture 40

Architecture Unstructured Data Machine Learning Data Ingestion 40

Rockset

JULY 6, 2022

This is the fifth post in a series by Rockset's CTO and Co-founder Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. It's not true and is just one of many outdated data myths that modern offerings such as Rockset are busting.

NoSQL 52

NoSQL SQL Systems PostgreSQL 52

Data Engineering Weekly

MAY 16, 2023

In the first part of this series, we talked about design patterns for data creation and the pros & cons of each system from the data contract perspective. In the second part, we will focus on architectural patterns to implement data quality from a data contract perspective.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Data Engineering Podcast

JUNE 12, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Unstructured Data 130

Unstructured Data MongoDB Scala MySQL 130

Cloudera

AUGUST 11, 2022

And while operations in the cyber-domain are more likely to make the evening news, there are a vast array of critical use cases that support the military’s need for a data architecture that collects, processes, and delivers any type of data, anywhere. . Universal Data Distribution Solves DoD Data Transport Challenges.

Transportation 89

Transportation Data Ingestion Architecture Data 89

Data Engineering Podcast

OCTOBER 9, 2022

In this episode Purvi Shah, the VP of Enterprise Big Data Platforms at American Express, explains how they have invested in the cloud to power this visibility and the complex suite of integrations they have built and maintained across legacy and modern systems to make it possible. That’s where our friends at Ascend.io

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

JUNE 5, 2022

The team at Skyflow decided that the second best way is to build a storage system dedicated to securely managing your sensitive information and making it easy to integrate with your applications and data systems. How have the design and goals of the system changed or evolved over time? That’s where our friends at Ascend.io

Data Security 100

Data Security Metadata MongoDB Scala 100

Data Engineering Podcast

NOVEMBER 13, 2022

To make that possible they need a reliable data platform that empowers all of the organization’s stakeholders. In this episode Vishnu Venkataraman shares the journey that he and his team have taken to build and evolve their systems and improve the product offerings that they are able to support.

MongoDB 100

MongoDB Scala Google Cloud MySQL 100

Data Engineering Podcast

OCTOBER 16, 2022

Summary The "data lakehouse" architecture balances the scalability and flexibility of data lakes with the ease of use and transaction support of data warehouses. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability.

Data Lake 100

Data Lake Food MongoDB Scala 100

Ascend.io

AUGUST 24, 2023

In recent years, the data space has transformed significantly. Advanced tools and platforms are now taking away the cumbersome tasks of managing outdated architectures and intricate codebases. Instead, their true merit lies in maximizing impacts and steering tangible outcomes for their organization with respect to data.

Engineering 52

Engineering Data Pipeline Data Ingestion Data 52

Databand.ai

JUNE 28, 2023

“Observability” has become a bit of a buzzword so it’s probably best to define it: Data observability is the blanket term for monitoring and improving the health of data within applications and systems like data pipelines. Data observability vs. monitoring: what is the difference?

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Knowledge Hut

MARCH 19, 2024

It allows businesses to construct event-driven architectures and microservices in which functions are invoked by events like file uploads, database changes, or HTTP requests. Lambda usage includes real-time data processing, communication with IoT devices, and execution of automated tasks.

AWS 52

AWS Cloud Computing Amazon Web Services Relational Database 52

Cloudera

APRIL 20, 2021

Yet, the information will always delay if they leverage an analytics system built for the past. It can access data from inside the business, like ERP and asset management, outside sources, like edge devices and external assets, and correlate them for real-time predictive maintenance. What is modern streaming architecture?

Hospitality 92

Hospitality Kafka Retail Data Ingestion 92

Ascend.io

JANUARY 2, 2024

These are the interfaces where the pipeline taps into various systems to acquire data. The sources of data can be incredibly diverse, ranging from data warehouses, relational databases, and web analytics to CRM platforms, social media tools, and IoT device sensors.

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

LinkedIn Engineering

OCTOBER 19, 2023

To enable the ingestion and real-time processing of enormous volumes of data, LinkedIn built a custom stream processing ecosystem largely with tools developed in-house (and subsequently open-sourced). In 2010, they introduced Apache Kafka , a pivotal Big Data ingestion backbone for LinkedIn’s real-time infrastructure.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

Towards Data Science

DECEMBER 1, 2023

Technical Overview The project architecture is depicted as follows: Google Calendar -> Fivetran -> Snowflake -> dbt -> Snowflake Dashboard , with GitHub Actions orchestrating the deployment. Now you can easily retrieve it from your account by leveraging “data movement platforms” like Fivetran. See Github repo.

Data Engineering 73

Data Engineering Data Engineer Project Engineering 73

ProjectPro

FEBRUARY 6, 2023

With over 10 million active subscriptions, 50 million active topics, and a trillion messages processed per day, Google Cloud Pub/Sub makes it easy to build and manage complex event-driven systems. Google Cloud Pub/Sub is a global, cloud-based messaging framework that has become increasingly popular among data engineers over recent years.

Google Cloud 52

Google Cloud Cloud Cloud Storage Data Ingestion 52

Monte Carlo

FEBRUARY 20, 2024

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder. Fivetran Image courtesy of Fivetran.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

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 Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Knowledge Hut

APRIL 23, 2024

For example, in 1880, the US Census Bureau needed to handle the 1880 Census data. They realized that compiling this data and converting it into information would take over 10 years without an efficient system. Thus, it is no wonder that the origin of big data is a topic many big data professionals like to explore.

Big Data 52

Big Data Amazon Web Services Media Cloud Computing 52

Data Engineering Podcast

JULY 10, 2022

In this episode Chris Riccomini shares his experiences building and scaling data operations at WePay and LinkedIn, as well as the lessons he has learned working with other teams as they automated their own systems. What are the most interesting, innovative, or unexpected ways that you have seen automation of data operations used?

Data Engineering 100

Data Engineering Data Engineer Engineering MongoDB 100

Data Engineering Podcast

JULY 3, 2022

In order to quickly identify if and how two data systems are out of sync Gleb Mezhanskiy and Simon Eskildsen partnered to create the open source data-diff utility. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability.

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

AUGUST 6, 2022

Summary The optimal format for storage and retrieval of data is dependent on how it is going to be used. For analytical systems there are decades of investment in data warehouses and various modeling techniques. What are the primary system requirements that have influenced the design choices?

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Podcast

AUGUST 13, 2022

The biggest challenge with modern data systems is understanding what data you have, where it is located, and who is using it. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Sifflet also offers a 2-week free trial.

Metadata 100

Metadata MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 2, 2022

Summary Data lineage is something that has grown from a convenient feature to a critical need as data systems have grown in scale, complexity, and centrality to business. Alvin is a platform that aims to provide a low effort solution for data lineage capabilities focused on simplifying the work of data engineers.

IT 100

IT Food PostgreSQL MongoDB 100

Data Engineering Podcast

OCTOBER 30, 2022

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java.

Engineering 100

Engineering MongoDB Scala MySQL 100

Cloudera

FEBRUARY 8, 2021

As advanced use cases, like advanced driver assistance systems featuring lane change departure detection, advanced vehicle diagnostics, or predictive maintenance move forward, the existing infrastructure of the connected car is being stressed. billion in 2019, and is projected to reach $225.16 billion by 2027, registering a CAGR of 17.1%

Manufacturing 106

Manufacturing Machine Learning Data Ingestion Electronics 106

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52