François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. As you can see, this is in the code part where you are building your data pipelines, a misnomer because this is an over simplification. ” He/She is managing triggers, he/she needs to check conditions (event type ?

Architecture 130

Architecture Technology Google Cloud Metadata 130

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. Their SDKs make event streaming from any app or website easy, and their state-of-the-art reverse ETL pipelines enable you to send enriched data to any cloud tool.

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

SEPTEMBER 11, 2022

Instead of trapping data in a black box, they enable you to easily collect customer data from the entire stack and build an identity graph on your warehouse, giving you full visibility and control. If you’re a data engineering podcast listener, you get credits worth $5,000 when you become a customer.

Data Pipeline 130

Data Pipeline Building MongoDB Scala 130

Data Engineering Podcast

OCTOBER 19, 2020

For more opportunities to stay up to date, gain new skills, and learn from your peers there are a growing number of virtual events that you can attend from the comfort and safety of your home. Go to dataengineeringpodcast.com/conferences to check out the upcoming events being offered by our partners and get registered today!

Machine Learning 100

Machine Learning Data Engineering Data Engineer Data 100

Data Engineering Podcast

AUGUST 5, 2019

Finding the data that you need is tricky, and Amundsen will help you solve that problem. And as your data grows in volume and complexity, there are foundational principles that you can follow to keep data workflows streamlined. Finding the data that you need is tricky, and Amundsen will help you solve that problem.

PostgreSQL 100

PostgreSQL MongoDB Metadata Media 100

Data Engineering Podcast

OCTOBER 15, 2021

What are the available events that can be used to trigger actions? What are some of the challenges that teams are facing when integrating metadata management and analysis into their data workflows? What are the available events that can be used to trigger actions?

Metadata 100

Metadata BI Data Warehouse Government 100

Monte Carlo

FEBRUARY 8, 2024

Here are some strategies to keep things firing on all cylinders: Parallelize data processing: Divide large data tasks into smaller, manageable chunks that can be processed concurrently. Identify parts of your data workflow that can be parallelized and adjust your pipeline configuration accordingly.

Data Pipeline 52

Data Pipeline AWS Datasets Data 52

Databand.ai

AUGUST 30, 2023

One key aspect of data orchestration is the automation of data pipeline tasks. By automating repetitive tasks, such as data extraction, transformation, and loading (ETL), organizations can streamline their data workflows and reduce the risk of human error.

Data Governance 52

Data Governance Data Pipeline Government Data Cleanse 52

Cloudera

AUGUST 21, 2020

For example, if a credit card was used in the United States and shortly afterward the same card was used in Spain to withdraw the same amount, these two events in isolation could appear legitimate. However, in the context of time and geography, these two events point to a pattern of fraud.

Banking 60

Banking Kafka Cloud Storage Government 60

Knowledge Hut

NOVEMBER 2, 2023

Multi-cloud Data Integration and Orchestration with Azure Data Factory Utilizing Azure Data Factory, develop a method for integrating and managing data workflows across several cloud platforms (such as AWS, GCP), facilitating smooth data transformation and migration.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Data Engineering Podcast

FEBRUARY 18, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 262

Data Lake High Quality Data Data Warehouse Google Cloud 262

Data Engineering Podcast

MARCH 17, 2024

Summary A significant portion of data workflows involve storing and processing information in database engines. In this episode Gleb Mezhanskiy, founder and CEO of Datafold, discusses the different error conditions and solutions that you need to know about to ensure the accuracy of your data. Data lakes are notoriously complex.

Database 147

Database Data Lake High Quality Data Data Workflow 147

Hepta Analytics

FEBRUARY 14, 2022

Disadvantages of a data lake are: Can easily become a data swamp data has no versioning Same data with incompatible schemas is a problem without versioning Has no metadata associated It is difficult to join the data Data warehouse stores processed data, mostly structured data.

Data Ingestion 52

Data Ingestion Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

MARCH 3, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Programming 162

Programming Data Lake High Quality Data Data Pipeline 162

Data Engineering Podcast

FEBRUARY 25, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Database 162

Database Technology Data Lake High Quality Data 162

Data Engineering Podcast

MARCH 10, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 147

Data Lake High Quality Data Data Pipeline Architecture 147

Monte Carlo

SEPTEMBER 20, 2022

Here’s how Prefect , Series B startup and creator of the popular data orchestration tool, harnessed the power of data observability to preserve headcount, improve data quality and reduce time to detection and resolution for data incidents.

Big Data 52

Big Data Data Warehouse Data Data Governance 52

Data Engineering Podcast

DECEMBER 24, 2023

Summary Kafka has become a ubiquitous technology, offering a simple method for coordinating events and data across different systems. Data lakes are notoriously complex. In the event of these different cluster errors, what are the strategies for mitigating and recovering from those failures?

Kafka 245

Kafka Data Lake High Quality Data SQL 245

Data Engineering Podcast

MARCH 24, 2024

Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics.

Data Lake 162

Data Lake High Quality Data Hadoop Data Pipeline 162

Data Engineering Podcast

JANUARY 28, 2024

Summary Monitoring and auditing IT systems for security events requires the ability to quickly analyze massive volumes of unstructured log data. Cliff Crosland co-founded Scanner to provide fast querying of high scale log data for security auditing.

Data Lake 147

Data Lake Building High Quality Data AWS 147

Data Engineering Podcast

NOVEMBER 26, 2023

Developing event-driven pipelines is going to be a lot easier - Meet Functions! Data lakes are notoriously complex. Memphis Logo]([link] Developing event-driven pipelines is going to be a lot easier - Meet Functions! Developing event-driven pipelines is going to be a lot easier - Meet Functions!

Architecture 147

Architecture Data Lake High Quality Data SQL 147

Data Engineering Podcast

SEPTEMBER 17, 2023

what are the characteristics that distinguish a knowledge graph from What are the layers/stages of applications and data that can/should incorporate JSON-LD as the representation for records and events? What is the level of native support/compatibiliity that you see for JSON-LD in data systems? When is JSON-LD the wrong choice?

Building 189

Building BI SQL Python 189

Ascend.io

DECEMBER 11, 2023

This contrasts with data pipeline orchestration , which adopts a narrower focus, centering on the construction, operation, and management of data pipelines. Data pipeline orchestration is characterized by a detailed understanding of pipeline events and processes. So, why is data orchestration a big deal?

Data Workflow 52

Data Workflow Data Pipeline Data Lake Data 52

Data Engineering Podcast

JUNE 1, 2021

It builds your customer data warehouse and your identity graph on your data warehouse, with support for Snowflake, Google BigQuery, Amazon Redshift, and more. Their SDKs and plugins make event streaming easy, and their integrations with cloud applications like Salesforce and ZenDesk help you go beyond event streaming.

Data Pipeline 100

Data Pipeline Data Warehouse Data Workflow Data 100

Data Engineering Podcast

OCTOBER 29, 2021

How does Narrator fit within the data workflows of an organization? Contact Info LinkedIn @ae4ai on Twitter Parting Question From your perspective, what is the biggest gap in the tooling or technology for data management today? How does Narrator fit within the data workflows of an organization?

Data Warehouse 100

Data Warehouse BI Data Workflow Data Pipeline 100

Monte Carlo

APRIL 24, 2023

The first is referred to as “events” data, which consists of clickstream events, logs, and other user activity events; while the second type— known as “transactional” data—captures all the upstream services. The scale of data events depends entirely on the product.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Data Engineering Weekly

JANUARY 15, 2023

. 🎯 I defined the modern data stack sometime back as; @sarahmk125 MDS is a set of vendor tools that solve niche data problems (lineage, orchestration, quality) with the side effect of creating a disjointed data workflow that makes data folks lives more complicated.","username":"ananthdurai","name":"at-ananth-at-data-folks

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

dbt Developer Hub

OCTOBER 14, 2021

Anna (dbt Labs Director of Community), does a phenomenal job connecting this week's events in the latest issue of the Analytics Engineering Roundup. Modeling behavioral data with Snowplow and dbt (coming up on 10/27). How Blend Eliminated Data Silos with dbt and Hightouch. Things to Watch ? Luckily you still can!

Metadata 52

Metadata BI Software Engineer Software Engineering 52

Monte Carlo

NOVEMBER 14, 2023

But even as the modern data stack continues to evolve, Airflow maintains its title as a perennial data orchestration favorite—and for good reason. This data orchestration tool manages task orchestration, cluster management, monitoring, and error reporting.

Pipeline-centric 40

Pipeline-centric Google Cloud Data Workflow Python 40

Netflix Tech

OCTOBER 18, 2022

With the high growth of workflows in the past few years?—?increasing increasing at > 100% a year, the need for a scalable data workflow orchestrator has become paramount for Netflix’s business needs. For example, the daily workflow should process the data when the data partition is ready, not always at midnight.

Java 81

Java Data Machine Learning Systems 81

Netflix Tech

NOVEMBER 20, 2023

This enables auto propagation of backfill data in multi-stage pipelines. Netflix Maestro Maestro is the Netflix data workflow orchestration platform built to meet the current and future needs of Netflix. Basically, the range derived from the change data indicates the dataset to be re-processed.

Process 84

Process Data Pipeline Datasets SQL 84

DataKitchen

OCTOBER 25, 2022

The journey reveals all of the complex steps, toolchains, and actions within the data workflow?most For example, in a single data pipeline, you might have some FTP file sources that you ingest into S3 buckets. The journey tracks all levels of the stack from data to tools to code to tests across all critical dimensions.

Data Pipeline 52

Data Pipeline Data Workflow Coding Building 52

Ripple Engineering

MAY 27, 2021

Using the open source version of DBT, the Data Engineering team aimed to equip Ripple’s analysts with a tool that cleans data and reduces the amount of time spent manually performing checks. Internally, we capture the raw application events in real time in our data lake on BigQuery.  This

Building 52

Building Raw Data SQL Data 52

AltexSoft

SEPTEMBER 21, 2023

The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization. Analysis of logs, metrics, and security events. Real-time behavior modeling with ML.

Engineering 52

Engineering NoSQL Programming Language Java 52

AltexSoft

NOVEMBER 7, 2022

DevOps tasks — for example, creating scheduled backups and restoring data from them. Airflow is especially useful for orchestrating Big Data workflows. Airflow is not a data processing tool by itself but rather an instrument to manage multiple components of data processing. When Airflow won’t work. Since the 2.0

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

Netflix Tech

FEBRUARY 9, 2022

More commonly, teams will opt to do more testing to try and catch regressions before deploying to production and will accept the extra burden of rebuilding all of their workflow dependencies in the event of a regression.

Data Pipeline 80

Data Pipeline Scala Management Python 80

Monte Carlo

JUNE 14, 2023

Airbyte – An open source platform that easily allows you to sync data from applications. Data streaming ingestion solutions include: Apache Kafka – Confluent is the vendor that supports Kafka, the open source event streaming platform to handle streaming analytics and data ingestion.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52