Data Engineering Podcast

DECEMBER 11, 2022

Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows. Their SDKs make event streaming from any app or website easy, and their extensive library of integrations enable you to automatically send data to hundreds of downstream tools.

Database 100

Database MySQL Data Lake MongoDB 100

Data Engineering Podcast

SEPTEMBER 25, 2022

Summary Data integration from source systems to their downstream destinations is the foundational step for any data product. In this episode Mark Van de Wiel explains how they integrated CDC functionality into their existing product, discusses the nuances of different approaches to change data capture from various sources.

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

MAY 10, 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. Sound exciting?

PostgreSQL 100

PostgreSQL Data Warehouse Data Pipeline Kafka 100

Booking.com Engineering

DECEMBER 2, 2022

To help people discover destinations, we are a leading travel advertiser on Google Pay Per Click (PPC). We make extensive use of Google BigQuery in PPC due to the scale of our business (up to 2 million room nights booked per day). BigQuery also offers native support for nested and repeated data schema[4][5].

Systems 52

Systems Cloud MySQL Relational Database 52

Data Engineering Podcast

FEBRUARY 22, 2021

Summary Data integration is a critical piece of every data pipeline, yet it is still far from being a solved problem. There are a number of managed platforms available, but the list of options for an open source system that supports a large variety of sources and destinations is still embarrasingly short.

Data Integration 100

Data Integration Data Warehouse Data Pipeline BI 100

Striim

FEBRUARY 10, 2023

Striim is a data integration platform that connects data from different applications and services to deliver real-time data analytics. is one of America’s largest retailers, delivering quality fashion to customers in more than 100 international destinations through the leading e-commerce site macys.com. Macy’s, Inc.

Data Analytics 52

Data Analytics Telecommunication Insurance Google Cloud 52

Data Engineering Podcast

MARCH 8, 2021

This introduces challenges such as keeping information synchronized, managing schema evolution, building transformations to match the expectations of the destination systems. Datafold integrates with all major data warehouses as well as frameworks such as Airflow & dbt and seamlessly plugs into CI workflows.

IT 100

IT Data Warehouse MongoDB Kafka 100

dbt Developer Hub

JANUARY 14, 2023

After an initial round of transformation (described in the next section), the deduplicated data is loaded into BigQuery where I can query it from the Google Sheets client and manually review the deduplication. dlt integrates well with dbt and enables fast and simple data ingestion, making this project simpler than I thought it would be.

Data Ingestion 52

Data Ingestion Google Cloud Python Cloud 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. With our new partnership and updated integration, Monte Carlo provides full, end-to-end coverage across data lake and lakehouse environments powered by Databricks.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Christophe Blefari

MARCH 2, 2024

Extract and load, still unsolved 🤭 I've started writing data pipelines in 2014 and the movement from sources to destinations has always been one of the most discussed topic in my data engineering spaces. In 2024 we are more than ever tools to move data from sources to destinations. But the field has taken a new direction.

Data 162

Data Python Database BI 162

Monte Carlo

AUGUST 31, 2023

With Captain Robert Falcon Scott and other early Antarctic explorers, poor data quality (or rather, data-uninformed decision making) led them to inaccurately forecast where and how long it would take to get to the South Pole, their target destination. There are several in more recent memory that stick out, too.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

dbt Developer Hub

MARCH 9, 2023

At Teads, we’ve been using BigQuery (BQ) to build our analytics stack since 2017. We built an internal SQL query executor tool to wrap the execution of our BigQuery jobs while dbt Labs (formerly known as Fishtown Analytics) was creating its own product: dbt. This is also the approach used by the dbt BigQuery connector.

SQL 59

SQL Designing Building IT 59

Snowflake

JANUARY 29, 2024

Imagine seamlessly integrating your Google Analytics data with Snowflake, allowing you to combine it effortlessly with other key sources like CRM, ERP, social media metrics, email campaign data, and whatever data sources compose the full scope of your data estate.

Raw Data 103

Raw Data Aggregated Data Data Government 103

Monte Carlo

FEBRUARY 20, 2024

Consideration What to Look For Integration Capabilities Support for a diverse array of data sources and destinations, ensuring compatibility with your data ecosystem. Integrations : They offer a wide array of connectors for databases, SaaS applications, cloud storage solutions, and more, covering both popular and niche data sources.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Monte Carlo

JUNE 14, 2023

For example, data may be extracted from multiple sources, reorganized, and joined at different times before ultimately being served to its final destination. At the moment, this tight integration is possible because most zero-ETL architectures require both the transactional database and data warehouse to be from the same cloud provider.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Ascend.io

MAY 8, 2023

For example, by selecting the aggregation strategy at any of the ingestion steps, you control how new records are integrated into existing partitions. Choosing Data Planes Each data plane (BigQuery, Databricks, and Snowflake) has its distinct cost and performance profiles for different types of workloads.

Data Pipeline 52

Data Pipeline Data Ingestion Metadata Data 52

dbt Developer Hub

NOVEMBER 28, 2021

Then I'll show you how I track engagement across Slack, GitHub, Docker Hub, and PyPI, using a warehouse built with BigQuery, dbt, OpenLineage and Superset. Here are the tools I chose to use: Google Bigquery acts as the main database, holding all the source data, intermediate models, and data marts.

Raw Data 52

Raw Data Metadata Datasets Database 52

AltexSoft

DECEMBER 23, 2022

Integrating data from numerous, disjointed sources and processing it to provide context provides both opportunities and challenges. One of the ways to overcome challenges and gain more opportunities in terms of data integration is to build an ELT (Extract, Load, Transform) pipeline. Data engineering in 14 minutes. What is ELT?

Process 52

Process Building Raw Data Data Lake 52

Data Engineering Podcast

JUNE 17, 2018

With their monitoring, metrics, and log collection agent, including extensive integrations and distributed tracing, you’ll have everything you need to find and fix performance bottlenecks in no time. How do you ensure the integrity and accuracy of that information? How do you ensure the integrity and accuracy of that information?

Scala 100

Scala Kafka SQL Architecture 100

Data Engineering Podcast

MARCH 4, 2019

In this interview Segment CTO and co-founder Calvin French-Owen explains how the company got started, how it manages to multiplex data streams from multiple sources to multiple destinations, and how it can simplify your work of gaining visibility into how your customers are engaging with your business.

Google Cloud 100

Google Cloud Kafka Media Data Warehouse 100

Monte Carlo

MARCH 14, 2023

Data ingestion works by transferring data from a variety of sources into a single common destination, where data orchestrators can then analyze it. a new transaction, an updated stock price, a power outage alert) to the destination data cloud without disrupting the database workload.

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Grouparoo

OCTOBER 21, 2021

Data synchronization is often confused with data integration. Integration refers to combining multiple data sources to form new information or insights to fuel business decisions. Having a data stack that reliably syncs data from your sources to your destinations enables powerful operational analytics and business intelligence.

Data Warehouse 52

Data Warehouse Data MySQL Cloud 52

Ascend.io

DECEMBER 21, 2022

Cloud data warehouses, such as Snowflake and BigQuery, have made it simpler than ever to combine all of your data into one location. As we hinted at in the introduction, reverse ETL stands on the shoulders of two data integration techniques: ETL and ELT. The last three years have seen a remarkable change in data infrastructure.

ETL Tools 52

ETL Tools ETL System Data Warehouse Data Consolidation 52

AltexSoft

OCTOBER 8, 2021

The good news is, businesses can choose the path of data integration to make the most out of the available information. The bad news is, integrating data can become a tedious task, especially when done manually. Data integration in a nutshell. Data integration process. So, why is data integration such a big deal?

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

AUGUST 24, 2021

Source Code: Aviation Data Analysis using Big Data Tools 3) Shipping and Distribution Demand Forecasting This one of the best data engineering projects for beginners and it uses historical demand data to forecast demand for the future across various customers, products, and destinations.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

NOVEMBER 7, 2022

The approach finds its application, for example, in ETL and ELT pipelines with many data sources or destinations. A large number of hooks: extensibility and simple integrations. If the target system has an API, you can always integrate it with Airflow. The most common applications of the platform are. Since the 2.0

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

AltexSoft

OCTOBER 21, 2022

Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time. In other words, Kafka can serve as a messaging system, commit log, data integration tool, and stream processing platform. Kafka Connect for simple integration. What is Kafka?

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

ProjectPro

MAY 31, 2021

And even if you’re not very active on social media, I’m sure you now and then check your phone before leaving the house to see what the traffic is like on your route to know how long it could take you to reach your destination. None of this would have been possible without the application of big data.

Big Data 52

Big Data Coding Project Hadoop 52

Monte Carlo

AUGUST 19, 2023

By integrating tools from a variety of vendors, a data platform enables a data engineering team to not only manage an organization’s data but also activate it for a domain’s use cases. Microsoft Azure – Microsoft’s cloud computing entrant in this list common among teams that leverage heavy Windows integrations.

Building 52

Building BI Data Lake Data Governance 52

Monte Carlo

MAY 17, 2023

Flag System Authorization And Integration Failures Mitigate Risk of Code Failures 10. Integrate Data Stacks Post Merger 35. In fact, director of data engineering, Daniel Rimon, and her team were managing more than 30,000 BigQuery tables alongside complex data pipelines. Prevent, Detect, Resolve Data Volume Issues 7.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Flag System Authorization And Integration Failures Mitigate Risk of Code Failures 10. Integrate Data Stacks Post Merger 35. In fact, director of data engineering, Daniel Rimon, and her team were managing more than 30,000 BigQuery tables alongside complex data pipelines. Prevent, detect, resolve data volume issues 7.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52