Christophe Blefari

JANUARY 20, 2024

The main difference between both is the fact that your computation resides in your warehouse with SQL rather than outside with a programming language loading data in memory. In this category I recommend also to have a look at data ingestion (Airbyte, Fivetran, etc.), Understand Change Data Capture — CDC.

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. A visualization of the flow of data in data lakehouse architecture vs. data warehouse and data lake.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. A visualization of the flow of data in data lakehouse architecture vs. data warehouse and data lake.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Data Engineering Weekly

MARCH 24, 2024

The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems. As we predicted in the key trends of 2023 about Apache Flink as a clear winner in the stream processing frameworks, we see Confluent offering Flink as a service.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Christophe Blefari

MARCH 4, 2023

Data ingestion pipeline with Operation Management — At Netflix they annotate video which can lead to thousand of annotation but they need to manage the annotation lifecycle each time the annotation algorithm runs. Some company also call it a lakehouse or a data lake, but the word shift is enough interesting to notice.

Machine Learning 130

Machine Learning AWS Data Data Lake 130

Snowflake

SEPTEMBER 14, 2023

Unbound by the limitations of a legacy on-premises solution, its multi-cluster shared data architecture separates compute from storage, allowing data teams to easily scale up and down based on their needs. With Snowflake’s Kafka connector, the technology team can ingest tokenized data as JSON into tables as VARIANT.

Data Architecture 95

Data Architecture Architecture Hadoop Data Warehouse 95

Knowledge Hut

NOVEMBER 2, 2023

Top 10 Azure Data Engineering Project Ideas for Beginners For beginners looking to gain practical experience in Azure Data Engineering, here are 10 Azure Data engineer real time projects ideas that cover various aspects of data processing, storage, analysis, and visualization using Azure services: 1.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

SEPTEMBER 26, 2023

Born out of the minds behind Apache Spark, an open-source distributed computing framework, Databricks is designed to simplify and accelerate data processing, data engineering, machine learning, and collaborative analytics tasks. This flexibility allows organizations to ingest data from virtually anywhere.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. It is also crucial to have experience with data ingestion and transformation.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Data Engineering Podcast

SEPTEMBER 25, 2022

Mention the podcast to get a free "In Data We Trust World Tour" t-shirt. RudderStack helps you build a customer data platform on your warehouse or data lake. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. In fact, while only 3.5%

Food 100

Food MongoDB Scala MySQL 100

Monte Carlo

APRIL 24, 2023

In this article, we’ll dive deep into the data presentation layers of the data stack to consider how scale impacts our build versus buy decisions, and how we can thoughtfully apply our five considerations at various points in our platform’s maturity to find the right mix of components for our organizations unique business needs.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Data Engineering Podcast

SEPTEMBER 11, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. 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. In fact, while only 3.5%

Data Pipeline 130

Data Pipeline Building MongoDB Scala 130

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Data Engineering Podcast

AUGUST 6, 2022

RudderStack helps you build a customer data platform on your warehouse or data lake. 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. In fact, while only 3.5%

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Knowledge Hut

MARCH 28, 2024

Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Snowflake

AUGUST 16, 2023

That’s why we built Snowpipe Streaming, now generally available to handle row-set data ingestion. The new Kafka connector, built with Snowpipe Streaming , now supports schema detection and evolution. Snowpipe streaming supports both database replication and group-based replication. Learn more here.

Scala 52

Scala Transportation Kafka Data Lake 52

Rockset

NOVEMBER 6, 2019

With event-driven architectures powered by systems like Apache Kafka becoming more prominent, there are now many applications in the modern software stack that make use of events and messages to operate effectively. Types of Event Data Applications emit events that correspond to important actions or state changes in their context.

Kafka 40

Kafka Data Lake SQL Hadoop 40

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? With companies moving their data platforms to the cloud, the emergence of cloud-native solutions ( data warehouse vs data lake or even a data lakehouse ) have taken over the market, offering more accessible and affordable options for storing data relative to many on-premises solutions.

Building 52

Building BI Data Lake Data Governance 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

AUGUST 26, 2020

All of these happen continuously and repetitively on a daily basis, amounting to petabytes worth of information and data. This requires massive amounts of data ingestion, messaging, and processing within a data-in-motion context. From a data ingestion standpoint, NiFi is designed for this purpose.

Banking 80

Banking Data Ingestion Kafka Data Lake 80

Cloudera

FEBRUARY 16, 2021

In the following sections, we see how the Cloudera Operational Database is integrated with other services within CDP that provide unified governance and security, data ingest capabilities, and expand compatibility with Cloudera Runtime components to cater to your specific use cases. . Integrated across the Enterprise Data Lifecycle .

Database 81

Database Machine Learning Data Lake Kafka 81

Knowledge Hut

JUNE 26, 2023

If you are struggling with Data Engineering projects for beginners, then Data Engineer Bootcamp is for you. Some simple beginner Data Engineer projects that might help you go forward professionally are provided below. Source Code: Stock and Twitter Data Extraction Using Python, Kafka, and Spark 2.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

SQL 52

SQL Kafka MongoDB MySQL 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Silectis

JANUARY 3, 2021

Data engineers design, build, and maintain data pipelines that transform data from a raw state to a useful one, ready for analysis or data science modeling. Data Integration Combining data from various, disparate sources into one unified view. HDFS stands for Hadoop Distributed File System.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

JUNE 14, 2022

Iceberg brings the reliability and simplicity of SQL tables to big data, while making it possible for engines like Apache Spark, Trino, Flink, Presto, and Hive to safely work with the same tables, at the same time. Christian then announced a new way to ingest data in Snowflake: Snowpipe streaming.

Cloud 52

Cloud Data Ingestion Government Python 52

Rockset

MARCH 27, 2023

Stream processing tools manipulate streaming data as it flows through a streaming data platform (Kafka being one of the most popular options, but there are others). This processing happens incrementally, as the streaming data arrives. But Where Will My Data Live? So do you need just one? Let’s get into the details.

Database 52

Database Process Scala SQL 52

Rockset

NOVEMBER 28, 2022

First, CDC theoretically allows companies to analyze and react to data in real time, as it’s generated. It works with existing streaming systems like Apache Kafka, Amazon Kinesis, and Azure Events Hubs, making it easier than ever to build a real-time data pipeline. This method offers a few enormous advantages over batch updates.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 52

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. However, Apache Kafka is more than just messaging. Some Kafka and Rockset users have also built real-time e-commerce applications , for example, using Rockset’s Java, Node.js

Kafka 21

Kafka BI SQL Datasets 21

ProjectPro

FEBRUARY 21, 2023

Must be familiar with data architecture, data warehousing, parallel processing concepts, etc. Proficient in building data processing solutions using Azure Data Factory , Azure Synapse Analytics , Azure Data Lake Storage, Azure Databricks , etc.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 82

Engineering Raw Data Data Science Scala 82

ProjectPro

NOVEMBER 15, 2021

Apache Zeppelin Source: Github Apache Zeppelin is a multi-purpose notebook that supports Data Ingestion, Data Discovery, Data Analytics , Data Visualization , and Data Collaboration. CMAK is developed to help the Kafka community. To learn more about the recent updates and contribute: [link] 8.

Big Data 52

Big Data Project Metadata Programming Language 52

phData: Data Engineering

JANUARY 3, 2022

In years past, some companies may have tried to create this report within Excel, having multiple business analysts and engineers contribute to data extraction and manipulation. Once the data has been collected from each system, a data engineer can determine how to optimally join the data sets.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

Cloudera

MARCH 31, 2021

Customers who have chosen Google Cloud as their cloud platform can now use CDP Public Cloud to create secure governed data lakes in their own cloud accounts and deliver security, compliance and metadata management across multiple compute clusters. Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 90

Google Cloud Cloud Amazon Web Services Cloud Storage 90

Cloudera

FEBRUARY 4, 2019

Cloudera DataFlow (CDF) is a scalable, real-time streaming data platform that collects, curates, and analyzes data so customers gain key insights for immediate actionable intelligence. CDF, as an end-to-end streaming data platform, emerges as a clear solution for managing data from the edge all the way to the enterprise.

Data Ingestion 72

Data Ingestion Retail Kafka Data Lake 72

phData: Data Engineering

JANUARY 3, 2022

One of our customers needed the ability to export/import data between systems and create data products from this source data. This required applying transformations and filters to the data for various business units. The data was being stored in their data lake (AWS S3) and within their data warehouse (AWS Redshift).

IT 52

IT AWS Software Engineer Software Engineering 52