Snowflake

OCTOBER 16, 2024

The company quickly realized maintaining 10 years’ worth of production data while enabling real-time data ingestion led to an unscalable situation that would have necessitated a data lake. Snowflake's separate clusters for ETL, reporting and data science eliminated resource contention.

Digital Media 81

Digital Media Media Data Lake Data Warehouse 81

Rockset

JULY 28, 2022

As capable as it is, there are still instances where MongoDB alone can't satisfy all of the requirements for an application, so getting a copy of the data into another platform via a change data capture (CDC) solution is required. Debezium It is also possible to capture MongoDB change data capture events using Debezium.

MongoDB 52

MongoDB Kafka NoSQL Data Lake 52

Data Engineering Weekly

APRIL 21, 2024

link] RevenueCat: How we solved RevenueCat’s biggest challenges on data ingestion into Snowflake A common design feature of modern data lakes and warehouses is that Inserts and deletes are fast, but the cost of scattered updates grows linearly with the table size.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

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 Engineer 130

Data Engineer Data Engineering 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

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 99

Data Architecture Architecture Hadoop Data Warehouse 99

Snowflake

JUNE 4, 2024

This includes pipelines and transformations with Snowpark, Streams, Tasks and Dynamic Tables (public preview soon); extending AI and ML to Iceberg with Snowflake Cortex AI; performing storage maintenance with capabilities like automatic clustering and compaction; as well as securely collaborating on live data shares.

Government 84

Government Data Ingestion Data PostgreSQL 84

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

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

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 Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

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 Engineer 52

Data Engineer Data Engineering Project Coding 52

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

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

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

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

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

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

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 94

Google Cloud Cloud Amazon Web Services Cloud Storage 94

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.

Transportation 52

Transportation Scala Kafka Data Lake 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 83

Banking Data Ingestion Kafka Data Lake 83

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

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 73

Data Ingestion Retail Kafka Data Lake 73

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 Engineer 52

Data Engineer Data Engineering Engineering Data Warehouse 52

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 82

Database Machine Learning Kafka Aggregated Data 82

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

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 Engineer 98

Data Engineer Data Engineering Coding Project 98

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 Engineer 52

Data Engineer Data Engineering Coding Project 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 Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Cloudera

AUGUST 21, 2020

Over time, additional use cases and functions expanded from original EDW and Data Lake related functions to support increasing demands from the business. More sources, data, and functionality were added to these platforms, expanding their value but adding to the complexity, such as: Streaming data ingestion. .

Hadoop 76

Hadoop Big Data Cloud Kafka 76

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 Python Government 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 SQL BI Hadoop 21

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 SQL 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