Monte Carlo

MARCH 14, 2023

Data ingestion is the process of collecting data from various sources and moving it to your data warehouse or lake for processing and analysis. It is the first step in modern data management workflows. Table of Contents What is Data Ingestion?

Data Ingestion 52

Data Ingestion Data Warehouse Lambda Architecture Raw Data 52

Knowledge Hut

JULY 3, 2023

Conventional batch processing techniques seem incomplete in fulfilling the demand of driving the commercial environment. This is where real-time data ingestion comes into the picture. Data is collected from various sources such as social media feeds, website interactions, log files and processing.

Data Ingestion 52

Data Ingestion Google Cloud Pipeline-centric Media 52

Rockset

MARCH 1, 2023

When you deconstruct the core database architecture, deep in the heart of it you will find a single component that is performing two distinct competing functions: real-time data ingestion and query serving. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky.

Data Ingestion 144

Data Ingestion Database Architecture SQL 144

Databand.ai

JULY 19, 2023

Complete Guide to Data Ingestion: Types, Process, and Best Practices Helen Soloveichik July 19, 2023 What Is Data Ingestion? Data Ingestion is the process of obtaining, importing, and processing data for later use or storage in a database.

Data Ingestion 52

Data Ingestion Process Data Cleanse Data Governance 52

Snowflake

APRIL 9, 2025

It employs Snowpark Container Services to build scalable AI/ML models for satellite data processing and Snowflake AI/ML functions to enable advanced analytics and predictive insights for satellite operators.

Pharmaceutical 98

Pharmaceutical Manufacturing Data Ingestion SQL 98

Team Data Science

MAY 10, 2020

I can now begin drafting my data ingestion/ streaming pipeline without being overwhelmed. With careful consideration and learning about your market, the choices you need to make become narrower and more clear. I'll use Python and Spark because they are the top 2 requested skills in Toronto.

Data Pipeline 130

Data Pipeline Data Ingestion AWS Kafka 130

Data Engineering Weekly

MARCH 23, 2025

The author emphasizes the importance of mastering state management, understanding "local first" data processing (prioritizing single-node solutions before distributed systems), and leveraging an asset graph approach for data pipelines. link] Grab: Improving Hugo's stability and addressing oncall challenges through automation.

Data Engineer 62

Data Engineer Data Engineering Engineering Data 62

phData: Data Engineering

FEBRUARY 21, 2025

On-prem data warehouses can provide lower latency solutions for critical applications that require high performance and low latency. Many companies may choose an on-prem data warehousing solution for quicker data processing to enable business decisions. Data integrations and pipelines can also impact latency.

Cloud 52

Cloud Data Warehouse Amazon Web Services Data Ingestion 52

Snowflake

MARCH 14, 2024

Customers can process changed data once or twice a day — or at whatever cadence they prefer — to the main table. SNP has been able to provide customers with a 10x cost reduction in Snowflake data processing associated with SAP data ingestion.

IT 121

IT Data Ingestion Data AWS 121

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. Core Digital Media’s BI team began evaluating infrastructure enhancements.

Digital Media 105

Digital Media Media Data Lake Data Warehouse 105

Ascend.io

OCTOBER 28, 2024

Tools like Python’s requests library or ETL/ELT tools can facilitate data enrichment by automating the retrieval and merging of external data. Read More: Discover how to build a data pipeline in 6 steps Data Integration Data integration involves combining data from different sources into a single, unified view.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Data Engineering Podcast

JULY 23, 2023

Summary Real-time data processing has steadily been gaining adoption due to advances in the accessibility of the technologies involved. To bring streaming data in reach of application engineers Matteo Pelati helped to create Dozer. To bring streaming data in reach of application engineers Matteo Pelati helped to create Dozer.

Building 130

Building Machine Learning SQL Python 130

Snowflake

JULY 18, 2023

Data infrastructure that makes light work of complex tasks Built as a connected application from day one, the anecdotes Compliance OS uses the Snowflake Data Cloud for data ingestion and modeling, including a single cybersecurity data lake where all data can be analyzed within Snowflake.

Data Process 52

Data Process Process Data Lake Data Ingestion 52

Data Engineering Weekly

MAY 16, 2023

Architectural Patterns for Data Quality Now we understand the trade-off between speed & correctness and the difference between data testing and observability. Let’s talk about the data processing types. In the 'Write' stage, we capture the computed data in a log or a staging area.

Engineering 110

Engineering Kafka Data Pipeline Data Warehouse 110

Cloudera

AUGUST 26, 2021

While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store. Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange. Data ingestion through ‘s3’. Ozone Namespace Overview.

Data Science 113

Data Science Cloud Hadoop Metadata 113

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 107

Machine Learning Python Kafka Java 107

Cloudera

JANUARY 20, 2021

The data journey is not linear, but it is an infinite loop data lifecycle – initiating at the edge, weaving through a data platform, and resulting in business imperative insights applied to real business-critical problems that result in new data-led initiatives. Conclusion.

Manufacturing 110

Manufacturing Data Warehouse Kafka Retail 110

phData: Data Engineering

NOVEMBER 8, 2024

Streaming and Real-Time Data Processing As organizations increasingly demand real-time data insights, Open Table Formats offer strong support for streaming data processing, allowing organizations to seamlessly merge real-time and batch data.

Architecture 52

Architecture Systems Data Lake Google Cloud 52

Snowflake

NOVEMBER 29, 2023

Figure 2: Questions answered by precision medicine Snowflake and FAIR in the world of precision medicine and biomedical research Cloud-based big data technologies are not new for large-scale data processing. A conceptual architecture illustrating this is shown in Figure 3.

Metadata 117

Metadata Healthcare Medical Data Storage 117

ProjectPro

JANUARY 25, 2022

Easy Processing- PySpark enables us to process data rapidly, around 100 times quicker in memory and ten times faster on storage. When it comes to data ingestion pipelines, PySpark has a lot of advantages. PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems.

Big Data 52

Big Data Data Process Process Kafka 52

Cloudera

APRIL 15, 2019

While Cloudera Flow Management has been eagerly awaited by our Cloudera customers for use on their existing Cloudera platform clusters, Cloudera Edge Management has generated equal buzz across the industry for the possibilities that it brings to enterprises in their IoT initiatives around edge management and edge data collection.

Management 17

Management Data Ingestion Data Collection Government 17

Cloudera

JUNE 7, 2021

It calls out that Cloudera DataFlow “ includes streaming flow and streaming data processing unified with Cloudera Data Platform ”.

Kafka 103

Kafka Data Ingestion Cloud Architecture 103

Cloudera

MAY 30, 2024

Here’s what implementing an open data lakehouse with Cloudera delivers: Integration of Data Lake and Data Warehouse : An open data lakehouse brings together the best of both worlds by integrating the storage flexibility of a data lake with the query performance and structured querying capabilities of a data warehouse.

Data Lake 74

Data Lake Data Warehouse Programming Language Data Ingestion 74

Cloudera

FEBRUARY 8, 2021

ECC will enrich the data collected and will make it available to be used in analysis and model creation later in the data lifecycle. Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig.

Data Pipeline 118

Data Pipeline Building Manufacturing Data Warehouse 118

Snowflake

JUNE 6, 2024

Schedule data ingestion, processing, model training and insight generation to enhance efficiency and consistency in your data processes. Connect your preferred platform (GitHub, GitLab, Bitbucket, Azure DevOps) to manage and track changes for collaborative development.

SQL 115

SQL Python Machine Learning Data Workflow 115

Cloudera

FEBRUARY 15, 2024

Data integration and ingestion: With robust data integration capabilities, a modern data architecture makes real-time data ingestion from various sources—including structured, unstructured, and streaming data, as well as external data feeds—a reality.

Insurance 88

Insurance Banking Data Architecture Data Ingestion 88

LinkedIn Engineering

JUNE 15, 2023

In this blog post, we will discuss the AvroTensorDataset API, techniques we used to improve data processing speeds by up to 162x over existing solutions (thereby decreasing overall training time by up to 66%), and performance results from benchmarks and production.

Datasets 102

Datasets Bytes Process Data Ingestion 102

Netflix Tech

OCTOBER 19, 2020

This flexibility allows tracer libraries to record 100% traces in our mission-critical streaming microservices while collecting minimal traces from auxiliary systems like offline batch data processing. The next challenge was to stream large amounts of traces via a scalable data processing platform.

Building 95

Building Transportation Java Metadata 95

Data Engineering Podcast

OCTOBER 12, 2020

Our comprehensive data-level security, auditing and de-identification features eliminate the need for time-consuming manual processes and our focus on data and compliance team collaboration empowers you to deliver quick and valuable data analytics on the most sensitive data to unlock the full potential of your cloud data platforms.

Business Intelligence 100

Business Intelligence BI Consulting Data Ingestion 100

Christophe Blefari

JANUARY 20, 2024

He wrote some years ago 3 articles defining data engineering field. Some concepts When doing data engineering you can touch a lot of different concepts. 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.

Data Engineer 130

Data Engineer Data Engineering Engineering Hadoop 130

Snowflake

JUNE 4, 2024

Finally, Tasks Backfill (PrPr) automates historical data processing within Task Graphs. Additionally, Dynamic Tables are a new table type that you can use at every stage of your processing pipeline. Follow this quickstart to test-drive Dynamic Tables yourself. Snowflake integrates with GitHub, GitLab, Azure DevOps and Bitbucket.

Data Pipeline 122

Data Pipeline Python SQL Database 122

LinkedIn Engineering

OCTOBER 19, 2023

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Hevo

JULY 10, 2024

While you can use Snowpipe for straightforward and low-complexity data ingestion into Snowflake, Snowpipe alternatives, like Kafka, Spark, and COPY, provide enhanced capabilities for real-time data processing, scalability, flexibility in data handling, and broader ecosystem integration.

Kafka 52

Kafka Data Ingestion Data Data Process 52

Data Engineering Weekly

SEPTEMBER 18, 2024

The Rise of Data Observability Data observability has become increasingly critical as companies seek greater visibility into their data processes. This growing demand has found a natural synergy with the rise of the data lake.

Data Lake 98

Data Lake Data Pipeline Unstructured Data Data 98

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python.

Data Lake 98

Data Lake SQL Data Data Warehouse 98