Netflix Tech

FEBRUARY 14, 2025

The data collected feeds into a comprehensive quality dashboard and supports a tiered threshold-based alerting system. The Flink jobs sink is equipped with a data mesh connector, as detailed in our Data Mesh platform which has two outputs: Kafka and Iceberg.

Kafka 66

Kafka Datasets Metadata Utilities 66

ProjectPro

JANUARY 25, 2022

PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. Another reason to use PySpark is that it has the benefit of being able to scale to far more giant data sets compared to the Python Pandas library.

Big Data 52

Big Data Data Process Process Kafka 52

Striim

MARCH 21, 2025

To access real-time data, organizations are turning to stream processing. There are two main data processing paradigms: batch processing and stream processing. Your electric consumption is collected during a month and then processed and billed at the end of that period.

Process 52

Process Data Warehouse Kafka Data Pipeline 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

Christophe Blefari

SEPTEMBER 15, 2023

💡 Additional big tech stuff to check: real-time ML training at Etsy and last mile data processing with Ray at Pinterest. — Hugo propose 7 hacks to optimise data warehouse cost. From what I understand this performance simulator unlock capabilities in finding what are the best parameters for training.

Data Warehouse 130

Data Warehouse Data SQL Python 130

Snowflake

JANUARY 18, 2024

For example, if you have a large data processing task such as the analysis of production sensor data, customer surveys or inspection reports, you can increase your compute resources without having to increase your storage. In addition, they can add third-party data sets through Snowflake Marketplace to enrich insights.

Manufacturing 111

Manufacturing Unstructured Data Cloud Architecture 111

Knowledge Hut

MARCH 7, 2024

The year 2024 saw some enthralling changes in volume and variety of data across businesses worldwide. The surge in data generation is only going to continue. Foresighted enterprises are the ones who will be able to leverage this data for maximum profitability through data processing and handling techniques.

Big Data 98

Big Data Bytes Data Governance Raw Data 98

Striim

FEBRUARY 26, 2025

Striims real-time data integration capabilities bring several benefits: Non-Intrusive and Secure Data Collection : Striim collects data securely and reliably from your Intercom platform without disrupting your operations, allowing for continuous, real-time customer insights. How Does Striim Add Value?

Data Integration 40

Data Integration Data Collection Data Security Cloud 40

Striim

SEPTEMBER 11, 2024

Third-Party Data: External data sources that your company does not collect directly but integrates to enhance insights or support decision-making. These data sources serve as the starting point for the pipeline, providing the raw data that will be ingested, processed, and analyzed.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

U-Next

MARCH 1, 2023

Being a hybrid role, Data Engineer requires technical as well as business skills. They build scalable data processing pipelines and provide analytical insights to business users. A Data Engineer also designs, builds, integrates, and manages large-scale data processing systems. What is a data warehouse?

Data Engineer 75

Data Engineer Data Engineering Non-relational Database Engineering 75

Data Engineering Podcast

MAY 15, 2022

Summary Industrial applications are one of the primary adopters of Internet of Things (IoT) technologies, with business critical operations being informed by data collected across a fleet of sensors.

Designing 100

Designing MongoDB AWS SQL 100

Knowledge Hut

MAY 3, 2024

Not all real-life use-cases need data to be processed in real real-time, a few seconds delay is tolerated over having a unified framework like Spark Streaming and volumes of data processing. It provides a range of capabilities by integrating with other spark tools to do a variety of data processing.

Kafka 98

Kafka Scala Java Amazon Web Services 98

Snowflake

JULY 31, 2024

They also cannot easily collect, process or share multimodal health data, which encompasses a wide variety of data types — including clinical notes, protein sequences, chemical compound information, medical imaging and patient data.

Medical 98

Medical Healthcare Insurance Hospitality 98

Knowledge Hut

JUNE 3, 2024

We are at the very cusp of the data collection explosion in such a case. There is currently a shortage of Data Science engineers. The world is data-driven, and the need for qualified data scientists will only increase in the future. Your watch history is a rich data bank for these companies.

Programming Language 96

Programming Language Data Science Entertainment Banking 96

Cloudera

NOVEMBER 22, 2021

Explosion of data availability from a variety of sources, including on-premises data stores used by enterprise data warehousing / data lake platforms, data on cloud object stores typically produced by heterogenous, cloud-only processing technologies, or data produced by SaaS applications that have now evolved into distinct platform ecosystems (e.g.,

Hadoop 94

Hadoop Government Data Security Cloud 94

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. However, the abundance of data opens numerous possibilities for research and analysis.

Data Engineer 98

Data Engineer Data Engineering Coding Project 98

Cloudera

FEBRUARY 23, 2023

Prior to implementation, basic tasks such as analyzing pharmacy orders for conspicuous opioid prescribing practices were resource-constrained and burdened by time-consuming manual processes, yielding little actionable insight.

Data Analytics 77

Data Analytics Electronics Pharmaceutical Medical 77

Hevo

JUNE 26, 2024

Organizations deal with data collected from multiple sources, which increases the complexity of managing and processing it. Oracle offers a suite of tools that helps you store and manage the data, and Apache Spark enables you to handle large-scale data processing tasks.

Data Collection 52

Data Collection Data Data Process Management 52

Cloudera

SEPTEMBER 23, 2021

CDP is designed to effectively manage and secure data collection, enrichment and analysis—and move the data from Point A to points unknown faster than other systems. As a result, data is processed faster for your customers, leading to improved sales.

Data 82

Data Cloud Data Collection Designing 82

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

JANUARY 18, 2024

For an organization, full-stack data science merges the concept of data mining with decision-making, data storage, and revenue generation. It also helps organizations to maintain complex data processing systems with machine learning.

Data Science 96

Data Science Computer Science Programming Language Machine Learning 96

Knowledge Hut

DECEMBER 26, 2023

It includes a computation at the network's edge, closer to the data generators. The need for more reliable and faster data processing is driving this trend. It refers to the use of data acquired from internet-connected devices. The data collected is then used to analyze, track, and predict human behavior.

Technology 98

Technology Cloud Computing Healthcare Data Science 98

Towards Data Science

DECEMBER 4, 2023

We won’t be alone in this data collection; thankfully, there are data integration tools available in the market that can be adopted to configure and maintain ingestion pipelines in one place (e.g. Data Warehouse & Data Transformation We’ll have numerous pipelines dedicated to data transformation and normalisation.

Data Engineer 98

Data Engineer Data Engineering Engineering Data Lake 98

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

Precisely

FEBRUARY 29, 2024

This “clean” analysis can then be used to reengineer the process for automation. Challenges specific to SAP master data processes Drilling down into SAP master data processes gives us a more granular sense of the challenges companies face around core data creation and management.

IT 59

IT Process Data Collection Data Process 59

Confluent

FEBRUARY 6, 2019

While all these solutions help data scientists, data engineers and production engineers to work better together, there are underlying challenges within the hidden debts: Data collection (i.e., Apache Kafka and KSQL for data scientists and data engineers. integration) and preprocessing need to run at scale.

Machine Learning 107

Machine Learning Python Kafka Java 107

Databand.ai

JUNE 8, 2023

By implementing an observability pipeline, which typically consists of multiple technologies and processes, organizations can gain insights into data pipeline performance, including metrics, errors, and resource usage. This ensures the reliability and accuracy of data-driven decision-making processes.

Data Pipeline 52

Data Pipeline Bytes Data Collection Raw Data 52

Confluent

JUNE 13, 2019

You might think that data collection in astronomy consists of a lone astronomer pointing a telescope at a single object in a static sky. While that may be true in some cases (I collected the data for my Ph.D. thesis this way), the field of astronomy is rapidly changing into a data-intensive science with real-time needs.

Kafka 102

Kafka Python Bytes Data Pipeline 102

AltexSoft

MAY 12, 2022

Audio data transformation basics to know. Before diving deeper into processing of audio files, we need to introduce specific terms, that you will encounter at almost every step of our journey from sound data collection to getting ML predictions. One of the largest audio data collections is AudioSet by Google.

Machine Learning 122

Machine Learning Building Deep Learning Healthcare 122

Knowledge Hut

NOVEMBER 28, 2023

In this article, we will look at 31 different places to find free datasets for data science projects. We will discuss the different types of datasets in data science which cover disciplines like data visualization, data processing, machine learning, data cleaning, exploratory data analysis, natural language processing, and computer vision.

Datasets 96

Datasets Data Science Project Machine Learning 96

Striim

OCTOBER 11, 2024

While legacy ETL has a slow transformation step, modern ETL platforms, like Striim, have evolved to replace disk-based processing with in-memory processing. This advancement allows for real-time data transformation , enrichment, and analysis, providing faster and more efficient data processing.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Hevo

MAY 31, 2024

The exponential data growth has increased the demand for tools that make data processes, such as data collection, integration, and transformation, as smooth as possible. These tools and technologies can help you evolve your methods of handling organizational data.

Data Collection 40

Data Collection Technology Data Process Process 40

Knowledge Hut

APRIL 25, 2024

Big data can be summed up as a sizable data collection comprising a variety of informational sets. It is a vast and intricate data set. Big data has been a concept for some time, but it has only just begun to change the corporate sector. What is Big Data? Who U ses Big Data? use big data.

Big Data 97

Big Data Entertainment Transportation Banking 97

DataKitchen

JUNE 21, 2024

Teams working in silos, poor communication channels, and a lack of standardized procedures can lead to inconsistencies and errors in data handling. Knowledge Gaps: A lack of comprehensive understanding of the data being handled and the business context it serves can lead to misinterpretations and incorrect data processing.

Data Engineer 52

Data Engineer Data Engineering Engineering Data 52

Knowledge Hut

JANUARY 19, 2024

However, having a lot of data is useless if businesses can't use it to make informed, data-driven decisions by analyzing it to extract useful insights. Business intelligence (BI) is becoming more important as a result of the growing need to use data to further organizational objectives.

Business Intelligence 52

Business Intelligence BI Business Analyst Finance 52

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Volume Big Data refers to large volumes of data, typically in the order of terabytes or petabytes. It involves processing and analyzing massive datasets that cannot be managed with traditional data processing techniques.

Big Data 52

Big Data Datasets Data Analysis Media 52

Snowflake

JUNE 13, 2023

This speed brings new efficiencies to tesa’s internal processes, and allows the company to experiment freely with an eye to improving the efficiency of its production. With data processing and analytics, you sometimes want to fail fast to answer your most pressing production questions. That view can accelerate time to market.

Cloud 52

Cloud Manufacturing Datasets Scala 52