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. integration) and preprocessing need to run at scale.

Machine Learning 107

Machine Learning Python Kafka Java 107

Rockset

OCTOBER 26, 2022

One was to create another data pipeline that would aggregate data as it was ingested into DynamoDB. And with the NFL season set to start in less than a month, we were in a bind. A Faster, Friendlier Solution We considered a few alternatives. Another was to scrap DynamoDB and find a traditional SQL database.

SQL 52

SQL NoSQL Database Aggregated Data 52

Striim

OCTOBER 11, 2024

Whether you’re in the healthcare industry or logistics, being data-driven is equally important. Here’s an example: Suppose your fleet management business uses batch processing to analyze vehicle data. This interconnected approach enables teams to create, manage, and automate data pipelines with ease and minimal intervention.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Striim

JULY 10, 2024

In contrast, data streaming offers continuous, real-time integration and analysis, ensuring predictive models always use the latest information. Data transformation includes normalizing data, encoding categorical variables, and aggregating data at the appropriate granularity. Here’s the process.

Management 52

Management Transportation Machine Learning High Quality Data 52

Monte Carlo

FEBRUARY 15, 2023

This article will define in simple terms what a data warehouse is, how it’s different from a database, fundamentals of how they work, and an overview of today’s most popular data warehouses. What is a data warehouse? Yes, data warehouses can store unstructured data as a blob datatype. They need to be transformed.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

DareData

JULY 5, 2023

Users: Who are users that will interact with your data and what's their technical proficiency? Data Sources: How different are your data sources? Latency: What is the minimum expected latency between data collection and analytics? And what is their format?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

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