VoltDB

DECEMBER 11, 2024

Data Overload and Storage Limitations As IoT and especially industrial IoT -based devices proliferate, the volume of data generated at the edge has skyrocketed. Managing and storing this data locally presents logistical and cost challenges, particularly for industries like manufacturing, healthcare, and autonomous vehicles.

IoT 52

IoT Energy Logistics Latency 52

O'Reilly

FEBRUARY 18, 2020

Along with R , Python is one of the most-used languages for data analysis. From pre-built libraries for linear or logistic regressions, decision trees, naïve Bayes, k-means, gradient-boosting, etc., there’s a Python library for virtually anything a developer or data scientist might need to do. This follows a 3% drop in 2018.

Software Architecture 145

Software Architecture DevOps Data Engineering Architecture 145

Abhishek Tiwari

JULY 7, 2023

Airflow provides rich scheduling and execution semantics enabling data engineers to easily define complex pipelines, running at regular intervals. From transportation and logistics to e-commerce and food delivery, the core operations of many successful companies can be viewed as workflow problems.

Logistics 52

Logistics Transportation Scalability Data Engineering 52

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 112

Cloud Big Data AWS Analytics 112