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How Manufacturers Drive Profits with Connected Products

Snowflake

Top of mind are services that enable fleet management, boost utilization rates, facilitate handshakes with other modes of transport, or match arrival times at warehouses with time slots for offloading. Connected trucks provide data for modular service components that can be customized or sold as needed.

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Case Study: Bringing Real-Time Analytics to Construction Logistics at Command Alkon

Rockset

Think construction logistics and one pictures a flow of trucks transporting concrete and other necessary materials from suppliers to construction sites. Yet for every physical delivery made, many more exchanges of data occur in the background in order to seamlessly orchestrate supply chain operations.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

There are open data platforms in several regions (like data.gov in the U.S.). These open data sets are a fantastic resource if you're working on a personal project for fun. Data Preparation and Cleaning The data preparation step, which may consume up to 80% of the time allocated to any big data or data engineering project, comes next.

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Data Labeling in Machine Learning: Process, Types, and Best Practices

AltexSoft

Not only is it hard to get lots of data (particularly for the cases of highly specialized niches such as healthcare), but manually adding tags for each item of data is also a difficult, time-consuming task requiring the work of human labelers. It is possible to render as much synthetic data as needed for the project.

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Big Data Analytics: How It Works, Tools, and Real-Life Applications

AltexSoft

It’s represented in terms of batch reporting, near real-time/real-time processing, and data streaming. The best-case scenario is when the speed with which the data is produced meets the speed with which it is processed. Let’s take the transportation industry for example. Big Data analytics processes and tools.

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Understanding the 4 Fundamental Components of Big Data Ecosystem

U-Next

The fast development of digital technologies, IoT goods and connectivity platforms, social networking apps, video, audio, and geolocation services has created the potential for massive amounts of data to be collected/accumulated. Financial services firms use big data platforms for risk management and real-time market data analysis. .