Data Wrangling/ Data Munging
Glossary page
Data munging, also known as data wrangling, refers to the manual process of converting or mapping data from its original "raw" form into a format that is more easily consumable with the aid of semi-automated tools. This process may involve additional steps such as data visualization, data aggregation, statistical modeling, or other applications. Typically, data munging follows a set of general steps, starting with extracting raw data from a source, using algorithms or parsing techniques to transform the data into predefined structures, and ultimately depositing the resulting content into a storage location for future use. With the rapid expansion of the internet, these techniques are becoming increasingly critical for organizing the vast amounts of available dat
https://online.hbs.edu/blog/post/data-wrangling
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T-Systems is now Catena-X-certified for Traceability use case
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Andrea Garcia
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T‑Systems and German Edge Cloud are joining forces to deliver integrated, ready‑to‑use digital solutions for industrial data ecosystems such as Catena‑X. By combining T‑Systems’ expertise in integration and connectivity with German Edge Cloud’s ONCITE Industrial SaaS solution, the partnership enables scalable applications for traceability and Industrial AI, provided via the Telekom Cloud. This collaboration helps manufacturing companies implement use cases quickly, achieve seamless integrations, and generate measurable value across the entire supply chain. The goal is to build open, interoperable digital ecosystems that accelerate and sustain digital transformation in the manufacturing industry.
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Sven Löffler
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End-to-end solution for carbon footprint in the supply chain
T‑Systems and IPOINT have launched an end‑to‑end solution that enables automotive manufacturers and suppliers to track product carbon footprints across global supply chains. By combining IPOINT’s sustainability software with T‑Systems’ access to the Catena‑X data ecosystem, the solution supports transparent emissions reporting in line with EU CSRD requirements and provides actionable insights for reducing environmental impact.
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Sven Löffler
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