What are the most efficient algorithms for data conversion in streaming data?
Data conversion is the process of transforming data from one format or structure to another, for example, from JSON to CSV or from XML to Parquet. Data conversion is essential for data engineering, as it enables data to be stored, processed, and analyzed more efficiently and effectively. However, data conversion can also be challenging, especially when dealing with streaming data, which is continuously generated and updated in real time. Streaming data requires fast and scalable algorithms that can handle large volumes, high velocity, and diverse sources of data. In this article, we will explore some of the most efficient algorithms for data conversion in streaming data, and how they can help you improve your data engineering skills and projects.
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Navya JammalamadakaData @Microsoft | NYU Alumna | Speaker | Mentor
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Rahul SSr. Engineering Manager - Data at Xiaomi Technology | Ex-Amazon, Merck | Top Data Engineer Voice - Principal Architect…
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Shibaji Biswas, PMP?Principal Project Engineer ?? | Mastering Emerging Tech and Data Engineering with Precision ?? #EmergingTech…