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In der Parallelwelt der ITler wurde das Tool und Ökosystem Apache Hadoop quasi mit Big Data beinahe synonym gesetzt. CloudComputing , erst mit den Infrastructure as a Service (IaaS) Angeboten von Amazon, Microsoft und Google, wurde zum Enabler für schnelle, flexible Big Data Architekturen.
For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. The popular tools, on the other hand, include PowerBI, ETL, IBM Db2, and Teradata. CloudComputing and Related Mechanics. But more importantly, these are the examples today — right now — and they may shift or change over time.
Tools like Tableau, PowerBI, and Python libraries such as Matplotlib and Seaborn are commonly taught. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. R : Often used for statistical analysis and data visualization.
A key aspect of this evolution is the increased adoption of cloudcomputing, which allows businesses to store and process vast amounts of data efficiently. Gain Experience with Big Data Technologies With the rise of Big Data, familiarity with technologies like Hadoop and Spark is essential.
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