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Java is also widely used in big data technologies, supported by powerful Java-based tools like Apache Hadoop and Spark, which are essential for data processing in AI. Big Data Technologies With the growth of data-driven technologies, AI engineers must be proficient in big data platforms like Hadoop, Spark, and NoSQL databases.
For frameworks and languages, there’s SAS, Python, R, Apache Hadoop and many others. CloudComputing and Related Mechanics. Big data, advanced analytics, machine learning, none of these technologies would exist without cloudcomputing and the resulting infrastructure.
Tools like Tableau, Power BI, 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.
Hadoop , Apache Spark ) is beneficial for handling large datasets effectively. CloudComputing Skills Familiarize yourself with cloud platforms like AWS , Google Cloud , or Microsoft Azure to manage infrastructure and deploy AI models efficiently. Salary Range: 6,00,000 – 18,00,000 per annum.
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.
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.
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