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Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or PowerBI. Programming Questions Data science roles typically require knowledge of Python, SQL, R, or Hadoop. Their role is crucial in understanding the underlying data structures and how to leverage them for insights.
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.
It’s for good reason too because automation and powerful machine learning tools can help extract insights that would otherwise be difficult to find even by skilled analysts. The entire process is also achieved much faster, boosting not just general efficiency but an organization’s reaction time to certain events, as well.
And you should have experience working with big data platforms such as Hadoop or Apache Spark. Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred. To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI.
Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing. Once data is collected, it needs to be stored efficiently.
Because they are the most likely to communicate data insights, they’ll also need to know SQL, and visualization tools such as PowerBI and Tableau as well. Some of the tools and techniques unique to business analysts are pivot tables, financial modeling in Excel, PowerBI Dashboards for forecasting, and Tableau for similar purposes.
Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments. PowerBI is surprisingly popular as well, possibly for its focus on business and applications, making it more commonly used by even non-tech-savvy individuals.
Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data. Apache Kafka Apache Kafka is a distributed event streaming platform used for real-time data processing. Apache Hive Apache Hive is a data warehouse tool that allows users to query and analyse large datasets stored in Hadoop.
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