Data Analysis using PySpark
Learn Data Analysis Using PySpark basics in this free online training. This free course is taught hands-on by experts. Learn about Real Time Data Analytics, Modelling Data & lot more. Best for Beginners. Start now!
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About this Course
PySpark is an interface developed for Apache Spark programmed in Python. Data is being generated continuously with the ability to draw insights from data and act on those insights is becoming an essential skill. Python is the top programming language globally which helps elevate Spark’s capabilities and helps you have an easy-to-use approach to learning the world of big data. It allows the programmer to develop applications using Python APIs. It helps the user perform more scalable analysis and pipelines. It interacts with Spark using Python to connect Jupyter to Spark to give rich data visualization.
In this Data Analysis using PySpark course, you will be introduced to real-time data analytics and learn about modelling data analytics, types of analytics, and Spark Streaming for real-time data analytics. Lastly, a hands-on session for analytics will be done using Twitter data. At the end of the course, you will be able to perform data analysis efficiently and have learned to use PySpark to analyze datasets at scale.
Course Outline
Real-time data analysis is a discipline that provides scope to draw insights through applying logic and mathematics to data to make better decisions quickly.
Modelling data uses different algorithms and varies on the inputs. While Descriptive, Diagnostic, Predictive and Prescriptive are the different types of analytics.
Spark steaming is used in real-time analysis as an integral part of Spark core API. It provides scalable, high-throughput, and fault-tolerant streaming application development opportunities for live data streams.
This section will demonstrate to you a sample analytics problem using Twitter data.
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