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Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate, doubling every two years, and changing the way we live. According to IBM, 2.5 billion gigabytes (GB) of data was generated every day in 2012.
An article by Forbes states that Data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet.
Which makes it extremely important to at least know the basics of the field. After all, here is where our future lies.
In this video, we will differentiate between the Data Science, Big Data, and Data Analytics, based on what it is, where it is used, the skills you need to become a professional in the field, and the salary prospects in each field.
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➡️ About Post Graduate Program In Data Engineering
This Data Engineering course is ideal for professionals, covering critical topics like the Hadoop framework, Data Processing using Spark, Data Pipelines with Kafka, Big Data on AWS, and Azure cloud infrastructures. This program is delivered via live sessions, industry projects, IBM hackathons, and Ask Me Anything sessions.
✅ Key Features
Post Graduate Program Certificate and Alumni Association membership
– Exclusive Master Classes and Ask me Anything sessions by IBM
– 8X higher live interaction in live Data Engineering online classes by industry experts
– Capstone from 3 domains and 14+ Projects with Industry datasets from YouTube, Glassdoor, Facebook etc.
– Simplilearn’s JobAssist helps you get noticed by top hiring companies
✅ Skills Covered
– Real-Time Data Processing
– Data Pipelining
– Big Data Analytics
– Data Visualization
– Provisioning data storage services
– Apache Hadoop
– Ingesting Streaming and Batch Data
– Transforming Data
– Implementing Security Requirements
– Data Protection
– Encryption Techniques
– Data Governance and Compliance Controls
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