Big Data Analytics

FAQs

• What is Big Data Analytics?

  Big Data Analytics is defined as using advanced analytic techniques to examine large amounts of data and make sense of it. The primary goal of big data analysis is to find patterns and actionable information that might otherwise be lost in the huge pile of raw data and use the results to provide valuable insights about the users who created it.

• What are the best Big Data Analytics foundation courses for beginners?

  Here are three of the best big data analytics starter courses:

  • Big Data Hadoop Certification
  • Data Science Certification Training - R Programming
  • MongoDB Certification Course

• What is the best intermediate-level course offered in Big Data Analytics?

  The Apache Kafka course is an excellent follow-up to the basic courses.

• What are the best advanced-level courses in Big Data Analytics?

  You can supplement your knowledge of big data analytics with the following advanced courses:

  • Big Data and Hadoop Administrator Course
  • Data Science with Python Course
  • Machine Learning Certification Course
  • Apache Spark and Scala Certification Course
  • Deep Learning with Tensorflow Certification Course
  • Data Scientist Courses
  • Artificial Intelligence Engineer Courses

• What does the Big Data Analytics job market look like?

  According to a new study from PwC, big data job openings are expected to grow at an increased pace in 2020, resulting in the creation of around 2.7 million new jobs.

• What are the most popular Big Data Analytics job titles?

  Here is a sample of the top job titles in Big Data Analytics:

  • Big Data Scientist
  • Big Data Analyst
  • Big Data Architect
  • Big Data Engineer
  • Machine Learning Engineer

• What is the recommended career path for Big Data Analytics aspirants?

  Anyone who wants to become a big data analytics professional should use the following path:

  1. Operating System - You must be proficient in any of the operating systems that Big Data uses, like Windows, Linux, or macOS.
  2. Programming - You should have an in-depth understanding of programming languages to easily process big data. Java, Python, R, and C++ are the most popular ones.
  3. DBMS and SQL - You need to learn to write SQL queries in My SQL, Oracle Database, or Microsoft SQL Server to manage data in the databases
  4. ETL and Warehousing tools - ETL tools, like Informatica, Talend, and Pentaho are critical to aggregation and analysis of unstructured data from different sources, so you need the ability to understand and work with them.
  5. Hadoop and Spark Frameworks - You need the ability to process and analyze large volumes of data using Hadoop and Spark.
  6. Data Mining and Modelling - You must develop the capability to analyze existing data and discover patterns for creating predictive data models

• What is the average salary of a Big Data Analytics professional?

  The average annual salary of a big data analytics professional is around USD 92,773.

• What are the top industries that have a high demand for Big Data Analytics professionals?

  • IT
  • Finance
  • Healthcare
  • Automotive
  • Telecommunications

• What specific companies are hiring the most Big Data Analytics professionals?

  Here are the top companies hiring Big Data Analytics professionals:

  • Amazon
  • Accenture
  • Apple
  • Intel
  • Facebook