How to become a Big Data Analyst?: Come Find the Answers

  • click to rate
    How to become a Big Data Analyst

    It is simply not enough to mention a process of data generation occurring at an unfathomable rate when discussing the data boom. Data fits this new trend's unusual nature. This is what enabled it to get the prefix "Big." While we will discuss the specifics of big data in the sections that follow, it is crucial to realise that big data is not the same as regular data. As a result, a Big Data Analyst's job also differs from a standard Data Analyst's. The former is in charge of processing Big Data, which includes Raw, Unstructured, and Semi-Structured Data, whereas the latter deal mostly with Structured Data. Furthermore, it is only reasonable to expect young, aspirant professionals to look for solutions to the subject of How to Become a Big Data Analyst given that "the world is one Big Data problem" (Andrew McAfee).

    How to Become a Big Data Analyst is a question that we will attempt to address in this article. In addition, we'll try to delve deeper into the role of a big data analyst in terms of academic background, job opportunities, and big data analyst skills, as well as what a big data analyst actually performs for a living.

    What is Big Data and who is a Big Data Analyst?

    Big Data Analyst Skills

    Big Data Analyst Job Description

    Big Data Analyst Salary 

    How to become a Big Data Analyst?: Step-by-Step Guide


    What is Big Data and who is a Big Data Analyst?

    Big Data is fundamentally described by Gartner as "high-volume, high-velocity, and high-variety information assets that demand cost-effective, creative forms of information processing for increased insight and decision making." Big Data has also been said to possess the fourth characteristic over time, called "veracity." Veracity is the term used to describe low-quality, unconfirmed data that comes from shady and unauthorized sources. Such information alone could produce inconsistent results and inaccurate conclusions. Therefore, it is necessary to use such raw data to make it appropriate for analytics. This is what a big data analyst does.

    It's crucial to keep in mind that a Big Data Analyst's job is quite similar to a Data Scientist's when attempting to grasp what a Big Data Analyst does. Big Data collecting, cleaning, processing, and analysis fall under the purview of both individuals. They next try to understand the conclusions drawn from the study of the Data in order to turn them into practical commercial decision-making methods. As a result, they are likely to use highly understandable kinds of data visualization to present and display their findings. In order to identify important industry trends, a big data analyst is also tasked with carrying out competitive market analysis activities.

    Big Data Analyst Skills

    Without knowing the essential skills and knowledge needed for big data analyst jobs, it is impossible to provide an effective response to the issue of how to become a big data analyst.

    Mathematical Competence

    Big Data Analysts must possess extraordinary mathematical skills, particularly in the areas of statistics, multivariable calculus, hypothesis testing, linear algebra, time series and longitudinal analysis, probability distribution, bayesian analysis, and others, in order to undertake data analysis.

    Database Management

    Understanding how data is stored and accessed is crucial if you want to land a job as a big data analyst. It is essential to have a working knowledge of both relational and non-relational databases. This includes knowledge of CouchDB, HBase, MongoDB, DB2, Oracle, HDFS, Cassandra, and NoSQL databases like MySQL and NoSQL.

    Computer Languages

    The ability to code is a crucial skill for a big data analyst. It is essential to be proficient in programming languages, at least in some of the most prominent ones like Python, R, and Java. Additionally, it will strengthen your competitive edge if you make an effort to study additional languages like C++, Ruby, Julia, Scala, MATLAB, and SPSS.

    Knowledge of Computing Frameworks

    You must have a thorough understanding of computational frameworks like Hadoop, Apache Spark, Apache Storm, Apache Samza, and Apache Flink if you want to succeed as a big data analyst. These frameworks aid in facilitating efficient big data processing.

    To read the full article visit - How to become a Big Data Analyst?: Come Find the Answers