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Why Learn Big Data Analytics

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Across various industries, professionals have begun to deal with Big Data, which comes in both structured and unstructured form, in multi-terabytes of volume, it changes quickly and can’t be adapted using the traditional data warehousing technologies; and most of these industries have benefited from insights drawn from Big Data Analytics.

For example, insights from Big Data Analytics has helped retail chains in predicting customer buying patterns and delivering custom made schemes; it helps banking and finance industries in managing assets, investments, predicting stock and bond prices and managing customer risk probabilities. Big Data Analytics has had its usage in industries like Power, Aviation, Healthcare, Telecom, Sports, etc. Here’s an infographic illustrating potential 1% savings across specific industries with smart application of Big Data Analytics by GE Estimates.

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Apart from all the hype and benefits of Big Data, one must ask a question; as to why learn Big Data Analytics and what are the benefits for an IT professional to learn Data Analytics Course. To put things in perspective, the average salary for a Big Data Analyst in US is close to $125,000/- (Source: Forbes). According to a recent study by Business Insider, companies like Cisco, IBM, Oracle, EMC have alone posted nearly 38,000 open positions for technical professionals with expertise in Big Data Analytics. Industries like Informational Technologies, Finance and Insurance, Retail Trading and Manufacturing are constantly hiring for Big Data Manager and Analyst.

But that’s not enough incentive to learn Big Data Analytics. What drives most people towards Big Data is its ability to generate insights about customer behavior, ability to use commodity hardware, reduced software and data warehousing costs, faster development cycles and low latency applications. Therefore it has become imperative to learn technologies like Hadoop, MapReduce, Spark, Scala, Flume, Zookeeper, Kafka, Oozie, etc.

Difference between Data Analytics and Data Science

Before we further understand how to learn Big Data Analytics, let’s look at the two terms, that are often used interchangeably; Data Analytics and Data Science.

  • Data Science is a branch of computing that deals with understanding data from a business perspective. Data Science enables professionals to make predictions and generate insights to help businesses. Data Scientist needs to be proficient in computer applications, modeling, machine learning algorithms, mathematics and statistics.
  • Data Analytics on the other hand performs tasks of gathering, filtering and organizing data and extracting statistical information out of them to drive business insights. A Data Analyst is capable of proper data representation using graphs, charts and tables and responsible for operations and administrations of relational databases.

In the context of this article, we will further discuss the qualifications for Data Analyst.

Data Analytics require familiarity with business intelligence ideas and data warehousing. It requires proficiency in technologies like SQL, Hadoop, MapReduce, Hive, Hbase, Impala, Cassandra, Spark, etc. A Data Analyst should also be able to set up an entire relational database and should have an exposure with data soring tools and have data retrieving skills.

Topics in Big Data Analytics Course

We have drawn up a list of topics that any aspiring Big Data Analyst should thoroughly learn and practice. This course structure for Big Data Analytics is concluded based on our own experts experience with leading analytics organizations and projects that they have undertaken. This course content is also regularly updated based on the industry trends.

Please refer to the below link to have a detailed look into our course modules for Big Data Analytics:

https://www.analytixlabs.co.in/big-data-analytics-hadoop-training-course-online

This is an elaborate and exclusive list of all the topics that that a Big Data Analyst may need. Knowledge of Java, at a basic level, is also required. Let’s look at a simplified approach to learn Big Data Analytics:

  • Think about a real life Big Data Problem
  • Download and Configure the Big Data
  • Solve the Big Data Problem
  • Visualization and Analytics of Big Data Solution

We at AnalytixLabsprovide a Certification in Big Data Analytics, which constitute live training of the topics mentioned previously along with hands-on practice and self-paced learning.

At the end of the course at AnalytixLabs, you will be given a final project to work upon which will include integration of various technologies discussed so far.

8 Comments

  1. Sujitkumar Reply

    Thanks for sharing Valuable information about hadoop. Really helpful. Keep sharing………..

  2. I have just gone through your article on learning big data analytics, which is helpful in know a lots of new things. This blog provides different information related to big data and your thoughts is highly commendable.

  3. John Peter Reply

    Thanks a lot very much for the high quality and results-oriented help. I won’t think twice to endorse your blog post to anybody who wants and needs support about this area.

  4. Great work. Big data is becoming an effective basis for competition in pretty much every industry.Thank you for sharing this blog with us.

  5. rainadawan Reply

    Needed to compose you a very little word to thank you yet again
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  6. Hey Sangeeta,
    Wonderful blog you have shared here with great advantages of learning Big Data technology!! Really useful..
    Thank you

  7. It was great to read your blog. Definitely, it would be beneficial for those who want to learn big data analytics.

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