What is the difference between Data Science and Big Data?

Yes, we have our ears to the ground. Many of you start your career in analytical data and big data, sometimes confused and unsure about which courses should be done. Well, many will depend on your career goals, as well as your competence. To help you better understand the difference between these courses, our big data expert at Kiran P.V’s house has spent the time to register each of these courses and even go further to explain which courses are more in accordance with your career aspirations.

Many IT experts around the world will agree that we live in great data. Science data and big data are two terms that are generally referenced in all literature while discussing the potential benefits of enabling decision-making driven by data. The important thing is this latest trend creates new job opportunities and demand for people with a series of right data skills is increasing. To meet the increasing needs of big data and data science talents, we witness the emergence of training programs around the world throughout the world, MOOCs, and other niche analytic institutes. In Jigsaw Academy, we have specifically created data science and big data courses with the help of industry experts to guide students who aspire and professionals to pursue a successful career in the world of interesting data.

Although this course is in the area of ​​extensive data analysis, some of the big differences exist between them in terms of the technology involved and the possibility of extensive final applications. Data science courses involve implementing various analytic project phases such as data manipulation, predictive visualization, and building models using R. software. This course also provides general programming training with R, using default data objects and writing special functions and programs.

On the other hand, big data certainly handles processing and analyzes a big number of data using Hadoop technology. The traditional database system fails to effectively deal with big data effectively, thus adopting NoSQL-based systems such as Hadoop and others in various industrial vertical increases. In addition to providing theoretical and hand aspects working with Hadoop, this course also includes conducting data analysis using software such as R and Tableau. One other main module of big data courses will be integrated R and Tableau with Hadoop Cluster to make the best of both worlds. Hadoop infrastructure allows handling smooth data smoothly while R and tables inbuilt functions help produce insight from data through summary statistics, dashboards, and visualization.

In the next section, I will discuss some of the main differences between data science and big data courses regarding exposure to tools, topics related to statistics, and advanced analytics. In addition, various aspects related to the choice of courses in terms of career fitting will be discussed including the comparison of existing big data courses offered by EMC and CLOUDERA HADOOP certification.

How do data science and big data courses differ from each other?

To better understand the difference between a data science master program course, one must try to see some of the main dimensions such as the type of tool and technology that can be learned and the level of the concept of big data will be borne in each. Building comprehensive knowledge and work expertise around various analytical tools and databases is the main step to superior in big data fields and data science.

The data science course is fully taught in software R, an open-source statistical programming language and one of the important tools that are part of any data scientist tool kit. Because of the spacious package repository around the statistical and analytic applications, R is very popular globally, and many companies are looking for R. programmers.

On the other hand, big jigsaw data courses provide extensive training on Hadoop and its components such as Hive, HBase, SQOOP, and Flume to process and analyze a big number of data. This course also includes Hadoop’s installation aspects and its components and trains students on Java-based MapReduce programming. Apart from the concept of Hadoop, a big data course also contains training modules about the integration of R and Tableau software with Hadoop Clusters using the Radoop Library and Tableau-Hadoop connectors, to carry out the task of data analysis and further produce dashboard and visualization.


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