Should you start with big data training or learn data analytics? Which one to start first?

January 9, 2019
data analytics

One of the biggest changes in global technology has been the emergence of data analytics and big data. The two streams fall under the data analytics field, but there are major differences between the two. Data science courses involve different projects such as visualization, a predictive model using R and data manipulation.

Big data generally deals with the analysis of massive data amounts with the help of Hadoop. Generally, database systems do not deal with big data, and the adoption of NoSQL systems such as Hadoop across industries is increasing.

One of the key modules of big data also talks about the integration of Tableau and R with the Hadoop cluster. The Hadoop infrastructure ensures smoother handling of big data while Tableau and R have in-built functions to help generate insights from summary statistics, visualizations and dashboards.

Difference between Big data and Data analytics:
If you wish to understand the difference between data analytics and big data, you must understand the technologies and tools which can be learnt. By building a good working knowledge around the database and analytical tools, you’ll be able to succeed in either of the fields.

Data science is taught in R software which is open source and statistical programming knowledge. It is one of the most essential tools of any Data scientist’s toolkit as it provides an extensive repository around analytical and statistical applications. R is growing in popularity and firms are generally on the lookout for more R programmers.

Big data, on the other hand, consists of components of Hadoop such as HBase, Hive, Flume and Sqoop and helps in analyzing and processing large data sets. There are also aspects of installation on Java-based programming such as MapReduce. Big data also contains modules on integrating R and software such as Tableau using Hadoop library along with the Tableau-Hadoop connectors and performs data analysis as well.

Which one should one begin with?
Advanced analytics techniques and statistical knowledge are extremely crucial to implement data analytic projects. If you’re someone who is comfortable programming with R, then data science is a good place to begin. Analytics projects consist of different sections such as exploration, visualization and the likes, so you will have to be well-equipped in the same to succeed.

If you have the ability to sort through massive volumes of unstructured and raw data and analyse the same, then big data is the course you need to go for. The data can be deciphered through multiple channels such as the internet, social media, mobiles etc. and then used by businesses to make decisions. If operational insights into a business are more of your thing, then data analytics is what you must consider. It considers the previous historical data and then draws insights and inferences to solve business problems.

Thus, make an informed choice before you head into the world of data analysis or big data training. Based on which skill set works best, you can choose one that suits your ability better. Imarticus provides courses on data analytics and big data, so you can weigh them out before making a decision.

Post a comment

15 − five =