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Which is a Better Career Option – Networking or Data Science?

Feb 14th 2020 at 1:42 AM

Networking refers to the connectivity between systems, mobile phones and even IOT devices. The fundamental basics in networking include switches, routers and wireless access points. The devices connected are able to communicate with each other and across networks.

Data Science refers to the use of scientific methods, processes, algorithms and systems to extract meaningful insights from both structured as well as unstructured data.

Networking VS Data Science

Networking vs. Data Science

Networking deals with wired as well as wireless networks whereas Data Science requires expertise in mathematics, statistics and computer science disciplines and uses techniques such as machine learning, data mining, data storing and visualization.

Networking is a domain where the data is exchanged within networks while data science deals with analyzing, maintaining and processing large amounts of data.

Advantages and Disadvantages

There are many pros and cons of both the fields that we must consider and ponder upon before opting for either of the one.

Networking is a well-established field and finding a job in this area is relatively easy. Bagging a suitable job in Data Science is known to be a little difficult as the companies require you to do really well in your course and also have some past experience in the field.

Networking as a career is meant for professionals who want to play safe and easy while data scientists need to be extraordinarily smart and active as the career is very demanding, though Data Science showcases a faster growth rate and is obviously more in demand than network administrator.

Networking jobs have been estimated to grow at a rate of only 6% by 2026 while jobs related to Data Science are expected to grow by 15% in the year 2020. The vast difference between the job opportunities here is clearly visible to choose a career between the two.

The entry-level position in networking can earn you an average annual salary of $58,000 while experienced worked earn up to $117,000. This is massively low than what a data scientist earns. An entry level data scientist earns an average salary of $98,233 per annum, as per PayScale. Hence, a career in Data Science proves to be a lucrative option as compared to a career in networking.

Emerging Trend

Off late, a rising trend has been seen wherein networking professionals are moving into Data Science, though the tools and technologies used by both the domains are extremely different. Since a career in Data Science requires a lot of analysis and a statistical bent of mind, a professional from any other field must be backed by a valid and recognized certification.

Here is a list of top certifications to choose from :

  • Dell EMC Proven Professional certification program


  • Certified Analytics Professional


  • SAS Academy of Data Science


  • Microsoft Certified Solutions Expert (MCSE)


  • Cloudera Certified Associate (CCA)


  • Cloudera Certified Professional: CCP Data Engineer


  • Data Science Certificate – Harvard Extension School


Data Science, because of the reasons mentioned above, is being preferred by professionals across the world but the decision must be taken as per an individual’s choice, the area of expertise and discretion. Analyzing all the aspects thoroughly and figuring out what is suitable, must form the base for any conclusion.

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