Decoding the Premise of Data Analytics Degrees
Written By: Pavithra Desikan


 The digital world leaves behind a trail of data with everything it consumes. The world is generating nearly 2.5 quintillion bytes data every day. Organizations are looking to leveraging this data to gain insights into the landscape, to gain edge over the market and to deliver business values. 

 Which brings us to Data Science and Analytics. Data science is a blend of tools, algorithms, and machine learning principles to interpret data, and utilize it to improve outcomes and drive effective digital strategies for business decisions. The process of inspecting the data sets to find trends and draw conclusions about the information so received is called Data analytics. 

 Why specialize in Data Analytics? 

 Understanding and making sense of the seemingly random data and extract value requires a level of expertise. Knowing one’s way around the data trail, identifying, managing, and analyzing structured and unstructured data, as well as various data analysis methods, descriptive statistics, regression analysis, and machine learning can enable contextual insights that empower businesses to understand priorities and build appropriate strategies. Also, a rounded exposure on critical thinking and problem-solving skills, as well as the ability to communicate the insights gained from data analysis to non-technical stakeholders, becomes an additional advantage. Deeper insights into business operations means a significant upper hand in the professional arena! 


Data Analytics related qualifications 

 From short certifications to full-blown degree courses, there are several avenues to pursue a qualification in data analytics.  

  • Certification courses. Lots of institutions like Google, IBM, Coursera, Udemy, AWS, Microsoft offer online data analyst certificate courses. 
  • Under-graduate courses in Computer Science/Data Science & Analytics/Statistics by universities worldwide  
  • Postgraduate, post graduate diploma, and MBA courses in data analytics and data science available online and in global universities as well. 
  • Several niche organizations have laser focus on full stack data analytics training programs. Systech’s bootcamp training program is a noteworthy mention. 


Key Offerings – Leveraging the data USP! 

 An expansive scope. Data analytics is under the radar more and more in recent years, mainly because of the versatility in application. By collecting and analyzing data from specific businesses, specific issues can be resolved at real time. Data analytics has proved itself comprehensively in the fields of manufacturing, RCPG, insurance, media and entertainment, renewable energy, and more. 

 Tenacious shelf life. Businesses are all focusing on big data predictive analysis to boost their revenue. Data is here to stay. There is always an open market for data professionals and it is expected to grow higher in the coming years. Data scientist, data engineer, data analyst, and data architect, to name a few.  

 Open to all (those apply!) While a specific degree in Data analytics is definitely welcome, they are not mandatory or restrictive. An eclectic collection of skills like statistical analytics, R, Python programming, Excel, PL/SQL, data structures/database, algorithm building, machine learning can stand one in good stead facing a data analytics job/interview, and can be picked up through an online academy like Coursera or Udemy. 

 Go for the gold. Be it remuneration, or career growth graph, data professionals have the goose with the golden egg. Experienced candidates have very high prospects, innumerous opportunities and are remunerated handsomely. 


 With the right skills, and the ability to keep pace with evolving trends, data analytics holds the key that unlocks all doors. For all analytically savvy candidates keeping up with the latest trends in the industry, leveraging its opportunities, exploring the intricacies of latent technologies, Data analytics is a strong contender. 


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