Why is Data Analytics Important for Technology Professionals

The era we live in is driven and ruled by data. The more data you analyze, the higher the competitive edge you have. Given the ocean-like quantity of data generated daily, demand for people who can analyze those oceans quickly, effectively and efficiently has risen.

A survey on page no.4, in a Deloitte report titled, ‘The Analytics Advantage,’ states that 49% of respondents believed they made better decisions with data. 16% of respondents believed data analytics helped in enabling key strategic initiatives.

Scaling businesses and new startups with disruptive tech; both need data analytics and data analysts equally needed for a competitive edge. Data analytics eases business processes and helps create long-lasting professional relationships. On page 16, the report also comments on the lack of skilled analytics professionals and how this gap will widen. For IT professionals learning data analytics is necessary.

How Data Analytics Revolutionised Tasks for Better

Data Analytics has a vast scope in daily life, technology, and business operations.

• Helps in understanding improved and informed decision making
• Helps in spotting trends in data visualization
• Helps in automating and streamlining processes to reduce manual labor
• Helps improve risk management by correlating one dataset with another.
• Helps in serving customers better by finding lagging areas
• Provides a competitive edge through data-driven decisions. 

Top Job Roles for a Career in Data Analytics

If you are considering having a career in Data Analytics, here is a list of job opportunities.

• Financial Analyst– Financial Analyst is responsible for the financial health of a department, project or company. They oversee all transactions and ensure the financial soundness of the organization. They analyze market conditions and forecast financial plans accordingly.

• Software Engineer: They write, debug, test and maintain softwares at the basic level. They also work with data scientists and engineers to analyze data and simplify larger datasets. Software Engineers convert what needs to be done into various programming languages and speed up tasks. 

Quoting Glassdoor, the average salary of a Software Engineer is $107,500 per annum in the USA, £54,650 per annum in the UK,and ₹850,000 per annum in India.

• Business Analyst: All the work related to data collection and scrutinization for business expansion is done by Business Analysts. They find opportunities, gather information, convince shareholders, lead the project, and work with colleagues for better outcomes and results. They can test business processes and give critical feedback for improvement.

Quoting Glassdoor, the average salary of a Business Analyst is $82,150 per annum in the US, £48,800 per annum in the UK,and ₹850,000 per annum in India.

• System Analyst: System Analysts are responsible for analyzing information systems’ data to find anomalies, test the system, and create a checklist of specifications that developers and engineers follow. They look after the IT system and maintain it to meet business requirements as it grows. 

Quoting Glassdoor, the average salary of a System Analyst is $86,120 per annum in the US, £38,060 per annum in the UK,and ₹875,890 per annum in India.

• Market Analyst: A Market Analyst collects information and important data regarding the market and analyzes and interprets it to suggest the sale of products and services. Market Analysts study demographic data, consumer behavior, and sales reports to suggest pricing. They forecast marketing and sales trends and adjust in-house marketing strategies accordingly.    

Quoting Glassdoor, the average salary of a Market Analyst is $73,690 per annum in the US, £38,480 per annum in the UK,and ₹10,24,030 per annum in India.

• Quantitative Analyst– Quantitative Analysts look after the business and finances and suggest ways a company can make sound financial decisions. Usually, these professionals work for investment firms, insurance, banking institutions, and hedge funds. They identify profitable investment windows and direct funds for the same.

Quoting Glassdoor, the average salary of a Quantitative Analyst is $146,080 per annum in the US,£98,990 per annum in the UK,and ₹15,94,600 per annum in India.   

How to Start a Career in Data Analytics

Learning Data Analytics skills for job growth and career advancement is important. A skilled candidate is the most desired one. Many courses are available on the web, but careervira has handpicked the best courses for Data Analytics. Indulge in courses by Simpliv LLC on Careervira to enhance your hiring chances.

• Python for Data Analytics and Machine Learning Bootcamp by Simpliv LLC: Python is an important tool for data analysis for scrutinizing business processes. The course covers advanced Python techniques, data exploration, and predictive and descriptive analysis. Other concepts like clustering methods, including k-means and hierarchical clustering, are covered in the course.

• 3 Essential Excel Skills for Data Analysts by Simpliv LLC: This quick 3-hour course teaches basic but 3 important Excel skills; table, pivot tables, and power query. Learning these skills saves time when one has to slice-dice large data sets to get quick results. These skills aid data analysis and visualization.  

• 3 Days Live Virtual Training on Data Science with R Certification by Simpliv LLC: The course focuses on imparting valuable skills for data analytics like R programming. R is an important tool for data analysis and statistical interpretation. The course teaches predictive analysis, data visualization, statistical concepts, ggplot2 packages, and the Apriori algorithm.

• Minitab Essentials Bootcamp by Simpliv LLC: Learning Minitab is important as it is the most useful software for statistical analysis. It teaches data management, analysis, and visualization. The module is perfect for professionals working in quality analysis and maintenance.    

• MongoDB Certification Bootcamp by Simpliv LLC: The course focuses on honing data analytics skills by teaching how to simplify large data with MongoDB. It is a popular query and database language everyone needs while working with any data type. Due to its importance in data analytics, MongoDB professionals are in great demand.   

Conclusion

Almost every problem in the present world is solved by data. Other operational issues which professionals traditionally solved now use computer softwares and programming languages to create algorithms that automate those tasks. Given job loss due to automation, updating skill sets to ensure job security has to be prioritized.

The Deloitte survey mentioned above also states on page 16 how 96% of the respondents believe data will be of supreme importance in the coming years and how most organizations use rudimentary analytics. Such advancement has to be met with upskilling of technology professionals to stay up to date in the dynamic world of data.