Both businesses and individual users are moving from physical storage to the cloud. With electronic devices becoming smaller, more capable and accessible to everyone, the world is seeing an exponential increase in the data generated. The size of data generated every single day is around 2.5 quintillion bytes and as forecasted, the size of the data will reach around 463 Zettabytes by 2025.
This data contains within it, a treasure trove of insights, opportunities, and potential, waiting to be unlocked by businesses world over. With every click, swipe, share, and like businesses are making decisions about the future.
Traditional business intelligence and analytics methods can’t keep up with such a vast amount of data, and this has given rise to the modern world of data science including highly specialized and powerful tools and techniques. However, with better technology comes the need for a new breed of professionals: specialized data professionals who can utilize this wealth of data to churn out insights that have immense business value. IBM estimates that there will be 700,000 new data jobs by 2022 across all industries. Data Science is brimming with a huge job opportunity because businesses now started realizing the importance of analyzing data and the growth potential it brings to the table. Learn by enrolling in Data Science Training in Bangalore from a reputed training partner.
This definitely makes “Data Science“, the field you need to be in, to grab opportunities for the future and beyond.
Data Science Applications has Spread Its Wings Across Industries
Genetics and Genomics, Medical Image Analysis, Digital Marketing, Fraud and Risk Detection, Airline Route Planning, Banking and Finance, Weather Forecast, Gaming, Image Recognition, Virtual Assistants, Logistics Delivery, Speech Recognition, Price comparison of websites, Automobile and Transportation, Targeted Advertising, Dynamic Pricing Models and much more.
Hottest Roles in the Field of Data Science
Some top roles in the field are Data Analyst, Business Analyst, Data Scientist, Data Engineer and Data Architect.
Data Analyst
$61,000/year
Just about everything is data-driven these days, from market research and sales figures to expenses and logistics. To most people, this information can be overwhelming and daunting. It can be difficult and time-consuming to sort through it all and know what’s important, what isn’t, and what it all means.
This is where data analysts come into the picture: they take this data and turn it into useful information for businesses, which allows them to make more informed decisions in the future.
A Data Analyst occupies an entry-level role in a data analytics team. In this role, you need to be adept at translating numeric data into a form that can be understood by everyone in an organization. You need to be proficient in several areas, including programming languages such as python, tools such as excel, fundamentals of data handling, reporting, and modeling. With enough experience under your belt, you can gradually progress from a data analyst to assume the role of a data engineer and a data scientist.
Day-to-day Tasks and Responsibilities:
- Collecting information from a database with the help of queries
- Enable data processing and summarize results
- Use basic algorithms in their work like logistic regression, linear regression and so on
- Possess and display deep expertise in data munging, data visualization, exploratory data analysis and statistics
There are many reasons to consider a career in data analytics, including pay grade. The average data analyst job salary is over $61,000 per year.
Top companies that Hunts for Data Analysts are Flipkart, Amazon, Bosch, Myntra, McAfee, Dell and Target.
Business Analyst
$67,000/year
The responsibilities of a business analyst vary depending on the industry, but at the core, the role requires analyzing data and using that data to inform important strategic decisions that improve the overall revenue or efficiency of a business.
Business Analyst understands the business and data requirements, translates the operational requirements of clients, has deep domain expertise and can also perform data collection and reporting. Core skills required include combining analytical and operational skills to drive projects forward and a deep understanding of how business analysis delivers more value to organizations.
Day-to-day Tasks and Responsibilities:
- Analyze large amounts of complex data to provide the business with fact-based insights
- Present recommendations on process improvements that address business needs or resolve impediments
- Implement advanced strategies for gathering, reviewing and analyzing data requirements
- Work with internal teams and third parties to escalate and resolve any issues detected in revenue streams, and evaluate broader trends within a company’s revenue streams
- Identify problematic areas with the data and research to determine the best course of action to correct the data
If you have a degree in business and enjoy using data to highlight areas of improvement for companies, you may want to consider a career as a business analyst. The average salary for a business analyst is about $67,000.
Top companies that Hunts for Business Analysts are JP Morgan Chase & Co, Bank of America, Amazon, Shell, Flipkart, Cargill, CISCO and Wells Fargo.
Data Engineer
$95,000/year
If data fascinates you and you’re interested in a career path in the technology industry, the data engineering profession is a perfect fit for you. A challenging and exciting position that will keep you on your toes, this job of the future is gaining traction like never before.
Data engineers often work alongside data scientists and are responsible for taking information and presenting it in a way that’s easy to understand and analyze. Experienced data engineers have mastered a variety of skills, such as system architecture, programming, and interface, and sensor configuration. Their daily tasks can change often and may include building data pipelines, deploying predictive models, cleaning data, and much more. Usually, in this role, you will get to work on Big Data, compile reports on it, and send it to data scientists for analysis.
Day-to-day Tasks and Responsibilities:
- Data Mining for getting insights from data
- Conversion of erroneous data into a useable form for data analysis
- Writing queries on data
- Maintenance of the data design and architecture
- Develop large data warehouses with the help of extra transform load (ETL)
Data engineers can command a salary upwards of $95,000/year.
Top companies that Hunts for Data Engineers are Ernst & Young, LinkedIn, VISA, UBER, Hotstar, Furlenco, PayTM and JP Morgan Chase & Co.
Data Scientist
$1,05,000/year
Data powers today’s world. From unleashing innovations to improving decision-making processes, data holds the potential to unlock the success of every industry. The world, as we know it, has been transformed radically by data such that it’s almost crippling to function without the insights generated from data in any domain. And here’s where Data Scientists comes into the play.
A Data Scientist employs advanced data techniques such as clustering, neural networks, decision trees, and the like for deriving business insights. In this role, you will be the senior-most in a team and should have deep expertise in machine learning, statistics, and data handling. You will be responsible for developing actionable business insights after they get inputs from Data Analysts and Data Engineers. You should have the skill-set of both data analyst and data engineer. However, in the case of a data scientist, the skill sets need to be more in-depth and exhaustive.
Day-to-day Tasks and Responsibilities:
- Manage, mine, and clean unstructured data to prepare it for practical use.
- Develop models that can operate on Big Data
- Understand and interpret Big Data analysis
- Take charge of the data team and help them towards their respective goals
- Deliver results that have an impact on business outcomes
As a data scientist, you can earn as much as $1,05,000 /year.
Top companies that Hunts for Data Scientists are IBM, Walmart, BOSCH, SAP, DELL, VISA, Ericsson and KPMG.
Data Architect
$1,22,000/year
Data architects are senior-level professionals and are highly valued because of their sophisticated computer design skills to develop databases for organizations, allowing for the collection and analysis of big data. Data architects must be creative problem-solvers who use a vast amount of programming tools to innovate and design new solutions to store and manage data.
A database architect helps a company understand its strategic goals with regards to data management, and works with software designers and data engineers to develop plans for new integration of databases.
Day-to-day Tasks and Responsibilities:
- Implement effective database solutions and identify database structural necessities by evaluating client operations, applications, and programming
- Assess database implementation procedures to ensure they comply with internal and external regulations
- Prepare accurate database design and architecture reports, and oversee the migration of data from legacy systems to new solutions
- Monitor the system performance by performing regular tests, troubleshooting and integrating new features, and recommend solutions to improve new and existing database systems
If you have a degree in business and enjoy using data to highlight areas of improvement for companies, you may want to consider a career as a business analyst. The average salary for a business analyst is about $1,22,000.
Top companies that Hunts for Data Architects are BOSCH, SHELL, Amazon, Philips, Deloitte, Capgemini, Mindtree and Dell.
Final Thoughts
The field of data science continues to blossom into one of the most exciting disciplines in the corporate world. Today’s data scientists can leverage massive datasets to diagnose a business problem, apply algorithms to analyze the data, craft a solution, and finally make a business recommendation backed by the data. The opportunities for newly minted data scientists are growing fast. And whether you’re looking to run and monetize a data science effort, create third-party insight services, or strive for a more senior data science position, there is a unique path to data science mastery just waiting to be followed.
Also Read: Data Science, the Good, the Bad, and the… Future and The Difference Between Computer Science and Data Science.
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