The broad field of Data Analytics involves the process of examining and analyzing raw data to draw conclusions from it. This process is executed with specialized systems and software. The results are processed by Data Analytic tools that use historical or real-time data. There are different forms of Data Analysis namely- qualitative data analysis, quantitative data analysis, predictive analytics, machine learning, and data mining.
Data Analytics has assumed great importance as a crucial part of industries. It helps organizations to make informed and calculated business decisions that are based on research and scientific data. This provides beneficial results for the company by improving its operational efficiency, and customer service.
By optimizing the efficiency of organizations, it gives them the advantage to succeed in this highly competitive world. It is also helpful for the R&D team of an organization, that can either reject or approve scientific theories, hypotheses and models. Data Analytics provides valuable insights to businesses that help them in making efficient and effective decisions.
Data Analytics plays an important role in the Financial sector which was one of the earliest adopters. The banking and finance sectors use this to assess risk and predict market trends. Evaluation of credit scores, prevention and detection of fraud, are also important uses of Data Analytics.
It is extremely useful in health informatics or providing crucial information for healthcare. The Data Analytics techniques also help in crime prevention and environmental protection that help improve our quality of life. Machine learning is being used by researchers to protect wildlife and improve drug discovery too.
The importance of Data Analytics is immense. With the collection of more and more data on a daily basis, new opportunities abound of applying Data Analytics to different aspects of business, daily life and science.
This blog will be your handy guide and reference point for all the important aspects related to the field of Data Analytics. This blog will discuss Data Analytics as a career, the skills required for a job in this field, the job opportunities that exist with short descriptions of each role along the indicative salaries.
With the world transforming to a global village with the internet and technology, this field is very promising as a career. Numerous opportunities exist across multiple and diverse industries. This field also offers the unique advantage like a few other professions, of remote work flexibility and self-employment. The demand for well-educated and talented data analytics professionals is currently higher than the supply. Some of the very good reasons that you may opt for a career in this field are because –
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Here are the required skills set for Data Analytics professionals:
Data visualization skills give a huge competitive advantage and these skills are in high demand. Through this, you can offer the company valuable insights related to its’s services and bottom line. Possession of this vital skillset attracts a high pay package too.
Employers in this field are offering positions that are both remote and onsite, In India and worldwide.
The projected growth for data analysts according to O *NET is 8% between 2019-2029.
The salary packages are influenced by the type of industry they work for and the geographical location.
Let us look at a few key roles and their job responsibilities along with an indicative salary.
This role is one of the most prominent ones. Data Scientist professionals, collect data and analyze it so that it can be communicated as insights that are actionable. They work with advanced analytics on complex data. They have to be well versed in programming languages like R and Python. They need a good knowledge of data visualization tools and other skills.
The average annual salary of a Data Scientist is ₹698,413. The entry-level data scientist can earn approximately ₹500,000 per annum. Data scientists who have experience of 1 to 4 years experience get around ₹610,811 per annum. (source: https://www.upgrad.com/)
Their job is focused on massive data sets and the objective is to optimize the infrastructure of the organization concerned with the various processes of Data Analytics. They ned a combination of good data visualization and programming skills, as well as a good experience in testing and developing solutions that are in line with the requirements.
The average annual salary of a Data Engineer is Rs.8,56,643.
(source: https://www.upgrad.com/)
As is evident from the title of the role, this job entails analysing the industry and company data to identify value and recommend opportunities. Every industry has Data Analysts, although the job titles may differ. For example, they may be titled Intelligence Analysts, Business Analysts, Healthcare Data Analysts etc. Although they may not be required to possess specific machine learning skills, they require SQL and programming skills. They also require data visualization skills, statistical knowledge and an ease with the data analysis work flow.
The average annual salary of a Data Analyst is ₹436988
(source: www.payscale.com)
This field combines the knowledge of Machine Learning/ Artificial Intelligence and Data Science. Machine Learning Engineers need to have skills in Python, Deep Learning and other programming languages They should also be well versed in data visualization tools and Big Data Analytics. Organizations like Accenture, JP Morgan, Apple Inc, and other reputed companies have good job prospects for these professionals.
A Machine Learning Engineer earns an average annual salary of ₹671,548. Those with less than 1-year experience earn around ₹500,000 per annum which is undoubtedly one of the highest entry-level salaries in India.
(source: https://www.upgrad.com/)
For any organization information and data are crucial especially in journalism. Useful data needs to be analysed and segregated from the bad data. Apart from a degree in journalism, these professionals need good technical skills in SQL and Python. They also need to be good in statistics and Data Visualization. Sound knowledge of other areas too, is needed to compare and analyze the useful data.
The average annual salary of a Data Journalist ranges from Rs 119,080 – Rs 836,614.
At the entry-level with less than 5 years of experience – the average annual salary is Rs 310,000.
Mid-career with 5 to 10 years of experience – the average annual salary is Rs 500,000
An experienced Journalist with 10 to 20 years of experience- the average annual salary is Rs 610,000
(source: https://school.careers360.com/articles/career-in-data-journalism)
. This job role deals with ensuring that the database is functioning properly.
Good knowledge of different database tools such as NoSQL, SQL, and
others are needed. They are responsible for monitoring and optimizing
performance. They ensure optimal health of the environment by implementing,
configuring and troubleshooting database instances.
The average annual salary of a Database Admin professional with less than one year of experience is ₹ 3 Lakh.
Those with 1 – 4 years of experience is ₹ 4.2 lakh.
During the middle of their career, Database Administrators earn an average of ₹ 8.4 lakh.
(source: https://www.upgrad.com/blog/dba-salary-in-india-for-freshers-experienced)
Financial Analysts work on data that is needed for investments, financial planning, and used for other financial decisions. These Data Analysts bring in their expertise in the Finance domain and employ various insights to interpret it.
They have a good working knowledge of Data Science, and financial assets like trading, bonds, stocks and other domain-specific instruments.
Their average annual salary for a Financial Analyst in India is ₹412592.
(source: www.Payscale.com)
In all organizations utilizing technology like IT services, Products, and other organizations, this is a key role. The Business Analyst’s role apart from having expertise in the chosen and specific domain is to do testing, installing, updating and maintaining the business process systems for the organization. These also include data processing and other tools. Having a functional rather than an in-depth knowledge of Data Science is very important.
The average annual salary of a Business Analyst at entry-level is between Rs. ₹606574.
(source: www.Payscale.com)
A Product Analyst is in charge of managing product-related processes, related to planning and analyzing new or existing products. They must possess a good knowledge of tools like R, Python, SQL and others in Data Science.
The average salary of a Product Analyst is ₹621701.
(source: www.payscale.com )
These professionals must possess a strong knowledge of Business Intelligence Tools. Raw data needs to be converted to valuable insights. They work in coordination with Analysts and Data Scientists. They create reports that are used in making important business decisions and also offer data visualizations by means of charts and graphs.
The average annual salary of a Business Intelligence Analyst is ₹589136
(source: www.payscale.com )
These professionals make smart decisions by using data for sales and marketing activities. They have expertise in data crunching and are also aware of the marketing activities of the business. The relevant data is used by them to identify opportunities, make predictions, and smoothen the processes. Their communication skills and technical skills need to be extremely good because they have to communicate and deal with client-facing teams.
The average annual salary of a Marketing Analyst is ₹485920.
(source: www.payscale.com)
This job role is very much in demand. They use data to understand and indicate potential investment opportunities and risks. Investment-related decisions are made based on the results they come up with. This role pays well since crucial decisions like stock predictions, exchange rates, commodities, and trading models are made based on their expertise.
The average annual salary of a Quantitative Analyst is ₹1015440.
(source: www.payscle,com)
This role is similar to a Business Intelligence Analyst’s role and they have to be well versed with data processing tools like SAP, TIBCO, Qlik, Tableau etc. A good knowledge of all the programming languages used for data analysis is also needed.
The average annual salary of a Data Visualization specialist is ₹787302.
(source: www.payscale.com)
A background in Data Science helps identify and mitigate system risks, records, and functions. These professionals identify problems, recommend the technology and system upgrades needed. They are responsible for ensuring that the operations run effectively and efficiently.
The average annual salary of a Functional Analyst is ₹ 1475000.
(source: https://in.talent.com)
The objective of organizations is to use their data for effective decision-making and insights. The Data System Developers are central to the database system. They build, design, and maintain an organization’s analytics infrastructure and data. They facilitate the procedure for Analysts, other developers and Data Scientists.
The average annual salary of a Database developer is ₹7,02,360
(source: https://in.indeed.com/career/database-developer/salaries)
The exciting field of Data Analytics as is evident from what we have read so far, offers a great career opportunity.
Do you feel you have the inclination and drive to pursue this course that introduces you to the fascinating world of Information Technology?
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