Organizations rely heavily on data to make informed decisions and gain a competitive edge in today's data-driven world. This has led to huge rise in demand for professionals who can analyze and interpret data and provide insights that drive business growth. Data analysts play a vital role in this process as they collect, organize, and analyze large volumes of data to identify trends, patterns, and insights that inform business decisions. In this blog, we will understand the role of a data analyst in more detail, including their responsibilities, skills, and the tools they use to perform their job. If you are considering a career in data analytics or simply learning more about this field, this blog will provide a comprehensive overview of what a data analyst does.
Before we jump into the enormous data analyst world and its details, let us understand what exactly a data analyst is. Simply put, a data analyst is a troubleshooter and a convergent thinker who prepares and analyzes the data for the system, association, or company. The analyzed data provided by a data analyst plays a vital role in the organization's development; the insights help the company with plans and progressive benefits.
If the technical skill sets and the outmost interesting challenges interest you. This tech career of a data analyst is the best career choice for you. As per the statistics, job openings for data analysts are about to grow by 20 percent between 2022 and 2030. Approximately 12,000 new job openings are projected each year in data analysis. An entry-level analyst is expected to grab a starting salary of $70,000 to $90,000 annually. The expected salary for a senior position exceeds in the range of $100,000 to $130,000 annually.
What is a Data Analyst?
A data analyst specializes in collecting, organizing, and analyzing large amounts of data to rectify patterns and trends that can be used to define business decisions. They use various tools and techniques to extract insights from data, including statistical analysis, data mining, and machine learning algorithms. Data analysts work with different types of data, such as customer, financial, and market data, to provide insights that help organizations improve their operations, products, and services. They also create reports and visualizations that communicate their findings to stakeholders, such as executives, managers, and clients. A successful data analyst possesses strong analytical skills, attention to detail, and the ability to work with large amounts of data. They are also proficient in using data analysis tools such as SQL, Python, R, and Excel.
How to become a Data Analyst?
The core technical skills of computer science, engineering, and statistics can help you understand data analytics concepts. However, getting a degree and having a technical background is one of many ways to make a mark in the career path of a data analyst. According to the data analysis surveys it is measured that 60% hold a bachelor's degree, 15% have a master's degree, and 25% have chosen a very different path; they are the experts who learn from upskilling and updating themselves from various sources.
It is generally preferred and understood that the data analyst requires a little fundamental understanding of statistics, and calculus requires a Ph.D. in data science. It also helps if you are a technical expert and have tried to consume the knowledge from different sources, making you quite an exciting data analyst expert. A successful data analyst requires the following skills: data visualization, data mining, data cleaning, etc.
The most in-demand skills in the field of data science are:
- SQL is a database communication language
- Python or R are the statistical programming languages used for advanced data analysis.
- Machine learning language.
Further than the Degrees
If you are not a degree holder or do not have a formal education. How can you enter the league of data science and lead the stream of data analytics? Well, you can try by gathering experience and good exposure through certification programs, internships, or by participating in various upskilling programs. It will enhance your knowledge and give you practical experience in the data analytic field. Advanced technology helps you gain technical knowledge through online learning mediums or programs. In this competitive world, if you aspire to be a successful data analyst practice the following points:
- Develop a portfolio of your work to showcase your abilities and passion.
- Stay updated by watching the news to keep up with industry trends.
- Study the market and focus on leveraging industry predictions to hold a strong position for yourself as a data analyst.
- Always be a learner and be ready to grasp new skills.
As you know how to become a data analyst, understand the job description.
What is the Data Analyst job description?
Data analysts help companies grow and develop their business, understand the business and market structure, and make predictions to derive meaningful insights. The data analyst job description include :
1. Participate and collaborate with IT, management, and data scientist teams to orient the company goals
2. To extract data from all available sources
3. To filter the valuable data and discard the irrelevant data
4. Follow the standard statistical methods to perform the data analysis process
5. Identify and highlight the data trends and patterns in the data sets
6. Improve the business strategy
7. To present clear data visualization to the management and client
8. Maintain and create useful databases and data systems
9. Define the structure and prioritize the tasks as per project requirement
10. Make business predictions by identifying the market trends and patterns
11. To design and create the data dashboards, graphs, and visualizations
12. Keep track of the key performance indicators
13. Perform descriptive analysis, which consists of implementing data mining for business intelligence,
14. Diagnostic analysis, which mines the data to understand the reason for the action,
15. Predictive analysis, where you forecast the business aspects based on the available data,
16. The prescriptive research focuses on data optimization
17. Cognitive analysis that combines data with the artificial intelligence
What are the tools used by Data Analysts?
You must be very comfortable with the following tools as a data analyst. Every tool the data analyst uses performs an individual function that extracts important and accurate data. Hence, having skills and a good hand in the tools mentioned below will only outshine your career as a data analyst and help you have a successful career.
The vital data analysis tools are:
- Microsoft Excel
Microsoft Excel helps you clean and explore data and add advanced data analytics functions through data analysis tools like Power Query, Auto Filter, Power Pivot, and Power Maps.
- Google Sheets
Google Sheets allows users to edit, organize, and analyze different data types. It will enable collaborations, and multiple users can edit and format files in real-time, and any changes made to the spreadsheet can be tracked by history.
SQL is the programing language used to interact with many databases. Since most systems today capture the data using one or more databases (like MySQL, Oracle, Redshift, SQL Server, etc.), with SQL you can filter and extract data from these systems and then make the best use of the data.
Tableau inclines the organization more towards data-driven aspects. It is the most preferred and market-leading choice for modern business intelligence; this analytics platform makes it easier to explore and manage data and faster to discover and share insights that can change the entire business.
- Apache Spark
Spark is a data analysis tool that is an open-source framework that focuses more on interactive queries, machine learning, and real-time job process. It runs analytics on storage systems like HDFS or other popular stores like Amazon Redshift, Amazon S3, Couchbase, Cassandra, etc.
R is a popular open-source programming language used for statistical computing and data mining. It can be used for data analytics to identify patterns and build real-time data models.
Python is the best programming language widely used in data analytics, and it is easy to use, fast and manipulates data smoothly. Many data analytics activities are accurately performed, such as data collection, analysis, modeling, and visualization.
SAS is a prominent business intelligence tool that helps analyze, report, data mining, and predictive modeling data with the help of powerful visualizations and interactive dashboards.
KNIME is a data analytics platform with great insights and capability with maximum level of data and algorithm selection; KNIME Analytics platform has all the required functions to give the best results. It provides quick and accurate insights of the available data sets.
- Microsoft Power BI
Power BI is a collection of applications, software services, and linking couplers that combine to convert unrelated data into logical, visually appealing, constructive, and interactive visions. The relevant data can be an Excel spreadsheet or a collection of cloud-based and available hybrid data warehouses.
- Jupyter Notebooks
Jupiter Notebook is a web-based data analytics tool with an interactive development platform for code and data. It specializes in configuring and arranging workflow in data science, machine learning, and computer science.
What are the skills required for the data analyst?
Expertise in technical skills is the core requirement for a data analyst professional. Still, along with the technical skills, it is essential to explore your soft skills, which support your technical skills and enhance performance with a unique identity and better insights.
Here are some the skills required for the data analyst.
Soft skills that you need to perform with best of your abilities:
- Alert and prompt work nature
- Resilience and flexible
- Planning and Strategic Thinking
- Innovative approach
- Complex thinking
- Inquiring mind
- Business judgment
- Solution provider
- Presentation and Data Storytelling
The hard skills you need to shine as a data analyst are:
- Coding: SQL, Python, Java, Scala, and R
- Data merging: Informatica, Alteryx, and SAS
- Data visualization: Excel, Tableau, Power BI
- Machine Learning: TensorFlow, Keras, PyTorch, and Pandas
- Perform query for databases
- Data management
- Data cleaning
- Data Mining
- Fundamentals of statistics and mathematics
- Advance analytical skills
Professionals performing the data analysis can be recognized as :
- Medical and health care analyst
- Market research analyst
- Business analyst
- Business intelligence analyst
- Operations research analyst
- Intelligence analyst
- Research Analyst
- Finance Analyst
What is the average salary package in India?
Data Analyst is one of the most demanding and looked-after career options, and it is considered the highest pay offer job in the industry with multiple options. Several job opportunities are generated for data analysts because every industry demands regular data manipulation.
The average salary for a Data Analyst with 0-3 years of experience is around Rs. 5.2 Lacs per annum, while a professional with more than 3 years of experience is around Rs. 6.5 Lacs per annum. The average salary for a professional with more than 10 years of experience is around Rs. 20 Lacs per annum. With a master's certification and experience, you can get a better salary than the average mentioned here. Factors like location also affect the salary scale of a data analyst. A Data Analyst fresher in Pune might earn equal to somebody in Kolkata with 2-3 years of experience.
Let us take a look at some Data Analyst salaries based on location.
The tentitive salary of a Data Analyst in Mumbai is ₹5,50,600 p.a.
The tentitive salary of a Data analyst in Chennai is ₹6,20,500 p.a.
The tentitive salary of a Data Analyst in Bengaluru is ₹6,50,000 p.a.
The tentitive salary of a Data Analyst in New Delhi is ₹ 5,00,000 p.a.
List of top recruiters who hire the data analysts
Data analysis is a job requirement that holds a very strong position in the market in every field and industry. You have many options if you want to succeed and build a strong career in your preferred stream. Organizations belonging to various streams like Entertainment, healthcare, finance, banking sector, hotel & hospitality, education, Innovation and technology, manufacturing, etc, are constantly looking for data analysts to program and derive meaningful solutions for the organizations.
Data analysts are in great demand across all industries, and there is a good career path for those who want to move up the professional ladder. Many top organizations require data analysts to help them make better use of their data or provide the right insights to help them in their business activities. Some top companies hiring data scientists are Ernst & Young, IBM, Accenture, HCL, TCS, Deloitte and WNS, JPMorgan Chase, Ernst & Young, Wipro, Adobe, Flipkart, AIG, Vodafone, etc.