The Ultimate Data Analyst Career Path You Need in 2024

Data Analyst Career Path in 2024 | A step-by-step guide for a successful Data Analyst career in 2024 | ProjectPro

The Ultimate Data Analyst Career Path You Need in 2024
 |  BY Daivi

Your search for the ideal data analyst career path ends here! Whether you are transitioning into data science or a beginner looking for tips to become a successful data analyst, this blog has all the information you need to build a career in data analytics. You will learn how to find your ideal data analytics career path based on your skill set and educational background.

Data Analyst Career Path

Data analytics is one of the most highly-demand career fields due to the industry’s inclination toward data-driven initiatives. Data analysts hold leading positions in tech, eCommerce, consulting firms, government sector, pharmaceutical, and manufacturing industries. Is data analyst a good career?


Customer Market Basket Analysis using Apriori and Fpgrowth algorithms

Downloadable solution code | Explanatory videos | Tech Support

Start Project

According to Fortune Business Insights, the global big data analytics market will likely grow at a CAGR of 13.2 percent to USD 549.73 billion by 2028. Due to the evolving technological landscape and emerging business challenges, most companies are searching for solutions that ensure higher business revenues and lower operating costs. Businesses employ data scientists, analytical frameworks, datasets, and various tools and techniques to leverage vast amounts of data for their profit. This leads to a significant need for qualified data analytics and data science experts, machine learning experts, data analysis specialists, or anyone with exceptional data analysis skills. All these job titles vary, i.e., they have different job descriptions depending on the responsibilities they need to perform at an organization. The Bureau of Labor Statistics (BLS) predicts that between 2018 and 2028, demand for data analysts will increase by 26%. The growing demand for these professionals and the lucrative salary for these job titles is another solid reason for pursuing a career in the data science and data analysis industry. Entry-level analysts earn an average salary of $78,202 per year, while senior analysts can earn up to $92,495 per year in the US. All these reasons are good enough for anyone to consider pursuing a data analyst career path. However, if you’re still not convinced how hot the market is for analytic careers, read on to understand the analytic job trends and rewarding perks that come with them.

 

ProjectPro Free Projects on Big Data and Data Science

Data Analyst Career Path- Unleashing the Job Trends and Salaries

The big data market will likely be worth $229.4 billion by 2025. What does this mean? The demand for data analysts is increasing dramatically along with the data market. According to the World Economic Forum report, data and AI is one of the seven high-growth emerging professions with the highest growth rate at 41% annually. Businesses consider data analytics to be one of the most challenging fields to recruit for, and as it is, there aren't enough data analyst professionals to meet this need. There are over 461,000 data analyst job openings in the US, ranging from junior or entry-level to senior analysts.

On the other hand, there are over 111,000 data analyst job openings in various industries in India. The growing number of data analyst jobs indicates an exceptionally high demand for data analyst professionals worldwide. So, it is fair to say that data analysts will continue to be in demand for quite a long time soon.

The number of job openings for data analysts in the US

The number of job openings for data analysts in India 

With such a massive demand for data analysts, there is another primary reason why you should aim to become a successful data analyst in 2022. In the USA, the annual average pay for a data analyst is $67,196. Data analysts at the entry-level level can expect to make $46,734 a year, while those with the highest experience earn up to $106,770 per year. On the other hand, the average annual pay for data analysts in India is ₹733,182. The starting salary for entry-level data analysts is ₹408,875 per year, while the average yearly salary for experienced data analysts is ₹15,37,500.

The average annual salary of a data analyst in the US

The average annual salary of a data analyst in India 

Below are the annual average salaries for a few other data analyst titles in the US according to platforms like Indeed, talent, Glassdoor, etc.

  • Data Analytics Manager- $84,373

  • Healthcare Data Analyst / Clinical Data Analyst- $90,384

  • Data Analytics Directors- $149,326

  • Chief Data Officer- $181,797

  • Business Analyst- $82,891

  • Machine Learning Engineer- $140,189

  • Data Scientist- $126,142

  • Financial Analyst- $70,002

Typical Data Analyst Career Path - What Should You Know ?

Six essential steps to become a successful data analyst 

You must be wondering- Who are data analysts? What do they do?

A data analyst gathers, organizes, and analyzes data statistically. Using precise calculations and suitable algorithms, they support business decisions and enable organizations to generate higher revenues. A career in data analytics is an excellent option if you like using data to resolve complex problems and have strong critical reasoning skills.

So, do you think you are convinced to build a successful career in data analytics? If yes, it’s time for you to check out what a typical data analytics career path looks like. Let us dive right into it!

The first step in data analytics involves acquiring the essential skills and expertise for the specific job role. Data analysts mainly collect raw data from various data sets or databases and perform data mining and wrangling processes. Their next task is analyzing data using statistical tools and machine learning algorithms. Data analysts must possess the right balance of technical skills and soft skills.

Here is a breakdown of the technical skills essential for any individual to get started with a career in data analytics.

i. Knowledge of Programming Languages (Python/R)

If you wish to build a career in data analytics or data science, you must possess proficient knowledge of programming languages. Python and R are two prevalent languages in the field of data science and analytics. Both languages offer data collection and processing frameworks that allow you to work efficiently with data sets. A career in data analytics is easier if you are proficient in either of the two languages.

Projects using Python/R for Data Analysts

ii. SQL

An expert in data analytics must continually have access to data to obtain it from its storage location or update it as needed. Most data analysts should be familiar with SQL, or Structured Query Language, as it is the most popular database language in the industry. Almost every business requires a SQL expert, whether it's to manage and store data, combine several databases, or build new database structures. The average compensation for an individual with advanced SQL abilities is around $81,000. 

Projects using SQL for Data Analysts

Here's what valued users are saying about ProjectPro

ProjectPro is an awesome platform that helps me learn much hands-on industrial experience with a step-by-step walkthrough of projects. There are two primary paths to learn: Data Science and Big Data. In each learning path, there are many customized projects with all the details from the beginner to...

Jingwei Li

Graduate Research assistance at Stony Brook University

I think that they are fantastic. I attended Yale and Stanford and have worked at Honeywell,Oracle, and Arthur Andersen(Accenture) in the US. I have taken Big Data and Hadoop,NoSQL, Spark, Hadoop Admin, Hadoop projects. I have been happy with every project. They have really brought me into the...

Ray han

Tech Leader | Stanford / Yale University

Not sure what you are looking for?

View All Projects

iii. Data Visualization

Data visualization is the skill of conveying one's insights graphically, such as through charts, graphs, or other representations. It can significantly impact how your data is interpreted and used by clients/businesses. Analysts often convey their findings clearly and simply by using eye-catching, high-quality charts and graphs. Several visualization tools available in the market, such as Power BI, Tableau, etc., offer a user-friendly interface and are easy to understand.

Projects using Data Visualization for Data Analysts

iv. Machine Learning and Natural Language Processing

Although not every analyst uses machine learning (ML) and natural language processing (NLP), it is necessary to understand the concepts and techniques to succeed in the field. A combination of machine learning and natural language processing algorithms and methods might be required to perform data processes efficiently.

Projects using ML and NLP for Data Analysts

v. Microsoft Excel

The first thing that pops in your mind when you think of Excel is probably a spreadsheet, but this tool has much more analytical ability. Even though a programming language like R or Python is better at handling a large data set, advanced Excel techniques like creating Macros and using VBA lookups are still more beneficial for faster analytics.

Learn more about real-world big data applications with unique examples of big data projects.

The next step in the data analytics career path is to gain a clear understanding of the day-to-day responsibilities of data analysts. Data professionals must understand what a data analyst's job entails and how it varies from other roles if they want to build a career in the industry. Data analytics is the process of analyzing raw data to get valuable, practical insights. These insights support the decision-making process in businesses, and data analysts are responsible for generating these insights.

The goal of data analysts is to provide specific solutions to problems or concerns that are significant to the business. Their task includes collecting data from relevant sources (databases) and cleaning this raw data using various data cleaning and processing techniques. They perform data analysis on the processed data to generate valuable insights.

Some of the typical responsibilities associated with a data analysis career path are -

  • Building and managing databases and data systems as necessary.

  • Identifying and resolving code errors that make these databases functional.

  • Performing data mining and data wrangling on primary and secondary data sources.

  • Create detailed reports describing trends, patterns, and forecasts using relevant data.

  • Analyzing data sets using statistical techniques and paying close attention to trends and patterns may be helpful for diagnostic and predictive analytic tasks.

  • Develop the necessary documentation so stakeholders may understand the phases of the analysis process and duplicate it if necessary.

  • Collaborating with other data team members, such as data scientists, data engineers, and analytics engineers.

The third step in a data analytics career path is getting your first data analyst job. You can either take up a role of a junior analyst or an entry-level data analyst. You must have prior industry experience to be eligible for an entry-level position. This includes knowledge of statistical analysis, programming languages, data manipulation, data cleaning, and data visualization. You will collaborate directly with company stakeholders and leverage your insights to impact their decisions. Employers usually demand that an entry-level data analyst must have a solid knowledge of data management systems and a thorough understanding of statistical principles.

You can begin to consider your next step once you've worked as a data analyst for one or two years. Highly experienced analysts typically acquire senior data analyst, analytics manager, or chief data officer positions. Such positions will require you to take charge of the data operations within your company and perhaps even oversee a team of junior analysts. Senior data analysts work with complex data systems to identify patterns and trends in the present and the future. Additionally, as a senior data analyst, you will create analytical reports, keep track of key performance indicators, and interact with other stakeholders. Senior data analysts execute competitive analysis and lead surveys for their clients in addition to these tasks. Most organizations seek candidates with at least five years of experience for senior roles.

Data Analysts can choose to work in various roles and industries. Their career paths can lead them to the banking/finance industry, sales and marketing industry, or even the healthcare industry. Their job titles also vary depending on their specialization.

Here are some of the data analyst roles that you can go for as a data analyst-

  • Financial Analysts- They are responsible for using data to manage financial risks, find revenue opportunities, and determine investment strategies.

  • Industry Research Analysts- Sometimes known as marketing analysts, they are responsible for studying market trends to define potential consumers, price points, and product and service offers.

  • Healthcare Analysts- They are responsible for using information from patient surveys, cost reports, and medical records to assist physicians in enhancing the standard of service.

Industry Specific Business Data Analyst Career Path

This section will cover the data analyst career paths depending on the various industries that hire these analysts. The career paths vary from the healthcare industry to the finance industry. Each one of these data analyst career paths will have the essential skills and responsibilities associated with the specific job role. Also, you will find sample job descriptions for each of these career paths that will help you understand the roles and responsibilities for each job role.

Various data analytics careers in different industries

Big data analytics for the pharma industry leverages various cutting-edge innovations in cloud computing, machine learning, etc.) to generate insights and help businesses develop effective strategies in the global market. Healthcare Data Analysts can identify trends that can enhance clinical treatment, lower expenses, and make healthcare facilities operate more effectively and efficiently. These analysts often work with clinical data to improve overall treatment quality, lower health risks, and even train artificial intelligence to detect cancer. They often perform medical image analysis using computer vision technology on X-ray, MRI, CT, PET, and ultrasound reports to create AI-based solutions for identifying anomalies. They also aid insurance companies in better understanding their premiums by using data from insurance claims. In some cases, these clinical analysts seek to speed up the discovery and development of potential treatments for various diseases.

Here is a job description for a clinical analyst in a pharma company.

A clinical analyst job description showing various essential skills and responsibilities 

Leading pharma companies, including Johnson & Johnson, Pfizer, Roche, Novartis, and others, hire healthcare data analysts to conduct in-depth competitor analysis and boost internal operations using data-driven insights.

If you want to become a Healthcare Data Analyst or Clinical Data Analyst, you need to hone the below skills and will have the following day-to-day responsibilities-

Skills Required for a Healthcare Data Analyst Career Path

    • A Bachelor's degree in computer science, life science, or a related field.

    • Experience working in a pharmaceutical, biotech, CRO, or regulatory agency for at least two years, focusing on developing data gathering and integration strategies.

    • Possess knowledge in relational database design, Oracle, PL/SQL, SAS, Java, and database programming.

    • Technical proficiency and database relational experience (e.g., Oracle InForm, Oracle DMW, MS SQL Server, or MS Access).

    • Exceptional written and verbal skills for decision-making, persuasion, negotiation, and project management.

    • The analysis of clinical trial data requires knowledge of the drug manufacturing process and data analytics.

    • Understanding critical data standards and regulatory obligations; organizations prefer those with CDISC expertise and experience.

Key Responsibilities of a Healthcare Data Analyst Career Path

    • The Data Analyst, a member of the Data Monitoring and Management (DMM) group, is in charge of developing significant clinical databases and offering advice on clinical database technologies.

    • Designing, creating, and maintaining clinical databases, verifying the accuracy of clinical data, and using standards to encourage uniformity in asset/submission data

    • The Clinical Data Analyst will frequently be responsible for training less experienced employees in database technology and practices.

    • In a particular therapy area, he or she might act as a subject matter expert for creating ECRFs and clinical databases.

Every organization relies on marketing data analysts to succeed in the industry. Both quantitative and qualitative market analysis are areas of expertise for marketing data analysts. They carefully review the market data, analyze the results, and assist in various business functions, such as helping businesses understand how their marketing strategies impact their growth. The ultimate goal of a marketing data analyst is to use data to achieve an ideal and feasible decision regarding market strategies. A marketing analyst evaluates and interprets an organization’s data using various analytics and machine learning techniques. Additionally, they use data visualization to create detailed reports on Key Performance Indicators and the ROI of various marketing campaigns. A marketing analyst also uses analytics to track email campaign metrics, such as delivery, open, click-through, etc.

Below is a job description for a marketing data analytics job role.

A marketing analyst job description showing various essential skills and responsibilities 

Various leading companies hire marketing analysts to accelerate their market growth. Salesforce works with marketing analysts to develop analytics tools and advertise their software. Google hires many marketing analysts to drive its internal business operations and expand its marketing platform.

If you want to become a Marketing Data Analyst, you need to hone the below skills and will have the following day-to-day responsibilities-

Skills Required for a Marketing Data Analyst Career Path

    • Bachelor of Arts in a quantitative subject, such as business, statistics, mathematics, economics, or a similar topic.

    • SQL programming skills are necessary. Knowledge of programming languages (Python and R), or at least a desire to learn and acquire these skills.

    • Ability to create efficient Tableau dashboards, reports, and data visualizations.

    • Knowledge of complex quantitative analysis, including but not limited to regression, classification, clustering, and time-series studies, and proficiency with exploratory data analysis.

    • A marketing analyst must be familiar with modern data science tools and basic data warehousing and database modeling knowledge.

    • Ability to collaborate efficiently with data science and engineering partners to address the company's data needs, turning business requirements into analytical needs.

Key Responsibilities of a Marketing Data Analyst Career Path

    • Provide data and customer insights to the marketing team.

    • Provide the marketing staff insights to help them understand and achieve their quarterly strategic objectives.

    • Analyze how marketing efforts affect consumer success and future behavior.

    • Accountable for all aspects of business analytics activity, including data quality, analysis, visualization, and presentation of outcomes and deliverables.

    • Assessing usage metrics and establishing business reasons for trends and patterns in customer lifecycle behavior.

    • Gather, examine, and understand transactional and advertising campaign performance data.

    • Create data models and analytical tools for ongoing market analysis, benchmarking, audience segmentation, and trend analysis.

    • Design, execute, and analyze A/B testing to improve the effectiveness of marketing efforts.

Wondering if Spark is suitable for Big Data? Find out by working on Apache Spark Projects that will help you understand the fundamentals of Spark.

Financial analysts are responsible for preparing budgets, keeping track of expenses, and managing the organization's finances in various ways. Financial data analysts gain insight into the pricing of mutual funds, equities, bonds, variable annuities, and other critical economic assets. A financial analyst uses spreadsheets and statistical tools for analyzing financial data, identifying patterns, building portfolios, and making forecasts. These data professionals analyze various kinds of economic data, including details about customer transactions, financial statements, credit scores, loan details, etc., to assess the financial risks in a company.

A financial analyst job description showing various essential skills and responsibilities 

Banks such as State Bank of India, First Tennessee Bank, etc., hire financial analysts to optimize their market strategies using predictive analytics, create various analytical data models to digitize their loan disbursement process, reduce money laundering activities, and other different purposes.

If you want to become a Financial Data Analyst, you need to hone the below skills and will have the following day-to-day responsibilities-

Skills Required for a Financial Data Analyst Career Path

    • Bachelor's degree in computer science, business, statistics, mathematics, economics, or a similar subject

    • Certifications in Google Big Query, Microsoft Power BI, or other relevant certifications

    • 4+ years of experience in software engineering.

    • 4+ years of practical experience with Power BI dashboards.

    • 4+ years of experience in the finance industry.

Key Responsibilities of a Financial Data Analyst Career Path

    • Extract data from familiar databases, build data pipelines, and transform the data into an appropriate format using suitable approaches.

    • Learn about the latest analytics and data science developments.

    • Contributes to conceptual, physical, and logical data models by analyzing complex data items, systems, data flows, dependencies, and relationships.

    • Create training materials for end-users and train them on data modeling.

    • Write code using the suitable programming language and the necessary combination of business, technical, and data requirements to create the desired solution and application features.

    • Build business cases for projects with potential returns on investment or cost reductions.

Access to a curated library of 250+ end-to-end industry projects with solution code, videos and tech support.

Request a demo

The HR analyst plays a significant role in gathering, organizing, analyzing, and reporting on HR processes and data in any organization. These analysts are responsible for gathering and assembling HR metrics and data from various sources, such as the payroll outputs and human resource information system (HRIS), management and employee surveys, employment records, government labor statistics, etc. HR analysts review applicant and employee data and upload it into relevant HR databases. Additionally, they are in charge of designing and delivering specialized training sessions and presentations on HR-related subjects to the entire organization.

Check out this job description for the position of an HR data analyst-

An HR analyst job description showing various essential skills and responsibilities 

Leading companies like Reed and Pepsico recruit HR analysts to manage and update their HR systems, develop methods to communicate workforce insights to their HR leaders, and push workforce data and insights into actions.

If you want to become an HR Data Analyst, you need to hone the below skills and will have the following day-to-day responsibilities-

Skills Required for an HR Data Analyst Career Path

    • A bachelor's degree in business, human resources, industrial/organizational psychology, statistics, or similar field, AND 3+ years of experience in business analytics, human resources, or other business-related roles OR a master's degree in business, human resources, industrial/organizational psychology, statistics, or a related field AND 2+ years of experience in business analytic roles OR 5+ years of experience in business analytics, human resources, or other business-related functions.

    • 3+ years of practical knowledge with BI tools (Excel, Power Pivot, Power BI, Tableau, SQL, etc.).

    • 3+ years of HR-related work experience.

Key Responsibilities of an HR Data Analyst Career Path

    • Create a flexible analytical strategy, and offer senior clients company-wide actionable insights through data, infographics, and powerful storytelling tactics.

    • Convert facts into brief, practical business insights, usually in collaboration with others who may assist you in telling a thorough narrative.

    • Contribute to high-impact business decisions by utilizing various scalable tools and analytical methods.

    • Communicate regularly with product groups while keeping up with the latest features and technical advances on the product roadmap.

    • Drive infrastructure requirements for projects ranging from ad hoc business analysis to accurate data collection, processing, and reporting.

This section will cover the data analyst career paths depending on the level of work experience. The career paths begin from entry-level positions and go up to senior or managerial level roles. Also, these career paths will have the essential skills and responsibilities associated with the specific job role.

Different levels of data analytics career paths by experience level

An entry-level data analyst is usually a part of a more extensive data analytics or data science team. In most cases, their duties entail performing tasks that, when combined, are essential to the data processes on a larger scale.

Let us look at an entry-level data analyst's preferred skills and responsibilities.

Skills Required for an Entry-Level Analyst

Apart from a quantitative degree (in computer science, economics, mathematics, engineering, or a related field) and at least one/two years of experience in an analytical or data-driven profession, you must possess the following skills to work as an entry-level data analyst or junior data analyst.

    • Excellent knowledge of data lineage (including data sources, metrics' aggregation, and the company's usage, interpretation, and response to the resultant business intelligence).

    • Proficient knowledge of one or more business intelligence and data visualization tools (such as Excel, Tableau, QuickSight, MicroStrategy, and PowerBI).

    • Basic knowledge of data science or statistical tools, including Tableau, MicroStrategy, SAS, etc.

    • Advanced knowledge and expertise in database querying (SQL).

    • Understanding of statistics and practical knowledge of statistical analysis software, particularly Excel.

Responsibilities of an Entry-Level Analyst

Following are a few primary responsibilities of a Data Analyst in an entry-level position-

    • Create and maintain essential data artifacts that satisfy business needs, including ETL, data models, and reports.

    • Detect data anomalies by using analytics and metrics visualization tools.

    • Assess metrics' trends and divide metrics into suitable dimensions to reveal other dynamics.

    • Enhance your awareness of the company's technical and operational details (such as necessary dependencies, company goals, the generation of valuable business insights, etc.) and engage in productive discussions.

Average Junior Data Analyst Salary: Junior data analysts typically make $78,202 per year in the United States and ₹3,06,244 per year in India.

Senior data analysts must possess more than just strong analytical skills. As senior team members, they can supervise junior analysts who are just starting their careers. A senior analyst (or chief data officer) is responsible for ensuring that his/her entire team adheres to company standards, staying ahead of new trends and certifications, learning new techniques and practices, and taking on managerial duties to lead the department. Becoming a senior data analyst takes more than just a bachelor's degree in data analysis and a few years of work experience. Senior analysts often require advanced education and a continually growing knowledge of the data analytics industry.

Below are the skills required and responsibilities of a senior data analyst.

Skills Required for a Senior Data Analyst

    • MS in computer science or a related discipline.

    • Over five years of experience in quantitative research and analysis.

    • Proficient data analysis skills in SQL.

    • Excellent programming skills, i.e., a solid knowledge of programming languages like Python/R for data visualization, data analytics, and data modeling.

    • Understanding business challenges and the ability to build technically sound, data-based solutions that are flexible, actionable, and effective.

Responsibilities of a Senior Data Analyst

    • Deliver insights, reports, and practical recommendations by using statistics to drive the success of your clients and your organization.

    • Build cutting-edge and innovative solutions in collaboration with clients and supply account teams to boost company revenue and maintain alliances.

    • Collaborate with other engineering and product teams to gather client feedback, test theories, and analyze the impact of product rollouts.

    • Proactively discover projects that will affect the company’s income, define the project's goals and objectives, and suggest a strategy to achieve those goals.

Average Senior Data Analyst Salary: Senior data analysts typically earn $92,495 per year ($5,000 cash bonuses annually) in the United States and ₹7,28,948 yearly in India.

Data scientists, data architects, data engineers, statisticians, data analysts, business analysts, and database administrators are standard members of data science teams. The data analytics manager gathers all of this expertise, directs the team's efforts, and develops the team's overall skill set to keep projects moving forward smoothly. The data analytics manager communicates with team members to ensure that each one clearly understands their role in the project before translating insights and proposals to other company stakeholders.

Here are some essential skills and responsibilities for a data analytics manager.

Skills Required for a Data Analytics Manager

    • A postgraduate degree in data and technology management or relevant professional experience.

    • Five to ten years of experience in the finance industry with data management and business intelligence.

    • Thorough knowledge of analytics and BI tools, including SQL, Alteryx, Power BI, and Excel.

    • Solid understanding of advanced analytics and statistics, as well as predictive modeling.

    • Efficient analytical skills include identifying, gathering, organizing, analyzing, and interpreting trends or patterns in large, complicated data sets.

    • Excellent project management and leadership skills.

Responsibilities of a Data Analytics Manager

    • Manage and administer the Data Analytics Team's operational activities directly and through staff.

    • Ensure all supported internal and external clients receive high-quality service and efficient securities operations.

    • Ensure compliance with applicable laws while implementing corporate policies and processes.

    • Manage operational risks associated with the area of responsibility effectively, including identifying gaps and developing operational controls to reduce risks and the organization's financial exposure.

Average Data Analytics Manager Salary: In the United States, a data analyst manager earns an average salary of $84,373 a year, whereas, in India, it is ₹11,35,866.

Most people who work as data analytics consultants have various specialized skills relevant to the position and industry. Data analytics consultants can offer suggestions for corporate planning by having a solid grasp of data management systems and strategic analytical abilities. These experts use the outcomes of their analysis to forecast upcoming results and aid in making business strategies and decisions. For instance, they might identify market trends or find potential growth prospects in new regions.

Below are some essentials skills and responsibilities for the role of a Data Analytics Consultant.

Skills Required for a Data Analytics Consultant

    • Solid understanding of the programming languages like Python, R, etc., for data analysis, storage, and tracking.

    • Proficient knowledge of databases such as SQL, BigQuery, etc., and analytical tools like Google Analytics, DataStudio, Smartlook, etc.

    • Analytical abilities in the areas of web analytics for data-based decision-making.

    • Must possess strategic thinking skills and leadership qualities.

    • Teamwork orientation and cross-functional communication skills are crucial for this position.

Responsibilities of a Data Analytics Consultant

    • Be a partner to your clients by interacting with them, offering advice, and supporting them while they undergo a digital transformation.

    • Analyze and build innovative methods and approaches for how clients collect data (from both online and offline data sources).

    • Plan and develop marketing strategies based on data that ensure support throughout monitoring and optimization stages depending on campaign goals.

    • Analyze data from various sources to look for opportunities, and convert it into actionable insights and recommendations helpful to stakeholders.

    • Supervise the use of data and analytics for client process and campaign optimization.

Average Data Analytics Consultant Salary: The average annual income for a data analytics consultant in the USA is $101,350, whereas it is ₹875,000 in India.

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization

It’s Time To Choose the Right Data Analyst Career Path Now!

The data analytics industry is so exciting because of the nonstop thrill of identifying and resolving challenges, which is why most data analytics experts find their job satisfying. Who doesn't love being able to work in a career field they are passionate about, make a great living, and determine their path to professional growth?

Once you are adept in the fundamentals of data analysis, you can build a career that reflects your interests and abilities. However, the foundation for every career path for a data analyst is the same: acquiring the necessary knowledge, skills, and hands-on experience while developing a strong professional portfolio. Check out the ProjectPro repository, which offers more than 250 projects on Data Science and Big Data that will help you build all the skills you need in a data science career. You also get a ‘Live Cloud Labs’ feature for the projects and a complete overview of all the projects to help you better understand the solutions.

FAQs on Data Analyst Career Path

Yes, data analyst is a good career since there is a constant growth in the demand for data analytics professionals worldwide. Data keeps growing exponentially, indicating that there will be more demand for data analytics experts in the future.

Here are a few steps you need to follow to build a successful data analyst career

  • Acquire the necessary skills and educational qualifications.

  • Gain solid hands-on experience by working on real-world industry-level projects.

  • Build an impressive data analyst portfolio showcasing your skills and expertise.

  • Get an entry-level job in the analytical field and slowly move up the ladder to senior roles.

If you want to become a data analyst without experience, you need to gain the essential technical, and non-technical skills and the minimum education required. Also, try working on good data analytics projects that enhance your skillset.

Becoming a data analyst is not hard if you follow the right career path and work hard to achieve your target. It might be challenging for some individuals, but you can easily overcome the challenges by focusing on your goals.

Yes, you can become a data analyst in 3 months. You need to utilize this period for acquiring essential skills such as programming (Python/R), data visualization (Power BI/Tableau, database management systems (SQL, NoSQL, etc.), and Microsoft Excel. Also, try and save some time for practicing some industry-level data analytics projects, as this will help you build a strong portfolio for data analyst jobs.

A data analyst does not require an advanced level of coding knowledge. He/she just needs basic coding skills that will be helpful in data analysis and processing.

Yes, you need a degree to become a data analyst. The majority of entry-level positions for data analysts need candidates to hold a Bachelor's degree as a prerequisite in either of the following subjects- Finance, Economics, Mathematics, Statistics, Computer Science, and Information Management.

The annual average salary for a data analyst in the USA is $67,196. On the other hand, data analysts in India make an average salary of INR 733,182 per year.

 

PREVIOUS

NEXT

Access Solved Big Data and Data Science Projects

About the Author

Daivi

Daivi is a highly skilled Technical Content Analyst with over a year of experience at ProjectPro. She is passionate about exploring various technology domains and enjoys staying up-to-date with industry trends and developments. Daivi is known for her excellent research skills and ability to distill

Meet The Author arrow link