How to Become a Data Analyst in 2022
How to Become a Data Analyst in 2022
Here are five steps to consider if you’re interested in pursuing a career in data science:
- Earn a bachelor’s degree in a field with an emphasis on statistical and analytical skills, such as math or computer science
- Learn important data analytics skills
- Consider certification
- Get your first entry-level data analyst job
- Earn a master’s degree in data analytics What Does a Data Analyst Do?
A data analyst collects, processes and performs statistical analyses on large dataset. They discover how data can be used to answer questions and solve problems. With the development of computers and an ever increasing move toward technological intertwinement, data analysis has evolved. The development of the relational database gave a new breath to data analysts, which allowed analysts to use SQL (pronounced “sequel” or “s-q-l”) to retrieve data from databases.
Case Western Reserve University
Columbia Engineering
University of California, Berkeley
Georgia Institute of Technology
The University of Texas at Austin
Most jobs in data analytics involve gathering and cleaning data to uncover trends and business insights. The day-to-day data analyst job varies depending on the industry or company or the you consider your specialty. Data analysts may be responsible for creating dashboards, designing and maintaining relationship databases and systems for different departments throughout their organization and
Most data analysts work with IT teams, management and/or data scientists to determine organizational goals. They mine and clean data from primary and secondary sources then analyze and interpret results using standard statistical tools and techniques. In most cases, they pinpoint trends, correlations and patterns in complex data sets and identify new opportunities for process improvement. Data analysts must also create reports on their findings and communicate next steps to key stakeholders.
Data Analyst Qualifications
Skills Required for Data Analysts
- Programming Languages (R/SAS): data analysts should be proficient in one language and have working knowledge of a few more. Data analysts use programming languages such as R and SAS for data gathering, data cleaning, statistical analysis, and data visualization.
- Creative and Analytical Thinking: Curiosity and creativity are key attributes of a good data analyst. It’s important to have a strong grounding in statistical methods, but even more critical to think through problems with a creative and analytical lens. This will help the analyst to generate interesting research questions that will enhance a company’s understanding of the matter at hand.
- Strong and Effective Communication: Data analysts must clearly convey their findings — whether it’s to an audience of readers or a small team of executives making business decisions. Strong communication is the key to success.
- Data Visualization: Effective data visualization takes trial and error. A successful data analyst understands what types of graphs to use, how to scale visualizations, and know which charts to use depending on their audience.
- Data Warehousing: Some data analysts work on the back-end. They connect databases from multiple sources to create a data warehouse and use querying languages to find and manage data.
- SQL Databases: SQL databases are relational databases with structured data. Data is stored in tables and a data analyst pulls information from different tables to perform analysis.
- Database Querying Languages: The most common querying language data analysts use is SQL and many variations of this language exist, including PostreSQL, T-SQL, PL/SQL (Procedural Language/SQL).
- Data Mining, Cleaning and Munging: When data isn’t neatly stored in a database, data analysts must use other tools to gather unstructured data. Once they have enough data, they clean and process through programming.
- Advanced Microsoft Excel: Data analysts should have a good handle on excel and understand advanced modeling and analytics techniques.
- Machine Learning: Data analysts with machine learning skills are incredibly valuable, although machine learning is not expected skill of typical data analyst jobs.Data Analyst Responsibilities
A Day in the Life of a Data Analyst
The day-to-day for a data analyst depends on where they work and what tools they work with. Some data analysts don’t use programming languages and prefer statistical software and Excel. Depending on the problems they are trying to solve, some analysts perform regression analysis or create data visualizations. Experienced data analysts are sometimes considered “junior data scientists” or “data scientists in training.” In some cases, a data analyst/scientist could be writing queries or addressing standard requests in the morning and building custom solutions or experimenting with relational databases, Hadoop and NoSQL in the afternoon.
What tools do data analysts use?
Here are some other important tools data analysts use on the job:
- Google Analytics (GA): GA helps analysts gain an understanding of customer data, including trends and areas of customer experience that need improvement on landing pages or calls to action (CTAs)
- Tableau: Analysts use Tableau to aggregate and analyze data. They can create and share dashboards with different team members and create visualizations
- Jupyter Notebook system: Jupyter notebooks make it simple for data analysts to test code. Non-technical folks prefer the simple design of jupyter notebooks because of its markdown feature
- Github: Github is a platform for sharing and building technical projects. A must for data analysts who use object-oriented programming
- AWS S3: AWS S3 is a cloud storage system. Data analysts can use it to store and retrieve large datasets
- Data Analyst Job Outlook
Today’s data analysts should be prepared for a change. Analyst’s roles are increasingly becoming more complex. Experienced analysts use modeling and predictive analytics techniques to generate useful insights and actions. Then they have to explain what they’ve discovered to rooms of confused laymen. In other words, they have to transform themselves from data analysts into data scientists, which is much faster than the average job growth according to recent data from the Bureau of Labor Statistics. Because data analysts can fit in the majority of industries such as finance, healthcare, information, manufacturing, professional services, and retail – the growth of technology brings the growth of more analyst positions. We are collecting data at every turn, its organization, and implication of predictive analysis assists society in becoming a better version of itself.
Data Analyst Salary
Salary numbers are dependent on job responsibilities. A senior data analyst with the skills of a data scientist can command a high price.
Salaries for Data Analysts:
Average salary for entry-level data analysts: $83,750
Average salary for data analysts: $100,250
Average salary for senior data analysts: $118,750-$142,500
Interested in a different career? Learn more about bootcamps
If you’re interested in a career change or deepening your understanding of data analytics, you may want to consider a bootcamp. are fast-paced training in specific or that are offered in a variety of formats. offer intensive learning experiences that mimic the real world and learn how to create projects from scratch.
If you’re interested in a career in analytics, attending a may help prepare you for a new job opportunity. Data analytics bootcamps typically cover statistical analysis, analyzing data to uncover insights, using such as and other various tools data analysts may use on the job.
Another option is enrolling in a . Data science bootcamps typically cover more advanced analytical concepts as well as machine learning, natural language processing and If you’re unsure of which bootcamp to enroll in, consider your career goals and what you want to achieve in your existing role or new role.
Bootcamps can last a week to a few months depending on whether you enroll in a part-time or full-time program. You can choose an option that works with your schedule and learning goals. Some bootcamps offer prep courses and workshops to help ensure students’ success.
Data Analyst FAQs
What Should I Learn to Become a Data Analyst?
There are a variety of tools data analysts use day to day. Some data analysts use business intelligence software. Others may use programming languages and tools which have various statistical and visualization libraries such as, Python, R, Excel and Tableau. Other skills include:
- Creative and analytical thinking
- Communication
- Database querying
- Data mining
- Data cleaning
Is Coding Required to be a Data Analyst?
Some data analysts are proficient in programming languages while others may use analytics software or Excel to analyze data and provide insights. Whether or not coding is required for a data analyst typically depends on the job or the employer. Employers may or may not list programming as a required skill for data analysts in job listings. It is important to look at the job description and consider your background before applying.
Is Being a Data Analyst a Good Career?
If you’re weighing your options between becoming a , both occupations are projected to grow faster than average. Data analysts have a bright job according to O*NET OnLine (O*NET). The between 2019 and 2029. Data analysts salaries typically depend on where they work and their industry. According to O*NET, data analysts earned an average annual salary of $94,280 in 2019.
Data Analyst Roles and Responsibilities Include:
- Using automated tools to extract data from primary and secondary sources
- Removing corrupted data and fixing coding errors and related problems
- Developing and maintaing data base, data systems – reorganizing data in a readable format
- Performing analysis to assess quality and meaning of data
- Filter Data by reviewing reports and performance indicators to identify and correct code problems
- Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction
- Assigning numerical value to essential business functions so that business performance can be assessed and compared over periods of time.
- Analyzing local, national, and global trends that impact both the organization and the industry
- Preparing reports for the management stating trends, patterns, and predictions using relevant data
- Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data goverenece strategies.
- Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.
Another integral element of data analyst job description is EDA or Exploratory Data Analysis Project. In such data analyst projects, the analyst needs to scrutinize data to recognize and identify patterns. The next thing data analyst do is use data modeling techniques to summarize the overall features of data analysis.
Data Analyst Skills Required
A successful data analyst needs to have a combination of technical as well leadership skills. A background in Mathematics, Statistics, Computer Science, Information Management, or Economics can serve as a solid foundation to build your career as a data analyst.
Key Skills for a Data Analyst
- Strong mathematical skills to help collect, measure, organize and analyze data
- Knowledge of programming languages like SQL, Oracle, R, MATLAB, and Python
- Technical proficiency regarding database design development, data models, techniques for data mining, and segmentation.
- Experience in handling reporting packages like Business Objects, programming (Java script XML, or ETL frameworks), databases
- Proficiency in statistics and statistical packages like EXCEL, SPSS, SAS to be used for data set analyzing
- Adept at using data processing platforms like Hadoop and Apache Spark
- Knowledge of data visualization software like Tableau Qlik
- Knowledge of how to create and apply the most accurate algorithms to datasets in order to find solutions
- Problem-solving skills
- Accuracy and attention to detail
- Adept at queries, writing reports, and making presentations
- Team-working skills
- Verbal and Written communication skills
- Proven working experience in data analysis
Data Analyst Qualifications: What Does it Take
You need more than technical expertise to excel in a career in data analytics. A bachelor’s degree in a field that emphasizes on statistical and analytical skills is desired. Students from mathematics, statistics, computer science, or economics background usually have an edge in the data analyst However, a postgraduate course in data analytics like Data analyst Bootcamp can make you an industry-ready professional.
You would also need soft data analytics like:
- excellent communication and presentation skills
- ability for critical thinking
- creativity
- having a systematic and logical approach to problem-solving
- team working skills.
Data Analyst Salary: How Much Does a Data Analyst Make?
The data analyst salary depends on a number of factors like educational qualification, location, relevant experience, and skills set.
The average annual salary of an experienced data analyst can range from approximately $60,000 to $140,000. Financial and technology firms tend to offer higher pay-package than average.
The cross-market average data analyst salary is approximately $73,528
Data analysts typically move on to higher positions like senior data analysts, data scientists, data analytics managers, bussiness analyst , etc. Higher responsibilities come with a substantial pay rise as well. It is estimated that the average annual salary of data scientists starts at around $95,000, while that of analytical managers begins at approximately $106,000.
Watch the video below that will help you have an understanding of the various responsibilities, skills required, and the salary structure of top Data Analytics job roles.
Top Companies Hiring Data Analysts
If you are looking for a data analyst job, you can choose from more than 86 thousand open jobs worldwide. Shocking, isn’t it? This is mainly because nearly all industries benefit from data analysis. Today, the data analyst job description is branching off into various specializations like finance, healthcare, business, marketing, and e-commerce.
Presently, business intelligence companies have the highest number of job openings for data analysts in the US and Europe, followed by finance, sharing economy services, healthcare, and entertainment companies.
Some of the top global companies hiring data analysts include Amazon, Netflix, Google, Intuit, Facebook, Apple, CISCO Systems. Smaller companies include Focus KPI, Affinity Solutions, Norgate Technology, Financial giants like Paypal and Barclays are also hiring data analysts across various departments.
Get Started to Become a Data Analyst Today!
Are you wondering how to get a job as a data analyst? Let’s break down the career progression. It would be easy for you to bag an entry-level data analysis job if you have a certification from a top-rated data analysis program like the ones we offer here at Simplilearn. Even if you don’t have a background in data analysis, consider these to have a successful career as a data analyst.
- Earn a bachelor’s degree from a reputed University in a field that emphasizes on statistical and analytical skills
- Learn Data Analytics skills
- Consider earning a certificate in Data Science or Business Analytics
- Grab your first data analyst job
- Earn a master’s degree in data analytics, and you can become a data engineer and eventually a data scientist.
There is no shortage of jobs for skillful data analysts in whichever location you are. A data analyst career is a rewarding journey to embark on, irrespective of the industry you choose to work in.
Want to learn more about how to get a job as a data analyst? Prepare for Data Analyst interview questions with any of the data analysis courses offered by a top educational institution like Simplilearn, one of the leading online certification training providers in the world.
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