Data Analyst Job Description | Salary, Skills, Qualification

Data analyst job description continues to evolve and in the last ten years, data has changed how our world looks. Nearly 2.5 quintillion bytes of data are made every day around the world. This includes all the emails, text messages, and YouTube videos we send and watch.

Both big and small businesses have to deal with a lot of data, which depends on how well they can make sense of it. This is what a data analyst does. They figure out what the numbers mean and turn them into helpful information businesses and organizations can use to make crucial decisions.

Organizations in all fields rely increasingly on data to make critical business decisions like what products to make, which markets to enter, what investments to make, and which customers to target. They also use data to find areas of the business that are weak and need to be fixed.

Because of this, data analysis has become one of the most sought-after jobs in the world, and the most prominent companies are looking for data analysts. The salary and perks of a data analyst only show how much people want to do this job, which is likely to keep growing by leaps and bounds.

So, if you have the skills to become a data analyst, you would be foolish not to take advantage of this situation. In this article about the “data analyst job description,” we’ll look at all the different parts of this job and then talk in depth about what a data analyst does.

What Is Data Analysis?

Data analysis is the process of cleaning, analyzing, interpreting, and showing data in different ways using different methods and business intelligence tools. Data analysis tools help you find key insights that can help you make better, more successful decisions. It is about turning raw data into statistics, information, and explanations that make sense.

What do they do?

A data analyst looks at groups of customer information to find ways to solve problems. A data analyst also tells management and other important people about this information. These people work in various fields, including business, finance, criminal justice, science, medicine, and the government.

A data analyst knows how to take raw data and turn it into information and insights that can be used to make business decisions.

Types of Data Analysts

Medical and Health Care Analyst

As the job title suggests, medical and healthcare data analysts use information from various sources to help improve healthcare quality. Most of the time, they focus on the business side of medicine, like improving patient care or making operations easier.

Market Research Analyst

The Market research analysts gather and analyze information about customers and competitors. Market research analysts determine how the market performs to predict how well a product or service will sell. They help businesses determine what products people want, who will buy them, and how much they will pay.

Business Analyst

A Business analyst use data to make business insights and push for improvements in companies and other groups. Business analysts can find problems in almost every part of a business, such as IT processes, organizational structures, and team member development. As companies are always trying to improve their overall efficiency and cut costs, business analytics is becoming increasingly important in how they run.

Business Intelligence Analyst

A business intelligence analyst (BI analyst) looks at data and other information to help companies make sound business decisions. They may collect, clean, and analyze data like a company’s sales, revenue, market intelligence, or indicators of consumer engagement. BI analysts may also have to make tools and data models to help people see or keep track of data.

Operations Research Analyst

Operations research analysts are high-level problem-solvers who use advanced techniques like optimization, data mining, statistical analysis, and mathematical modeling to develop solutions that help businesses and organizations work better and cheaper.

Intelligence Analyst

Analysts of intelligence look at information and data to find security problems and ways to fix them. Statistics from inside and outside the company, databases, and field reports are all types of information sources. Analysts need to be good at research, understanding, and analysis to gather information and develop action plans.

Data Analyst Job Description: Roles and Responsibilities

A data analyst’s job is to organize information about sales numbers, market research, logistics, linguistics, and other things people do.

They use their technical skills to ensure the data is correct and of high quality. The data is then analyzed, designed, and shown in a way that helps people, businesses, and organizations make better decisions.

• Using automated tools to get information from first-hand and second-hand sources
• Getting rid of insufficient data and fixing coding mistakes and other issues
• Developing and maintaining databases and data systems – reorganizing data in a readable format
• analyzing data to figure out its quality and meaning
• Review reports and performance indicators to find and fix code problems to filter data.
• Using statistical tools to find, analyze, and understand patterns and trends in large, complicated data sets, could help diagnose and predict
• Putting a number on essential business functions so that the performance of the business can be measured and compared over time.
• Analyzing local, national, and global trends that affect both the organization and the industry
• Using relevant data to show trends, patterns, and predictions in reports for the management
• Working with programmers, engineers, and top managers to find ways to improve processes, suggest system changes, and develop data governance strategies.
• They are putting together final analysis reports so that the people who matter can understand the steps of data analysis and make critical decisions based on facts and trends.

EDA, or Exploratory Data Analysis Project, is another essential part of a data analyst’s job description. In these kinds of projects, the analyst must look closely at the data to find patterns. The next thing that data analysts do is use techniques for data modeling to sum up, the main parts of data analysis.

Data Analyst Skills Required

Now that you know what a data analyst does let’s look at the skills you’ll need to get the job. A good data analyst must have technical skills and the ability to lead. If you want to become a data analyst, a background in math, statistics, computer science, information management, or economics can give you a good start.

Key Skills for a Data Analyst

• Strong math skills to help collect, measure, organize, and analyze data
• Knowing how to code in SQL, Oracle, R, MATLAB, and Python is essential.
• Know-how about database design and development, data models, data mining techniques, and segmentation.
• Experience with programming (Javascript, XML, or ETL frameworks), databases, and reporting tools like Business Objects.
• Skill with statistics and statistical software like Excel, SPSS, and SAS, which can be used to analyze data sets.
• good at using platforms for data processing like Hadoop and Apache Spark
• Software for showing data, such as Tableau and Qlik
• Knowing how to make and use the most accurate algorithms on datasets to find answers
• Problem-solving skills
• Accuracy and care for the details
• able to answer questions, write reports, and give talks.
• Team-working skills
• Work experience that shows you know how to analyze data

What tools do people who look at data use?

SQL

The SQL is one of the essential tools for analysts because many large companies use it to analyze data. SQL is also used by software engineers when they make new software. SQL is a computer language used to manage data from relational databases. It is a tool that is easy to learn and can be used to analyze data that is complicated and hard to understand. It is a popular choice among data analysts because the code is easy to read and understand and can be used to change and edit data. Also, it lets you combine data in a way similar to Excel, but for massive datasets and many tables simultaneously.

Microsoft Excel

As a data analyst, you should know how to use Excel, the essential tool. It’s easy to learn, and data analysts should be able to use all of Excel’s features, from formulas to pivot tables. Any spreadsheet program will work, but the most popular one is Microsoft Excel.

SPSS and VBA

 In addition to the tools listed above, analysts often need a statistical analysis program like SPSS. SPSS is excellent for analysts who just got their licenses (more on SPSS below). VBA, which stands for Visual Basic for Applications, may be needed by data analysts with more experience. It is a programming language that was made just for Excel. Often used for financial analysis. It also works with Word and PowerPoint. Matlab is another excellent tool that can be used to make algorithms, build models, and look at data.

Jupyter Notebooks

Project Jupyter is a one-of-a-kind service for making open-source software, open standards, and interactive computing services. It can be used with a lot of different programming languages. Jupyter Notebook is an open-source online tool that lets you make and share documents with live code, equations, graphics, and written prose. The notebook can be used for many things, like cleaning and transforming data, machine learning, and more.

R

Another important and widely used tool in data analytics is the open-source programming language R, which works on all platforms (Windows, Mac OS, and Linux). It is used a lot for statistical modeling because it has so many statistical and graphical options. Also used a lot for data wrangling and can be found in many libraries, such as Plotly, and lets data analysts make plots and graphs to show how the data looks.

It is used in banking, sales, and several scientific fields, such as medicine and technology. To use this tool for analyzing data, you need to know a little bit about statistics and programming in general.

Tableau

Tableau is another program that data scientists often use. It is used frequently because it makes it easy to evaluate data quickly. Visualizations can also be done with dashboards and spreadsheets. Tableau lets you make dashboards that show information that can be used to move a business forward. Tableau products always run in virtualized environments when they are set up with the correct operating system and hardware.

SAS

SAS, which stands for “Statistical Analysis System,” is a well-known business suite of business intelligence and data analysis tools. In the 1960s, the SAS Institute made it, and since then, it has changed. Its main uses are profiling clients, creating reports, mining data, and making predictions.

The software is often more reliable, flexible, and easy to use for large enterprises because it is made for the business market. This is because they have different levels of programming skills in-house.

Power BI from Microsoft

Microsoft Power BI is a relatively new tool for analyzing data. It has only been around for a few years. It started as an add-on for Excel. In the early 2010s, it was updated to become a full suite of tools for analyzing corporate data. Power BI makes it easy for users to quickly create interactive visual reports and dashboards.

Its best feature is how well it connects to data. It works well with Excel, as you might expect from a Microsoft product. Still, it works well with text files, SQL servers, and cloud sources like Google and Facebook analytics.

What do you need to do to be a data analyst?

Now that we know what a data analyst does and what skills they need, let’s find out more about what makes a good data analyst. To do well in a career in data analytics, you need more than just technical skills.

A bachelor’s degree in a field that emphasizes statistical and analytical skills is preferred. Students with a background in math, statistics, computer science, or economics often have an advantage in data analysis. But a postgraduate course in data analytics like Data Analytics Bootcamp can help you become a professional who is ready to work.

You would also need soft skills to be a good data analyst, such as:

• excellent communication and presentation skills
• creativity and the ability to think critically
• having a systematic and logical way of solving problems and working as a team.

How much money does a data analyst get paid?

Does the job description for a data analyst get you excited enough? If not, let’s look at how much this in-demand job pays. But remember that a data analyst’s salary depends on several things, such as the person’s education, location, experience, and skill set. 

An experienced data analyst can average earn anywhere from $60,000 to $140,000 per year. Most of the time, financial and tech companies pay more than average.

The average salary for a data analyst across all markets is about $73,528. Data analysts usually move to positions like senior data scientists, data analytics managers, business analysts, etc.

When you take on more responsibilities, your pay goes up a lot. It is thought that the average starting salary for a data scientist is around $95,000, while the average starting salary for an analytical manager is around $106,000.

Top Companies Hiring Data Analysts

If you want to work as a data analyst, more than 86,000 jobs are open worldwide. It’s crazy. This is mainly because data analysis is helpful in almost every field. Today, the job description for a data analyst includes many different specialties, such as finance, health care, business, marketing, and e-commerce.

In the US and Europe, the most job openings for data analysts are at business intelligence companies, followed by finance, sharing economy services, healthcare, and entertainment companies.

Amazon, Netflix, Google, Intuit, Facebook, Apple, and CISCO Systems are some of the best companies in the world that hire data analysts. Focus KPI, Affinity Solutions, and Norgate Technology are some smaller companies that hire data analysts. Financial giants like Paypal and Barclays also hire data analysts in different departments.

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