Choosing a career path is often a big decision; choosing to switch career paths can be an even bigger one. Sometimes it means a leap of faith because after all, you want to make the right choice. Ideally, your career choice will be a rewarding one, and something that you’ll succeed at and genuinely enjoy. With all of the exciting roles and positions in the technology industry, it’s a vast field to work in with a lot of potentials. Specifically, working as a data analyst can be a fulfilling experience.
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What Is a Data Analyst?
The goal of any data analysis project should be to provide helpful information for making informed business decisions. Typically, there are five loops involved in the data analyst job descriptions process:
- Identify the data you want to analyze
- Acquire the information to be analyzed
- Prepare the data for analysis by cleaning it
- Analyze the data
- Infer meaning from the analysis
The method used to analyze data will vary from one question to the next. You may read more about the sorts of data analysis here. Descriptive analytics informs us what happened; diagnostic analytics tells us why; predictive analytics produces future projections, and prescriptive analytics generates the next steps.
Why Become a Data Analyst?
Job security is essential for most people, and a role in data is likely to be a secure one because these positions are in high demand. MorningFuture reports that the data analyst role will be the most in-demand position in the future. Knowing that your job is likely to be secure (or at the very least, it won’t be challenging to find a replacement), is a significant advantage.
Working as a data analyst can also be an exciting experience that gives you the chance to work on different projects in an array of industries.
Salary is also another crucial deciding factor for many people when it comes to choosing a career path. And working as a data analyst is undoubtedly a lucrative option. Salaryexpert reports that in the United States, the average base pay for a data analyst is $92,038 annually.
What Exactly Does a Data Analyst Do?
It's your job as a data analyst to conclude from seemingly innocuous information. Following the data analysis process (which we'll explore in the next part), you'll solve specific problems or answer certain queries based on data and the insights it provides.
Here’s what are typical a Data Analyst does:
- Develop and implement databases and data collection systems
- To determine the most critical KPIs and measurements and to set priorities for the company in conjunction with management
- Acquire information from original and secondary sources
- Sort and sanitise the data
- Trends and patterns in large datasets must be identified, analyzed, and interpreted
- Create a visual representation of the data and share it with relevant parties
- Construct and modify reports
- Develop and maintain dashboards
- Data models, metrics, and supporting infrastructure must be documented as they are created and maintained
So far, we've just scratched the surface of a data analyst's responsibilities.
The Role of a Data Analyst
Just about everything is data-driven these days, from market research and sales figures to expenses and logistics. To most people, this information can be overwhelming and daunting. It can be difficult and time-consuming to sort through it all and know what’s important, what isn’t, and what it all means.
This is where data analysts come into the picture: they take this data and turn it into useful information for businesses. This allows them to make more informed decisions in the future.
Data Analyst Roles and Responsibilities
A data analyst is someone whose job is to collect and analyze data to find a solution to a problem. The position requires extensive time with data and time spent communicating results.
Many data analysts spend their days doing the following:
Data Collection
The analyst generally performs their data collection. Obtaining this information could involve polling a sample of customers, monitoring website traffic for trends, or purchasing data sets from experts in the field.
Clean Data
Duplicates, mistakes, and outliers exist in raw data. Keeping the data in a spreadsheet or computer language in good shape ensures that your results will be accurate and will not be distorted.
Model Data
Making a database from scratch requires planning and design. You may have to decide which data to keep and which to discard, map out the connections between different kinds of information, and consider how everything will ultimately look.
Interpret Data
To interpret data, you must look for recurring themes or other indicators that may point to a solution to the problem at hand.
Present the Data
A significant portion of your role will be disseminating your uncovered findings. You accomplish this by preparing visual aids like charts and graphs, drafting reports, and giving audience presentations.
What Tools Do Data Analysts Use?
Analysts use various tools to improve the quality and efficiency of their data analysis. The field of data analytics makes extensive use of a wide variety of tools, including:
- Google Sheets
- SQL
- Microsoft Excel
- SAS
- Tableau
- R or Python
- Jupyter Notebooks
- Microsoft Power BI
Types of Data Analysts
Knowledge of data collection, organisation, and analysis is now an integral aspect of virtually every field. New technologies have vastly increased the kind and volume of data we collect. Data analysts are in high demand in many areas, including law enforcement, the fashion industry, the food industry, the IT industry, businesses, the environmental sector, and the government.
Data analysts may go by a variety of other names, including but not limited to:
- Medical and health care analyst
- Expertise in Market Analysis
- Business analyst
- Business intelligence analyst
- Operations research analyst
- Intelligence analyst
Data Analyst vs. Data Scientist
You've already done some reading about data science and the data analyst job descriptions. Although these two phrases are frequently used interchangeably, they refer to distinct professional paths that accomplish different goals and necessitate different skill sets.
As we've established, data analysts utilise a firm's data and interpret it for decision-makers within the company. They analyze data trends and create dashboards and visualisations for widespread use to provide answers to questions and build solutions.
On the other hand, a data scientist will dig deeper into the data, employing data mining and machine learning to find patterns. They will conduct experiments, develop models, and conduct tests to validate or refute their hypotheses. Then, they'll provide recommendations for how a business might move forward in light of their results.
Who Should Be a Data Analyst?
If you want to be challenged and avoid the mundane, a data analyst role may be ideally suited for you. Good data analysts are problem solvers, have an interest and curiosity when it comes to data, are good with numbers, and of course, are analytical. If you possess these qualities, a data analyst may be your perfect career match.
It also takes a willingness to learn as a data analyst. Technology is always evolving, and people in these positions must be willing to adapt to changes and learn about new processes, programs, and techniques. As a data analyst, it’s also crucial to have specific technical skills as well. It is preferable to know particular programming languages, such as Python and R. Therefore, enrolling in an accredited Data Analyst online course can teach you the skills needed to succeed. Remember, the willingness to learn is what’s most important.
Note: As a data analyst, it would add an advantage to your skill if you know the types too!
Is Data Analytics a Good Career?
What Does a Data Analyst Do? Gaining experience as a data analyst may also lead to opportunities in related fields. Numerous entrant-level data analysts progress to more senior positions as data scientists. Data scientists, like analysts, conduct their work using quantitative and computational methods. On the other hand, a scientist might employ cutting-edge techniques to construct models and other instruments to shed light on upcoming tendencies.
Data Analytics Courses
Once you’ve decided to become a data analyst, the next step is earning your data analytics certification. Enrolling in the right Data Analytics program will not only help you master data analytics but also prepare you for your certification exam. Earning your Data Analytics certification is an essential part of pursuing a career as a data analyst, as this can be a highly competitive position. In a competitive job market, it’s crucial to stand out in the best way possible by having the right credentials to include on your resume.
Simplilearn is excited to announce that we’ve recently unrolled a Data Analyst Certification Course, which was created for budding data analysts and co-developed with IBM. This thorough program is perfect for all levels, whether you have some data analytics knowledge or you’re starting from scratch. Learn the fundamentals, as well as advanced skills, in our latest data analytics program and move one step closer to landing on your dream job as a data analyst.
