Many individuals already hold the belief that the tech industry demands coding skills, which they perceive as difficult. Consequently, they tend to avoid pursuing careers in tech. However, the trick is that, with some career paths, you can break into the tech industry without a tech background and one of these career paths is Data Analysis.
Job Description of a Data Analyst
A Data Analyst is a professional with the appropriate skills to collect data and analyze it to obtain relevant and meaningful ideas, trends, and patterns. This skill requires the use of certain tools to achieve data interpretation, create reports, and make necessary recommendations. However, the full job description of a data analyst includes:
- Collection of all types of data – whether big or small data sets.
- Evaluating the quality of data and transforming it to be fit for use.
- Create a visual representation of data to communicate results effectively.
- Interpreting complex data findings in such a way that it will be understood by non-technical workers.
- Ensuring data security and integrity.
- Develop and deploy data models that can be used for proper decision-making.
These points explain the job of a data analyst. However, organizations can customize the job description of a data analyst whenever they are looking to hire one.
Who can work as a Data Analyst?
Anyone can work in any organization as a data analyst. If you are landing your first, you are most likely going to be hired as an Entry-level data analyst which of course still makes you one of them as long as you have the required skill. Whether you are looking for a remote data analyst job or you want to work onsite, it still doesn’t change the fact that you are a data analyst.
So, if you are looking to work as a data analyst, it is very important to make up your mind to be committed to learning the skills.
Where can I find Data Analyst Jobs?
Data Analyst jobs are available in many organizations that use data. These organizations can include:
- Banks
- Tech Companies
- Retail and E-commerce
- Telecommunications companies
- Hospital/Health care centers
- Travel and Hospitality firms
- Consulting firms
However, to gain access to data analyst positions in these companies, you must register and look for the jobs on job boards such as Hubforjobs.
How do I become a Data Analyst without a Tech Background?
If you have been wanting answers to these questions, we may have a few solutions for you. This is what we think:
Get familiar with Microsoft Excel for a start
Microsoft Excel is the most used tool in Data Analysis, especially for beginners. The tool allows you to enter data into cells which can be further organized into rows and columns. Know how to use basic formulas, format cells, and pivot tables. You can also learn about how to input data into cells through Power Query and analyze it with pivot tables. Pivot tables are tools that greatly help to summarize large datasets. Make sure that at this stage, you can confidently manipulate and visualize data.
Move on to SQL (Structured Query Language)
SQL is another foundation of Data Analysis that can be used when working with relational databases. This language can help you to manage and query structured data. Also, this path requires certain steps starting with a “SELECT” statement that is used to retrieve data from the database. Then, you can go ahead to learn how to filter, sort, and aggregate data. SQL also requires that you learn how to combine data from two or more tables using JOINS. You can also practice data aggregation effectively using COUNT, AVG, and GROUP. There are other parts including Subqueries, Database Modification, Indexes, and Views that you can familiarize yourself with while learning SQL.
Learn about Database in general
Having a rich knowledge of databases is important as It helps you to handle the other aspects of data analysis. Learn about how they are created, where the data comes from, and how they are updated. Be familiar with the different key concepts in databases, and the types and importance of databases in data Analysis. Learning about databases helps you to know how to interact with your data effectively and become a better data analyst.
Delve into Data Visualization tools
You can start with tools like Power BI or Tableau while practicing simple visualizations such as bar charts, line graphs, and pie charts. These tools have online communities where you can find tutorials and simple datasets that can help you practice how to add data, create calculated fields, and format visuals. Go deeper into learning and see how you can transform, clean, reshape, and aggregate data using Power BI of Tableau. There are also interactivity options within the tools that help you learn about creating interactive dashboards by combining more than one visualization and making use of filters and slicers. Be sure to know how to share your reports and dashboards with other people as this can serve as a means of collaboration.
Know a little or more about Python/R
Several data analysts use Python and R programming languages. They have a rich package that allows you to carry out data manipulation, statistical analysis, and data visualization. You can start with the basics of the language such as the variables, data types, and basic operations. You can also take time to learn about the data structures which will effectively help in handling data. Check libraries that can help you simplify your tasks and create visualizations. All of these basics learned will help you to find other data analyst courses easily. You don’t have a technical background but you’ve dedicated enough time and resources to learning what you need to know starting as a data analyst.
Is Data Analysis a stressful job?
The answer to the question of whether data analysis is a stressful job is personal. For some people, it’s far from stress because they love their job and find it intellectually stimulating. However, for some, it can be stressful based on factors such as the work environment, job expectations, deadlines, and complexity of tasks. There is no need to overthink it because, with proper management of time, coping strategies, and a supportive work environment, any type of stress can be effectively manage
