In the current era, we can hardly find an organization without data; each and every organization generates data in the raw format. If it is processed in an efficient way, one can find hidden insights that can result in business gains. For processing data, companies hire engineers who collect and analyze raw data to draw inferences using various tools and techniques. Data analysis is one such key role in most companies, and the professionals responsible for extracting insights from the data for problem-solving are data analysts. Many aspirants are looking forward to a successful career in data analysis. Candidates usually opt for data analysis training to enhance their skills and develop an excellent understanding of data analysis fundamentals.
As the digital world is rapidly growing, data analysis is becoming a great career choice. This may be attributed to the advanced developments in computer technologies such as increased data processing speed, flexible storage capacity at minimal cost, user-friendly visualization tools, simple scripting languages, and more importantly a lot of data to process. Further development in evolving technologies such as artificial intelligence and machine learning increases the scope significantly.
This article is all about data analysis and why you should go for data analyst certification. It will further enhance your understanding of the roles and responsibilities of a data analyst along with the salary and demand aspects.
What is a Data Analyst?
Data analyst is not a completely new designation. In fact, it is quite old and has evolved greatly in the last couple of years. Nowadays, data analysts have tremendous scope in various fields including banking, healthcare, eCommerce, education, and communications. The data analyst role is closely linked to data scientist and data engineer roles. Moreover, It can be considered as an entry-level job to data-related roles. Any professional with basic knowledge of statistics, data analysis, or even computer scientists are suitable to take the role of a data analyst. However, these professionals aren’t limited to the world of information technology.
Roles and Responsibilities of Data Analysts
Data analysis is quite challenging at times while other times it is straightforward. It depends on the problem at hand. The following points are expected from data analysts.
- The first and foremost role of a data analyst is to collect data from external or internal sources to start with their analysis or research. The source can be anything: a database, data warehouse, or data dump. Sometimes raw data needs to be structured in patterns using algorithms before being used for further processing.
- Every data has some bugs or inconsistencies and needs to be filtered out before analysis. Process of correcting raw data to remove bugs or inconsistencies commonly known as data cleansing. It is very important as failure would result in misleading insights and heavy penalties. You would also need to see data with respect to physical limits. For example, if you are recording environmental temperature in India it should not have value -100C and can be considered a bug. It should be removed before analysis specifically if the outcome of the analysis is minimum temperature or an average temperature in India.
- The next step is most important and can be considered as the backbone for the data analyst role. Data processing or analysis can be thought of as finding answers to certain questions and it varies depending on the problem statements that need to be solved. Some example of problem statements are as follows
- Root cause analysis for any failure in an existing product or process.
- Ways to improve the existing product or process i.e. to improve product or process quality.
- To solve a critical business problem that can affect the business significantly.
- To suggest design changes for the betterment of product or process.
- To understand customer behavior to improve sales targets or penetrate new markets.
- You generally start analysis on filtered data to arrive at the solution of a specific problem in mind at the start of the analysis. Data analytics is nothing short of art. You need to be highly skilled in the field and good at exploring the facts from the data to answer specific questions. It requires a high level of understanding, experience, strong analytical ability along with logical reasoning. Due to the large data size nowadays, statistical tools are used heavily to examine and interpret the data effectively and quickly.
- You may have to spend a considerable amount of time on finding trends and patterns in raw and filtered data. Finding a correlation between various parameters in a complicated set of data could be quite challenging. Specifically, you are handling large data sets from various sources involving hundreds of parameters. Trends give you various insights to data in a very short span of time and make it very easy for you to communicate findings to stakeholders. Trends can be extremely important to look at both in the short and long-term to find and resolve critical problems if happening for a long time. Sometimes trend analysis can be helpful to understand the business performance and loopholes in current business models. It gives you direction to move ahead to answer the question you begin the analysis with.
- Once all analysis is done, analysts need to communicate the findings to the team and stakeholders to take necessary actions. It depends on the skill of the analyst to compile the reports with a compelling storyline to tell to the audience. If you are good at storytelling and preparing reports, you have already won half the battle. Compelling a story with data is very crucial to put forth the points you wanted to make and keep the audience engaged.
- Reporting is part of data visualization, either dynamic or stating. While dynamic reporting is more attractive to customers as it may reflect live changes in raw data however it is a bit challenging. Whereas static reporting such as pdf is less challenging and engaging but always helpful. One step ahead is a dashboard with multiple functionalities to improve customer experience to the next level and highly desirable. In short, good reporting helps you convert raw data into useful insights. Trendy graphs, plots, eye-catching content, high-quality charts in stylish fonts help you present findings in a clear and concise way.
Important Skills for Data Analyst
- Basic programming skills such as python, java, R, or scala are helpful in automatic some steps in data analysis such as cleaning, integration, etc.
- Good understanding of basic mathematical and statistical tools to find out correlation in various parameters and trend analysis.
- Knowledge of good visualization tools such as PowerBi, Tableau to prepare good reports.
- Good problem-solving skills along with logical and analytical thinking in order to solve the question in hand.
Salary and Demand Trend
The demand for Data specialists has increased rapidly in the last few years. According to payscale average annual salary for data analysts falls close to 425k INR in India.
Conclusion
Now that you have come across what is a data analyst, its associated role in the organization and the skills required. It is high time to move ahead and start your career as a data analyst. This makes sense specifically looking at the current market trend, high demand, and earning potential for data analyst roles. In order to start with a career in data analyst, it is highly recommended to equip yourself with some advanced degree or certifications. A Data Analyst course will enhance your proficiency in the tools and systems used by Data Analyst professionals.
