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Mar, 2021Data Analyst Skills You Need To Secure A Job
Who’s A Data Analyst?
A data analyst is a person who uses some of the most powerful tools available for business transformation and development. A job in Data analytics is a highly in-demand career of the current digital age. This job requires particular skills such as understanding the patterns of data and finding out the hidden meaning in them. Through this analysis the business decisions can be influenced for organizational growth. Data Analysts professionals are those who can classify the customer requirements, forecast utilizing predictive analysis, and then present exceptionally clear data visualizations and presentations to determine and lead all the business decisions.
There is a huge opening of jobs in analytics from every industry that is finance, telecom, construction, Auto, Manufacturing, Etc.
As in this case, the monetary rewards of a career in analytics will only come through proper training and knowledge. Data analysts require technical skills as well as soft skills for the completion of their jobs. You can join our course on Big Data Training and become a skilled data analyst now.
In this article, we will explore the necessary skills required to become a data analyst and grow your career exponentially.
8 Key Skills For Data Analysts
Statistical Skills
A strong foundational skill in probability and statistics is extremely important for any data analyst. Statistical knowledge will guide deep analysis and exploration and also provide insights for understanding the data that you're working with. Additionally, interpreting the raw data will assist you to make sure how valid your analysis is and will also help you withdraw the common misconceptions and logical errors. A critical understanding of statistical methods provides you the potential to gather relevant data, execute accurate analyses, and display the ultimate results in the most applicable form. This complete process aids analysts to make better predictions based on data. The main concepts required to learn here in this field are theory of probability, data transformation, regression, classification, computation utilizing statistical computation, and graphics.
Mathematical Skills
One of the second most important skills to learn for a data analyst is Math Skills. The concepts of Mathematics help in logical thinking, identification of patterns, and algorithm design. These Concepts here include Linear Algebra, Calculus, Optimization Theory, and Discrete Mathematics. Linear algebra has major applications in deep learning and also machine learning, where it supports matrix, vector, tensor, and scalars. Calculus is comparably utilized to develop the cost/loss and objective functions that instruct algorithms to attain their objectives. So, with the help of learning these skills, it will be majorly helpful if you develop a strong set of academic skills, you should always build up the way through the technical medium for the development of these sophisticated mathematical skill sets.
Analytical Skills
Analytical skills are the core of any data analyst professional. Specialized business developments need constant analysis. There is a requirement of describing the main business growth and management questions, the answers to these questions are to be extracted from these large datasets. Analytical intelligence involves finding out the parameters to be considered for specifying the range of datasets, analyzing them from different perspectives, determining variable dependencies, and deriving meaningful data from the results. Analytical thinking is defined as the potential to break down a complex issue into basic components or parts and sort out these components accordingly.
Programming Skills
The accountabilities of Data Analyst professionals are more focused on data composing and presentation instead of coding. However, without any knowledge of the programming languages, a data analyst is unable to put his knowledge into practice. The languages mainly used here are MATLAB, R, Python, and SAS, and SQL. Here, SAS is mostly used for the medical industry and SQL is for retrieving data from massive databases. A deep knowledge of these dominant programming languages assists a data analyst to perform high-level analytics operations on huge datasets without the need of depending on a dedicated programming expert. This skill can be called an add-on for all data analyst professionals. Microsoft Excel is another major spreadsheet program that is extremely useful for data analysis.
Research Skills
Data Analysts should be ready to do some digging if they want to make the most out of the data they collect. For extraction of accurate patterns and trends, a Data Analyst Expert needs to have the potential to research the proper areas up to a point where the desired results are gained with the inclusion of the right features. A Data Analyst also needs the capability to sort-out all relevant and required data to reach out to a precise goal that is clear insights and provides a logical argument for all the next decisions of the organization. Exploration of various angles for similar situations helps you to answer many of the questions and assess if you should pursue things additionally. In this situation, you will consider yourself as an investigator and researcher.
Data Visualization Skills
Analytics professionals need to frequently convey the insights in a report, interactive dashboard, or a chart. To perform this effectively, you need to make sure you have picked the perfect chart type for the data and further design your work in a certain way that displays the key findings visibly and swiftly. Attention to the context should be taken care i.e: Reporting of numbers should not be done in seclusion. How are they affiliated to previous times, to different departments, and to industry benchmarks, etc? Add these data into perspective. This will give guidance to your audience on whether they are worth it or not and if any action is needed at the required time-frame. Good knowledge of data visualization is the key to becoming an effective analyst so you need to know the best practices and apply them successfully.
Presentation Skills
Insights need to be presented frequently to a wide set of audience who can be the management team, customers, or other decision-makers. Also, there will be many instances where you will have to give a presentation in front of a live audience. This is the main reason, you need to hone your presentation skills so that you can effectively share your findings and analysis. A clear structure that is easy to follow and communicates focused insights in a logical order. While you present to your audience, focus on what is necessary and learn the navigational process to make your way through informational interactive dashboards. A most valuable and perfect approach to take is to not limit your answers for the apparent questions that routed you towards this analysis but to consider potential follow-up questions. This depends on the knowledge and proper understanding of your business and your stakeholders.
Machine Learning Skills
This skill is somewhat similar to the job requirements needed to become a data analyst. But you need this skill to keep an upper hand while applying for jobs in Analytics.
According to Statistanow research, artificial intelligence and predictive analytics comprises huge investments by organizations across the globe. Not all analysts have to work on machine learning projects but a sufficient understanding of machine learning tools and concepts is required to successfully work on the various projects you may be assigned in the future or when you apply for similar jobs at different companies. Also, in terms of competition, you will be preferred more than other candidates.
Conclusion
We have deeply covered all the Main skills needed to become an Analytics Professional. Data Analysts are highly sought after in today’s time. If you are interested in progressing in this career path and want to learn now and develop the technical skills needed to successfully secure a data analyst job, check out our interactive and helpful online analytics courses here.
