Businesses are increasingly becoming data-driven and realising the value of strategies made from analysing data. Making any decisions without taking valuable inputs can be disastrous as they would be a product of false assumptions. In this scenario, there is a dire need for those who can provide insights from the growing pool of data.
A data analyst is someone who gathers, processes and then turns raw data into functional data. They must be able to expertly analyse large volumes structured and unstructured data. The core responsibility of a professional on this job role is to turn incomprehensible information into understandable forms such as graphs, chart or tables. If you are keen to join this field then here are some revenant skills needed for data analytics.
1. Critical thinking
Data is available in copious amount and to use it for finding answers to your questions means you need to begin with asking the right question. This requires you to have thinking skills vital to the field as you would be synthesising information that is hard to determine. Being a quick, calculative thinker who sees the holistic view of a query or issue, you must work upon your critical thinking skills. Unravelling data for complex scenarios also means that you have to stick to clear and crisp solutions.
2. Paying attention to details
Being able to pay attention to detail is a trait that all data analyst must develop. This is beneficial in assuring that no information is overlooked while solving problems or making decisions. This also adds efficiency to your work and decreases any risk of making errors. For a data analyst, this is a must-have skill that will bring quality and productivity to your work.
3. Structured Query Language (SQL)
SQL is the global database language that is the standard norm pan-industry. It is among the most essential skill that is a pre-requisite to be a data analyst. Often referred to as the “graduated” version of Excel, SQL has the capability to handle large databases easily. Organisations require professionals who are proficient with this language to manage data or build or change databases.
4. Data Visualisation
Data analytics must put across their findings in a simple yet compelling manner. In case your findings cannot be easily identified then you will have trouble explaining it to others. Therefore, analyst generally use catchy and high- quality charts to present information compactly and clearly. Tableau’s visualization software is the norm in the industry as it very user-friendly.
5. Presentation skills
Along with data visualisation, one must also have good presentation skills which is vital to showcasing collected and processed information. This helps in focusing on the audience and conveying specific findings to them in an articulate manner. Excellent graphs will also not be useful if one is unable to present them well.
A good academic qualification is perhaps the first step in making a stable future in the field of data analytics. The coursework helps in building a strong foundation and developing all the above skills.