Usually, two things combine to make a resource highly valuable; short supply and high demand. It was how oil maintained its position as the most valuable commodity in the world. However, these are not usual times. After a dominance of many decades, oil is no longer the most valuable resource in the world. Interestingly, it got replaced by data science and not another mineral.
Even more, interestingly, the two things that combined to make oil valuable do not apply here. While data has a significant demand component, it is not at all short in supply. With a rapidly increasing global online audience, data is collected daily of a large volume. However, in itself, data has limited benefits. The raw data must get transformed into useful information.
It is where the role of a data analyst comes in.
The idea is to make decisions that are data-driven so that the risk of failure is minimal. The data analyst turns raw data into information that becomes practical for actionable business intelligence. All trends indicate a preference among employers for hiring candidates with data skills. It is because whichever industry you operate in, data-backed decisions can give you a competitive edge.
Thus, data analytics continues to be a high paying field.
If you are looking to enter this field, we have identified the most valuable analyst skills you need to master.
The more time you spend on excel, the faster you realize how powerful it is. The key benefit of excel is its user-friendliness and simplicity. As a result, it is ideal for people who are new to data analytics. You can use it to make tables, charts, dashboards, predictive models, etc. Additionally, the VLOOKUP function scans a large set of data for identifying relevant information.
Excel skills are a must if you want to climb the ladder in the data analytics area. Moreover, excel is ideal for businesses where the amount of data is not massive.
SQL stands for Structured Query Language. If you thought excel was powerful, then SQL would be nothing short of a pleasant surprise. It allows you to work on an extensive relational database, whether it be entering new information or making edits. As a result, based on a large set of data, different predictive models are created to identify possible scenarios. The best part of SQL relative to excel is that it keeps data separate from the analysis part.
Learning SQL is one of the best investments you can make in the data analytics field. While it is possible to self-educate through video tutorials, taking a thorough course will pay better dividends in the long-term. With top colleges of the world now offering online programs, learning data analytics has never been more convenient. Among these, the online master of science in analytics program is a practical option for a career boost. Even those who are new to the field of data analytics can master it when provided sufficient learning resources and
- DATA VISUALIZATION
We all like listening to stories. Similarly, data needs a transformation into a compelling story. Otherwise, it runs the risk of losing the attention of the intended audience. This element is particularly crucial because data does not have an innate appeal to it. Moreover, it becomes difficult to discern what a set of data with tens of columns and rows is trying to say. When shown as a pie chart or bar graph, the same data becomes easier to understand.
Therefore, data visualization is an integral part of data analysis.
- DOMAIN-SPECIFIC KNOWLEDGE
A universal textbook doesn’t exist for data analysts because different industries have different usage. Moreover, similar data may not be relevant for two companies in the same industry. Therefore, even before data starts rolling, a high level of familiarity with the industry is essential. For instance, data might show that 12,000 people visit a particular shopping mall daily. The data analyst must know if this much data is enough for its company. What if the product buyer is only a specific gender, age group, or income group?
Thus, domain-specific knowledge is critical.
- PROBLEM-SOLVING SKILLS
The field of data analytics is a rapidly evolving area. No two days in the life of a data analyst are alike. It is because there will continue to be new problems every day. There is no guarantee that the data will always be complete or free from errors. Therefore, the data analyst must have the skillset to navigate around problems innovatively. Otherwise, despite technical skills, the data analyst may get stuck on daily issues.
- PRESENTATION SKILLS
The problem with data is that it cannot speak on its own. It is where the role of the data analyst comes into the picture. The data analyst must communicate to the relevant people about what the data is trying to tell. Therefore, having solid presentation skills comes in handy. If for any reason, the presentation lacks clarity, data will not be considered actionable business intelligence.
All of us have seen people get nervous when asked to deliver presentations (Even more so if the audience pool is large). However, it is learnable at any stage of life.
- MACHINE LEARNING
With recent developments in the artificial intelligence arena, a comprehensive data analysis is achievable through bots. Machine learning cannot only analyze humongous data, but it can do so at a breakneck speed. Therefore, machine learning would give a significant edge to you over other data analysts.
Also note, machine learning is one of the fastest-growing fields. A data analyst with machine learning skills can expect to earn well above $100,000.
As digitization speed continues to pace globally, there will be a greater need for data science professionals. Moreover, the growing realization about the effectiveness of data-centered decisions will fuel demand for data analysts everywhere. Therefore, it would be safe to say that the field of data analytics offers promise, unlike any other. To reap long-term benefits, you must work on mastering the above mentioned seven skills as quickly as possible.