Data analysis is the process of examining, cleansing, transforming, and modeling data with the goal of identifying useful information, drawing conclusions, and supporting decision-making.
Data is increasingly being used by businesses across all industries to make crucial business decisions, such as which new goods to develop, which new markets to enter, which new investments to make, and which new (or existing) clients to target. They also use data to discover inefficiencies and other issues that need to be addressed in the firm. Herein lies the core goals of a data analyst. However, the profession entails more than merely crunching numbers. An analyst must also understand how to use data to help an organization make better decisions.
So,what does a data analyst do? The answer to this question will differ based on the type of organization and the amount to which data-driven decision-making methods have been implemented. The data analyst acts as a gatekeeper for an organization’s data, ensuring that all stakeholders understand the information and can use it to make smart business decisions. It’s a technical position that necessitates a bachelor’s or master’s degree in analytics, computer modeling, science, or mathematics.
Emerson’s online masters in digital marketing is an ideal place to gain your relevant qualification. This program integrates digital marketing and analytics skills while linking you to a creative and diverse network of communicators. A data analyst’s job does not necessarily require computer science or math expertise but these are highly beneficial. However, even if you come from a non-technical background, you can learn the technical abilities required for this position.
Some of the essential skills, abilities and characteristics required to be a successful data analyst can be learned and perfected through education. Others can be honed via practice and experience. Always aim to have the right attitude and be eager to learn.
A Keen Interest in the Subject
An interest and passion for the subject matter is an important asset in any profession and data analysis is no different. This characteristic differentiates a job from a career. You have to love what you do to be good at it. If it is just a way to pay the bills, then you won’t have the required motivation and passion. You either have it or you don’t. It is important to know about data collection processes and operations before jumping in to analyze the given data. Understanding the background of the data will be beneficial when it comes to making conclusions.
Natural Curiosity and Attention to Detail
You need to have a curious nature that drives you to dig deep and to ask all the right questions when it comes to your dataset. To arrive at reasonable conclusions, you need to be able to search for and find the hidden details that will assist you in making the right decisions when it comes to problem-solving.
Problem-solving Abilities
Data analysts need to be good problem-solvers who can think on their feet and be innovative and creative in their approaches. They need to be able to solve complex and intricate problems by paying attention to the details in the data they are analyzing. Sometimes they need to break through surface feedback as research participants often answer with an ‘aim to please’ attitude rather than one hundred percent honesty.
Self-motivated and Open-minded
A good data analyst is self-motivated and proactive in their analysis. They are willing to give the relevant data the time and attention it needs to find the answers. The data analyst must be open-minded to put aside any preconceived notions and to trust the findings from reading the data. They must be imaginative and creative in the ways that they dissect and deconstruct the given data.
Understanding
A data analyst must understand the data chain and be able to work methodically through its links. These are illustrated by a series of questions that can be asked. The data analyst will ask where the data came from, as well as why, how and by whom was it collected. They will question whether it went through any transformations, where it is stored and who has access to it. They will investigate what questions the stakeholders may have and what tools are available for their analysis. They will determine what actions need to be taken based on their findings and whether their analysis had any impact on decision making.
Analytical and Critical Thinker
A good data analyst needs to be able to look at a number and dig deeper to find what makes up that number. To discover the optimal result, they must be able to wade through vast amounts of data, numbers, and facts. They must be able to collect, gather, visualize and analyze information in detail. They must ask more questions to be able to solve complex problems by making effective decisions. Sometimes, the results are not clear and they may need to think more critically, be willing to go beyond the task at hand and to prompt further investigations. It is oftentimes necessary to look at data from different perspectives to support the critical thinking process.
Many successful data analysts create a personal step-by-step systematic approach that works for them. They have an internal checklist so as to know what to do on a data set.
Ability to Identify Patterns
It is important to be able to spot trends and themes in data. This takes a unique eye to be able to predict patterns and give opinions. The data may need to be squeezed by studying and comparing related data. The data analyst needs to be willing to trust the data. Unfortunately, no data collection process is without its flaws so the analyst needs to be able to take a step back to see the bigger picture. Playing devil’s advocate is an essential part of good and thorough analysis.
Numerical Skills or Aptitude
Numerical skills are an advantageous quality in the world of data analysis. This includes knowledge of numbers and figures, awareness of numerical relationships, analyzing mathematical data, and organizing data.Logical reasoning and arguments, calculation skills, working with graphical data, and scheduling or budgeting are all useful talents to have. Visual perception of information with diagrams, charts, and tables is also valuable in this profession. Mathematical trends, measurement, and clustering are all things that need to be understood by a data analyst. These skills can be learned and practiced but a natural aptitude for numbers will assist greatly in this regard.
Excellent Communication Skills
Communication skills are essential since conveying how insightful the results are and how they might assist clients in increasing revenues is critical. The data analyst must be able to communicate technical findings in layman’s terms to non-technical colleagues in the sales and marketing departments. This is the ability to translate data into understandable documents, reports or presentations. Data analysts often present to stakeholders, colleagues, data suppliers, system owners and others. The goal of a data analyst is to help company leaders make informed business decisions using the power of the data analyzed. They must know the right medium to effectively share the information using digital, interactive or exploratory dashboards. Print-ready materials for reading may also be required.
A good data analyst takes into account who the audience is and what are they looking for, by using these tools to communicate their findings: language, culture, geographical locations and timelines. One of the most significant components of succeeding in this profession is asking the right questions all of the time. Data analysis is the ongoing exchange of ideas and information.
Presentation and Story-telling Skills
A good data analyst needs to be able to convey and explain their message convincingly and effectively. Tools used include visually compelling charts, tables and graphs. The data analyst must be able to sell the ideas to company stakeholders and make sure they understand the perspective and conclusions drawn. This can be done digitally to a large audience or in-person to a live audience. The information needs to be shared in a polished logical manner with a clear structure and easy to follow key insights. A good data analyst should anticipate follow-up questions and propose further processes as required. Being able to anticipate needs, being a good listener and being prepared are key points to refining these skills.
Data visualization skills allow a good data analyst to present a comprehensive picture to show what they want to communicate. The results need to be put into perspective to guide the audience to the conclusion as well as what action is needed and in what timeframe. A common phrase that emphasizes the value of visuals is thata picture is worth a thousand words. A visual data analyst is well-versed in the numerous types of charts that can be used for data comparison and analysis.Thepresentationdashboardshouldnotbeajumbleofdataandvisualsthataredifficulttounderstandbytheend-user.The viewer’s attention must be focused on the key points in the presentation.
Your dashboard, which contains all of the charts and data, isn’t adequate if it’s just bright and pleasing to the eye. Each item on the dashboard should convey a message, and you must build a tale for the stakeholder that includes a problem and a solution. You must be able to provide a story about your findings in the time allotted without confusing the audience. Your tale should be brief, straightforward, and focus on the problem area.
Collaboration
A data analyst needs to be able to work as a team player alongside other experts in their relevant fields. They may be required to collaborate with engineers, web developers and data scientists to achieve their goals. They need to be comfortable working with both internal and external stakeholders. There will always be those who want to find fault in your analysis of the numbers or data. You need to be respectful but have the confidence to stand up for your conclusions without becoming indignant.
Business Acumen
A solid understanding of how a particular business works is vital. To be a more valuable part of a team, you need to build your business knowledge through hard work and relationships within the company. A good understanding of the industry in which you work will help you to perceive what problems need to be solved.
Technical Knowledge
It is possible to learn and perfect data analyzing techniques but a strong background in mathematics is often beneficial. It is important to keep developing your skills to keep up with the progression of technology. The ability to take raw inputs and turn them into something meaningful for the business or public requires knowledge and skills about databases. Structured Query Language, Microsoft Excel and other Programming Languages are skills that can be taught. With the help of free online lessons, a basic understanding of how to use these tools may be acquired in a matter of weeks. Excel has several tools that may be utilized to create excellent dashboards, including pivot tables, formulae for data manipulation, and charts for visualization.
The most talented data analysts must keep up with new technology, tools, and theories by attending industry events, reading widely, and building relationships.
Time Management Skills
Successful data analysts need good time management skills to be able to meet deadlines. This skill is also required when collecting, gathering and analyzing data at the most appropriate time. This enables the analyst to work in a logical order of importance.
Leadership Skills
A data analyst’s leadership abilities prepare him or her to perform decision-making and problem-solving responsibilities. These skills enable analysts to think strategically about the data that will aid stakeholders in making data-driven business decisions and effectively communicate the value of that data. Project managers, for example, rely on data analysts to keep track of the most critical metrics for their projects, detect problems that may arise, and forecast how different courses of action can solve a problem.
Analytical and abstract thinking are two of the key characteristics of a successful data analyst. They must comprehend the question, the response, and the methods used to arrive at the answer. A competent analyst knows how to get the most out of flawed data by employing techniques that make the data as objective as feasible.
