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Data has always been an essential aspect of a business. However, there has been a tremendous increase in the amount of data available for companies to optimize their strategies. The need to get insight from these massive data necessitated the field of data analysis.
Data analysts are in demand across all sectors, from manufacturing, finance, education, and even government. To start a career as a data analyst, consider enrolling for a data science Bootcamp to get adequate skills required for the field.
A data analyst is an individual who collects, scrutinizes, and performs statistical analysis on data to gain meaningful results. A data analyst translates numbers and figures into plain English that can help the employer or client make critical decisions. Whether it’s a sales report, logistics, marketing research, or transportation details, the data analyst can pull out meaningful facts from the raw data.
The task of a data analyst varies depending on the type of data the business or client works with.
Businesses benefit a lot by working with a data analyst. The results from the data analyst allow them to define customer needs and improve their products.
Here are some of the daily tasks of a typical data analyst.
The data analyst has to spend time collecting data and compiling their reports. It’s one of the most technical aspects of data analyst job description. The task requires great attention to detail to be able to understand the available data and how to work with it. The data analyst also works with a handful of specialized tools that help automate their work.
After collecting data, the analyst has to scrutinize the data to provide a meaningful report. To achieve this, they need to identify specific patterns in the data. Those patterns give insight to produce the reports and recommendations.
As a data analyst, you have to do a lot of collaboration right from the offset. You will work together with management and other people in the organization to optimize data collection. You also collaborate with people from various departments, including marketers, management, and salespeople.
For instance, you have to speak with management about what they wish to learn from the data.
Data analyst spends a significant amount of their time writing reports from their analysis. The reports provide insights into their findings and how the company can improve. As an analyst, you have to make the report very clear and understandable for decision-makers. You can use graphs, pie-charts, and illustrations to simplify numbers and trends.
Data analysts use various tools for scrutinizing available data to derive information for client and management. Some of the skills needed to be a successful data analyst include:
Proficiency in at least one programming language is an essential requirement. Data analysts use various programming languages, including R, Python, C++, PHP, and Java. R and python are the major statistical programming languages used for predictive analysis. R is built explicitly for analytics. However, both languages can be used for exploring a dataset. Employers also don’t care about the programming language you use as long as your analysis is accurate.
R and python are both open sources, and you can find free resources online to help you get started, as well as structured data science Bootcamp led by instructors.
Microsoft Excel is a potent tool that can be used for organizing and calculating numbers. Excel serves as a substitute for other complex tools like R and Python. As a new entrant to data analysis, excel tools like Macros and VBA lookup can allow you to perform quick analytics.
Excel is, however, suitable for startups and bootstrap companies with smaller data set.
Structured Query Language (SQL) is a database language that is used for data analysis. Unlike Excel, SQL can handle large datasets. SQL is one of the most in-demand skills for data-analysts, and also the first step to working with big data.
As a data analyst, you should be able to tell a compelling story with the available data. Data visualization has to do with breaking down the data to its simplest and meaningful form. If your analysis is not adequately visualized, then it may be challenging to use. You can use both charts and graphs to make your findings visually appealing.
A good understanding of statistics is required for real-world data analysis. You need to be able to solve business problems like compound interest, depreciation, calculus, algebra, and standard derivation.
A degree in mathematics, statistics, computer science, finance, economics, or information management will also be an extra advantage for this field.
Data analysis amongst one of the most sought-after skills in today’s business place. It has predicted a 19% increase within the next seven years.
Upon completing a data science Bootcamp, there’s a wide range of options available to you, including the following.
Data analyst works in a wide range of places, from big companies to financial institutions and small or medium businesses.
Employers of data analysts include the following.
The salary a data analyst earn depends on the job and the responsibilities. A senior analyst with data scientist skills will command a higher salary. However, an entry data analyst working with essential tools will earn about $54,000 annually. The take-home pay range for the industry is $59,000 – $106,000.
Conclusively, a career in data analysis begins with learning its basics. While there are online sources where you can learn from, they are most times unstructured and might end up making the whole process confusing. Enrolling for a structured data science Bootcamp taught by seasoned data analysts will give you an edge.