Who is a data analyst?
A data analyst collects, cleans, and interprets data sets in order to answer a question or solve a problem. They work in many industries, including business, finance, criminal justice, science, medicine, and government.
What is data analysis?
Data analysis is the process of gleaning insights from data to inform better business decisions. The process of analyzing data typically moves through five iterative phases:
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Identify the data you want to analyze
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Collect the data
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Clean the data in preparation for analysis
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Analyze the data
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Interpret the results of the analysis
Responsibilities of a Data Analyst
1. Understanding the Goal
First and foremost, a data analyst must identify the organization’s goal. They must assess the available resources, comprehend the business problem, and collect the right data.
2. Querying
Data analysts write complex SQL queries and scripts to gather, store, manipulate, and retrieve information from relational databases such as MS SQL Server, Oracle DB, and MySQL.
3. Data Mining
Data is mined from a plethora of sources and organized to obtain new details from it. By doing so, data models are built to increase the efficiency of the system.
4. Data Cleansing
Cleaning and data wrangling is the vital duties of a data analyst. The data gathered initially will often be messy and have missing values. Hence, it’s crucial to clean the collected data to make it ready for the analysis purpose.
5. Data Examining
Data analysts use analytical and statistical tools, including programming languages, for carrying out a logical examination of data.
6. Interpreting Data Trends
Data analysts use various packages and libraries to spot trends and patterns from complex datasets, thereby discovering unseen business insights.
7. Preparing Summary Reports
Data analysts prepare summary reports with the help of data visualization tools. These reports guide the leadership team to make timely decisions.
8. Collaborating with Other Teams
Data analysts interact with the management team, development team, and data scientists to ensure proper implementation of business requirements and figure out process improvement opportunities.
How to become a data analyst?
1. Complete a data analytics certification
You don’t need a full-blown degree to become a data analyst, but you do need a structured and formal approach to learning the necessary skills. The best (and most flexible) way to do so is through a project-based course
2. Polish up your data analytics portfolio
Data analytics is a hands-on field, and employers want to see proof that you can apply what you know to real projects.
If you don’t have any real-world experience, you might be wondering what you could possibly include in your data portfolio. Here are some ideas:
Take a course that includes projects in the curriculum
3. Identify (and emphasize) your transferable skills
If you’re brand new to the field of data, it’s especially important to connect your previous career and your new career. Spend some time identifying your core hard and soft skills, and think about how they might be transferred to data analytics.
Perhaps you’ve got a marketing background and are already familiar with some basic analytics tools. Maybe you’re a teacher, which makes you great at explaining things—an excellent skill when it comes to presenting your data insights and explaining what they mean to non-technical stakeholders.
Soft skills
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Communication, collaboration, and presentation skills
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Problem-solving
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Research
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Attention to detail
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An analytical mindset
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An affinity for numbers
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Good organizational skills and an ability to meet deadlines
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Some commercial knowledge or business acumen
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A methodical and logical approach
Hard Skills
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Proficiency in Microsoft Excel
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Knowledge of programming and querying languages such as SQL, Oracle, and Python
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Proficiency in business intelligence and analytics software, such as Tableau, SAS, and RapidMiner
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The ability to mine, analyze, model, and interpret data
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The ability to work with large, complex datasets
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Solid understanding of data profiling and requirement-gathering processes and principles
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Expertise in data visualization
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The ability to communicate findings and to make actionable recommendations for the business
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The ability to deploy commercially viable statistical models
What kinds of companies can you expect to work for?
As a newly qualified analyst, you’re likely to find job opportunities in the following sectors:
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Media and entertainment
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Finance
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Retail
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Marketing
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Wellness and fitness
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Education
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Transport and logistics
How to Become a Data Analyst With No Experience?
Acquire the relevant data skills by studying or enrolling in a data analytics course/bootcamp
Practice using those skills by building and developing data analytics projects
Gather projects into a portfolio and display it on Github
Practice visualizing and presenting your data analytics projects to an audience
Join online communities such as Kaggle to grow your expertise and network
