4 Tips To Become A Successful Entry-Level Data Analystby@udacity
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4 Tips To Become A Successful Entry-Level Data Analyst

by UdacityFebruary 9th, 2021
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Companies across every industry rely on big data to make strategic decisions about their business, which is why data analyst roles are constantly in demand.

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Companies across every industry rely on big data to make strategic decisions about their business, which is why data analyst roles are constantly in demand. Even as we transition to more automated data collection systems, data analysts remain a crucial piece in the data puzzle. Not only do they build the systems that extract and organize data, but they also make sense of it –– identifying patterns, trends, and formulating actionable insights.

If you think that an entry-level data analyst role might be right for you, you might be wondering what to focus on in the first 90 days on the job. What skills should you have going in and what should you focus on developing in order to advance in this career path?

Let’s take a look at the most important things you need to know.

1. Develop the Most Important Hard Skill: SQL

SQL is a free, open-source programming language and arguably the most important language for data analysts to learn. Luckily, it’s also the easiest to grasp, especially if you’re new to programming since it utilizes English words. 

SQL is crucial for assessing and manipulating data and will give you a solid understanding of relational databases. Not only will SQL help you interpret data, but it will also prepare you for learning more complex programming languages down the line. SQL also integrates with many database management systems like MySQL, Microsoft SQL Server, and Oracle Database, to name a few. Check out Udacity’s free SQL for Data Analysis course to make sure you’re familiar with this language before your first day on the job.

2. Question Everything

More than any technical requirement, having an inquisitive nature is vital to succeeding as an entry-level data analyst and beyond. A significant component of data analysis is noticing when things seem out of the ordinary or need further investigation. Asking questions, wondering why, and digging deeper is how you find incredibly valuable insights. 

“You have to be curious and inquisitive, and enjoy not knowing how to solve a problem, not knowing the answer, and working through that to get to a usable solution or usable actionable answer,” says Matthew May, a lead data scientist at URSA Inc., a data analytics and visualization company. 

Demonstrating this skill in your first 90 days of the job will help you stand out and make your value abundantly clear. Always be on the lookout for data that doesn’t make sense or seems off. Identifying any problems with data before presenting reports to stakeholders will ensure that you build trust with the company and solidify your skills.

“Data science is constantly evolving and there will be new concepts and new algorithms to learn every year. A curious attitude is what I need. I need somebody who isn’t afraid of saying, ‘I don’t know. I’ll research it.’ says Dr. Rosaria Silipo, the principal data scientist at KNIME.

3. Be a Storyteller

Producing reports is a big part of the day-to-day as an entry-level data analyst, but writing an effective report involves much more than just putting numbers on a page. Drawing meaningful conclusions and telling a story with data is where your value as a data analyst really comes to life. 

Questions like, “Why’s this trending up? What’s the reason for this anomaly? What can we do to mitigate a future incident?” will help direct you to valuable conclusions, according to Solita, an online SQL editor for data analysts. 

Creating a compelling narrative around these questions and answers makes data analysts better equipped to predict future outcomes. A well-constructed analysis also makes it easier to motivate people to get on board with certain business changes that you might suggest.

4. Have a Solid Understanding of Statistics & Math

The role of a data analyst can be narrowed down to two main components: statistics and translating those statistics into digestible stories.

However, you don’t need to be a master-level statistician or mathematician to excel. Understanding the basics of statistics and probability will help you tell a compelling story with the data. Statistical metrics, probability distributions, and statistical plots will all come in handy in your first 30, 60, and 90 days on the job.

“Everything else — algorithms, more programming languages — you can learn,” says Dr. Silipo. “And since programming languages dedicated to AI change every few years, you’ll need to learn new ones throughout your career. However, the math skills you must have from the beginning, and they are the basis to understand and learn everything else.”

If an entry-level data analyst role sounds exciting to you, and you’re ready to learn practical statistics, data wrangling, and data visualization, Udacity’s Data Analyst Nanodegree program could be the perfect fit. In this program, you’ll refine your ability to work with complex data sets and learn the skills to tell a compelling story with data. 

Then, you’ll have the knowledge, experience, and skills to succeed as an entry-level data analyst. When you’re ready to get hired, check out our post about the best ways to get noticed and hired as a data analyst.