4 tips for becoming an effective entry-level data analyst

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

If you think an entry-level data analyst position 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 to get started and what should you focus on developing in order to progress in this career path?

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

1. Develop the most important hardware skill: SQL

SQL is a free, open source programming language and arguably the most important language to learn for data analysts. Fortunately, it is also the easiest to understand, especially if you are new to programming since it uses English words.

SQL is crucial for evaluating and manipulating data and will give you a solid understanding of relational databases. Not only will SQL help you interpret data, it will also prepare you to learn more complex programming languages ​​down the line. SQL also integrates with many database management systems such as 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 are familiar with this language before your first day on the job.

2. Question everything

More than any technical requirement, having a curious nature is essential for success as a novice data analyst and beyond. An important part of data analysis is noticing when things appear to be out of the ordinary or in need of further investigation. Asking questions, wondering why, and digging deeper is how you find incredibly valuable information.

“You have to be curious and curious, and like not knowing how to solve a problem, not knowing the answer, and working through that to come up with a usable solution or an actionable answer,” says Matthew May, data manager at URSA. Inc., a data analysis and visualization company.

Demonstrating this skill in your first 90 days on the job will help you stand out and make your worth clearly understood. Always be on the lookout for data that doesn’t make sense or appears to be wrong. Identifying any issues with the data before reporting to stakeholders will ensure you build trust with the business and solidify your skills.

“Data science is constantly evolving and there will be new concepts and algorithms to learn every year. A curious attitude is what I need. I need someone who isn’t afraid to say, ‘I don’t know. I’ll do some research. says Dr Rosaria Silipo, senior data scientist at KNIVES.

3. Be a storyteller

Reporting is a big part of a novice data analyst’s day-to-day life, but there is more to writing an effective report 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 such as “Why is this trend on the rise?” What is the reason for this anomaly? What can we do to mitigate a future incident? Will help you draw 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 engage in certain business changes that you might suggest.

4. Have a solid understanding of statistics and mathematics

The role of a data analyst can be reduced to two main elements: statistics and the translation of those statistics into digestible stories.

However, you don’t have to be a master’s-level statistician or mathematician to be good. Understanding the basics of statistics and probability will help you tell a compelling story with data. Statistical measures, probability distributions, and statistical graphs 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 AI programming languages ​​change every few years, you’ll need to learn new ones throughout your career. However, the math skills you need to have early on are the foundation for understanding and learning everything else.

If an entry-level Data Analyst role sounds exciting to you and you’re ready to learn hands-on statistics, data management, and data visualization, Udacity’s Data Analyst Nanodegre program might be the perfect fit. . In this program, you will hone your ability to work with complex data sets and gain the skills to tell a compelling story with data.

Then you will have the knowledge, experience and skills to be successful as a entry-level data analyst. When you’re ready to be hired, check out our article on the best ways to get noticed and get hired as a Data Analyst.

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Sean N. Ayres