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Businesses need data specialists now more than ever. With a surge in demand for data professionals, many people are undergoing self training to fill the vacancies in the data space. There are many roles in the field of data. Data scientists, data engineers and data analysts are some roles in data analytics with high demand for skilled workers.
Many people are willing to dive into the field of data analytics. However, the question remains, 'how can one become a self-trained data analyst'? In this article, we shall look at the essential skills that are needed to get started as a data analyst.
Having gone through this process myself, I have noted some key things that may be essential to every aspiring data analyst.
TECHNICAL SKILLS
There are different schools of thought on which technical skills are necessary and in which order one should learn them. Having been here myself and after making so many mistakes in my journey before finding my foot, these are the technical skills I think are fundamental to starting your journey in data analysis.
Statistics
What will a data analyst do if he does not understand statistics? It is essential for every data analyst to understand basic statistics. Basic statistical terms such as mean, mode, average, standard deviation and how to use percentages must be well understood by a data analyst. This will enable you to find the needed insights from your analysis.
There are many tutorials online on statistics. However, recommend Khan Academy to get started with statistics.
Microsoft Excel for Data Analysis
Yes, the good old excel is still relevant. Many organizations still use excel and this should be the starting point for any aspiring data analyst. Excel can do most of the things any other tool can do from data cleaning, data analysis to data visualization. However, excel is limited in its ability to contain large amount of data. That is why more advanced and specialized tools are preferred. Aspiring data analysts must know how to perform basic operations in excel. Excel formulas, data validation, formatting, data analysis, pivot tables and pivot charts are essential excel skills that an aspiring data analyst must know.
Learn excel for data analysis with Simplilearn for free with completion certificate.
You can also subscribe to my YouTube channel (Data Driven Consult), where I share tutorials on data analytics tools including excel.
SQL for Data Cleansing
SQL stands for Structured Query Language. A structured query language in simply term, is a programming language used to interact or query a database. This means you can use SQL to get information from a database. SQL is very essential for every data analyst as it forms part of the most crucial element of data analysis which is data cleansing. Data cleaning and wrangling takes about 80% of the data analysis process. Thus, as an aspiring data analyst, you must be able to perform some tasks using SQL.
I recommend using Simplilearn.
Power BI for Data Visualization
The visible end result of a data analyst project is visualization. This is where findings are turned into charts and graphs for easy interpretation. There are many data visualization tools on the market with the two most used ones being Power BI and Tableau. It is essential to know both of these tools as you may not know which tool is used by your organization. However, for its simplicity and ease of use, I recommend starting with Power BI. Power BI also has a data cleaning feature called power query (also available in excel). Data cleansing, Data Analysis Expression (DAX), Data Modelling and dashboard building are power bi skills that one must master.
I recommend using Simplilearn to learn both tableau and power bi for data visualization.
Tableau for Visualization
Tableau performs similar functions to power bi in data analysis. This tool is used for data visualization and its the preferred choice by most large organizations as it can handle larger datasets. Choosing between these two should be at one's own discretion. However, having basic knowledge of both is very essential.
Python or R
Let me stress that, this is not a necessity to get started as a data analyst. I personally made a mistake of learning python right after excel. I spent six months learning the various python libraries when I should have been learning other important tools instead. These programming languages are used to perform advanced data operations. Theses tools are essential for data scientists as they perform predictive analysis, machine learning and artificial intelligence. Data analysts perform descriptive analysis of existing data so they do not have to perform complex operations using programming languages. However, knowing the basic syntax of at least one preferably python is essential. It can be used by the analysts to scrip data from the web.
Learn python for data analytics for free on Simplilearn.
These are the skills one need to get started as a data analyst. However, technical skills are not enough. There are some soft skills that a very essential for one to be successful in data analytics. Communication, presentation, team work and attention to details are some qualities of a good data analyst. We will look into these soft skills in the next article.
ONLINE RESOURCES TO GET STARTED
For those who can afford, the Google Data Analytics Certificate on coursera is a good starting point. This certificate is well prepared and instructed to equip you with the all the skills needed as a data analyst. There are financial aids available for people who cannot afford of which I am a beneficiary.
Other paid platforms include Data Camp, Udacity, Udemy etc.
There are also many free resources online to get started with data analytics. The most obvious one is to watch tutorials on YouTube. These are the some of the data analytics dedicated channels I will recommend for you.
My own channel Data Driven Consult.
Finally, join the data community on social media. The data community on twitter is a very vibrant one on which you can meet mentors and seniors in the field of data analytics.
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