It might not be as simple as it seems to learn data analytics. But, If you are really eager to learn data analytics we would advise you to study it from the perspective of a domain specialist.
With the use of appropriate data, data analytics is a branch of technology that may solve issues or provide answers to queries. A data analyst’s job is to look for patterns in the data to boost productivity and efficiency. There are many different approaches to evaluating data since they also need to perform a thorough study of the data flow.
The main responsibility of a data analytics expert is to go through vast volumes of unstructured data using a range of techniques and equipment. They will conclude the data, which can occasionally be challenging because not all variables are always relevant in the same manner for all types of inquiries, even if the datasets may have been designed for certain analyses.
Strong computer knowledge and the ability to interpret data without a prior understanding of its meaning are some requirements needed to become a successful data analyst. They also need to be able to analyse the findings and offer recommendations for improving processes.
Apart from this, there are several technical skills required. This article lists the best technical skills required to become a data analyst from scratch. Do have a look.
1. Learn the Technical Skills required
- Excel- For a strong foundation
- PowerBI or Tableau- Data visualization
- SQL- Store, manage and retrieve data
- Python or R- Processing/cleaning/analyzing data (This is optional and can be done later especially for non-IT people)
2) Work on hands-on Projects to practice and build a proof of work
- Go toKagglee, data. gov, GitHub websites, etc and get datasets and practice your learnings.
- You can also do guided projects and for this Alex, the Analyst YouTube channel is great for such projects!
- Projects are very important! Do diverse projects- Pick up different domains such as sales, marketing, tech, HR, etc to get an overall idea.
Certifications are not necessary but can help enhance your resume (only after Projects). Our recommendation would be Google/IBM certification or doing official certifications from Microsoft/salesforce etc.
4)Practice soft skills
Soft skills such as presentation, communication, teamwork, critical thinking etc. are important as a data analyst. Practice them by giving mock presentations and recording yourself.
5)Update your Linkedin profile and resume
- Update your Resume with your skills and experiences, and make sure it is ATS compliant.
- Optimize your Linkedin profile to showcase your skills and projects and network with people. This way you will create connections and get referrals.
6) Apply for Jobs and prepare for Interviews
- Find jobs through referrals, and online portals such as Linkedin, glassdoor, indeed,d, etc.
- Practice interview questions from Leetcode, Stratascratch, Datalemur, and Interview Query.