How to get an internship as a Data Analyst?

Getting an Internship is the best way to inter in any field and the same is true in data Analytics if you want to inter easily and want to learn practical knowledge then Internships are the best way. Below are some steps that you can follow to get an Internship as a Data Analyst -

1)Learn PowerBI/Tabluea and SQL - The very first thing you can do in getting an Internship as a data analyst is to learn PowerBI/Tabluea and SQL because you will be asked questions in the interview mostly on these only.

2)Build Projects - After getting your hands dirty with PowerBI/Tableau and SQL the next thing is to build projects as much as possible but at least 10. You can get these projects from a simple YouTube search and most important thing publish these projects on some platform where the recruiter can look into them and post the link in your resume.

3)LinkedIn - Make a presence on LinkedIn as it's the best place to make connections with recruiters and senior developers You can also post your projects on LinkedIn and if some recruiter likes your work they will directly contact you on LinkedIn.

4)Make a catchy resume - A resume is the first thing that represents you in front of the recruiters so make it as catchy as possible. You can learn about resume-building techniques on various YouTube channels.

5)Internship Portals - Many portals are designed specifically for internships like Internshala, Indeed, etc so keep an eye on those and send your resume to relevant internships. Read more.

Comments

Free Udemy Course for PowerBI

Free Udemy Course for PowerBI Get This Course for Free. Create beautiful dashboards instead of boring spreadsheets and slides. Make an involving presentation based on an interactive visual story. Create visualizations without programming skills. Learn some interesting tips for simply working with Power BI. Get this course for free. Basic Data Connection: Students will learn how to connect Power BI to simple data sources, gaining an understanding of basic data import techniques. Introductory Data Cleaning: Learners will be introduced to the Power Query Editor for basic data cleaning tasks, such as removing duplicates and filtering data. Fundamentals of Data Modeling: Participants will learn the basics of creating data models in Power BI, including simple relationships between tables. Basic DAX Formulas and Visualizations: Students will acquire foundational skills in writing simple DAX formulas and creating basic reports. Understanding the overall life cycle of building a Power BI Report...

Is Web Scraping Illegal and How Can We Do It?

Is Web Scraping Illegal and How Can We Do It? Web Scraping Course. Web scraping is not illegal by default, but its legality hinges on the method employed and adherence to applicable laws and website terms of service. Below is a summary of legal considerations and guidelines for responsible web scraping: Legal Considerations: Terms of Service (ToS): Website ToS dictate the permissible use of their content. Some explicitly forbid web scraping, and violation of these terms could lead to legal repercussions. Copyright Law: Website content is often under copyright protection. While raw data and facts are not copyrightable, their creative presentation might be. Unauthorized scraping of significant amounts of such content could constitute copyright infringement. Computer Fraud and Abuse Act (CFAA): In the U.S., the CFAA outlaws unauthorized computer and system access. Scraping in contravention of website ToS may breach this act. Data Protection Laws: Web scraping may fall under data ...

Connecting Power BI to Azure Data Lake: Streamlining Big Data Analytics

Connecting Power BI to Azure Data Lake: Streamlining Big Data Analytics Azure Data Lake and Power BI provide a powerful combination for businesses to handle and analyze large datasets efficiently. Here’s a step-by-step breakdown of how connecting Power BI to Azure Data Lake helps streamline big data analytics. 1. What is Azure Data Lake? Azure Data Lake is a cloud-based storage solution designed to handle large volumes of structured and unstructured data. It provides highly scalable and cost-effective storage, making it an ideal choice for big data projects, data lakes, and large-scale analytics. 2. Benefits of Connecting Power BI to Azure Data Lake Handling Large Datasets : Power BI’s integration with Azure Data Lake allows users to work with large datasets without needing to import all the data into Power BI. Instead, users can connect and query data directly. Scalable Analytics : Azure Data Lake’s ability to scale horizontally ensures that it can handle growing volumes of data se...

TechBis

Search This Blog