Steps to become a data analyst

Learn the Basics of Data Analysis:
Familiarize yourself with foundational concepts in data analysis, statistics, and data visualization. Online courses and textbooks can help.
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Develop Technical Skills:
Gain proficiency in essential tools and technologies such as:

SQL: Learn how to query and manipulate data in relational databases.
Free Resources- @sqlanalyst

Excel: Master data manipulation, basic analysis, and visualization.
Free Resources- @excel_analyst

Data Visualization Tools: Become skilled in tools like Tableau, Power BI, or Python libraries like Matplotlib and Seaborn.
Free Resources- @PowerBI_analyst

Programming: Learn a programming language like Python or R for data analysis and manipulation.
Free Resources- @pythonanalyst

Statistical Packages: Familiarize yourself with packages like Pandas, NumPy, and SciPy (for Python) or ggplot2 (for R).

Hands-On Practice:
Apply your knowledge to real datasets. You can find publicly available datasets on platforms like Kaggle or create your datasets for analysis.

Build a Portfolio:
Create data analysis projects to showcase your skills. Share them on platforms like GitHub, where potential employers can see your work.

Networking:
Attend data-related meetups, conferences, and online communities. Networking can lead to job opportunities and valuable insights.

Data Analysis Projects:
Work on personal or freelance data analysis projects to gain experience and demonstrate your abilities.

Job Search:
Start applying for entry-level data analyst positions or internships. Look for job listings on company websites, job boards, and LinkedIn.
Jobs & Internship opportunities: @getjobss

Prepare for Interviews:
Practice common data analyst interview questions and be ready to discuss your past projects and experiences.

Continual Learning:
The field of data analysis is constantly evolving. Stay updated with new tools, techniques, and industry trends.

Soft Skills:
Develop soft skills like critical thinking, problem-solving, communication, and attention to detail, as they are crucial for data analysts.

Never ever give up:
The journey to becoming a data analyst can be challenging, with complex concepts and technical skills to learn. There may be moments of frustration and self-doubt, but remember that these are normal parts of the learning process. Keep pushing through setbacks, keep learning, and stay committed to your goal.

ENJOY LEARNING 👍👍

What each data job does:

📍 1. Data engineer - develops pipelines that generate high quality data

📍 2. Data analyst - answers business questions with historical data

📍 3. Data scientist - predicts future outcomes with ML models and patterns

📍4. Business analyst - translates user requirements to data teams, and technical insights to stakeholders

Tech stack of Data Analyst

3 Must-Learn Topics to Launch Your Data Analytics Career 📊

• SQL 💾
• Excel 📈
• Power BI 📊

Pro tip: Master these fundamentals, then expand your toolkit.

Everyone wants to jump to advanced topics, but these are your REAL foundation.

Start here. Crush it. 💪

#DataAnalytics

Don't stress too much on which tools to learn first.

Pickup 2-3 tools and master them. Skills are transferable.

For eg- If you can create an amazing dashboard in Power BI, you can make similar impressive dashboard in Tableau as well.

If you can run efficient queries in MySQL, it's going to be nearly same in PostgreSQL as well.

If you can manipulate fields in Excel, you can do the same stuff in Google Sheets as well.

Continuity is the key 😄

Never stop Learning ❤️

5 Data Analysis Projects ✅

Exploratory Data Analysis ( EDA)

3 Pillars of Data Analytics :

• Technical Skills :

- SQL
- Excel
- PowerBi

• Verbal Communication :

- Presentation
- Data Storytelling
- Stakeholder Analysis

• Written Communication :

- Reverse Brief
- Project Scoping
- Technical Documentation

Master these 3 pillars and you will become a great Data Analyst.

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Data Analysis Interview Questions and Answers
👇👇

1.How to create filters in Power BI?

Filters are an integral part of Power BI reports. They are used to slice and dice the data as per the dimensions we want. Filters are created in a couple of ways.

Using Slicers: A slicer is a visual under Visualization Pane. This can be added to the design view to filter our reports. When a slicer is added to the design view, it requires a field to be added to it. For example- Slicer can be added for Country fields. Then the data can be filtered based on countries.
Using Filter Pane: The Power BI team has added a filter pane to the reports, which is a single space where we can add different fields as filters. And these fields can be added depending on whether you want to filter only one visual(Visual level filter), or all the visuals in the report page(Page level filters), or applicable to all the pages of the report(report level filters)


2.How to sort data in Power BI?

Sorting is available in multiple formats. In the data view, a common sorting option of alphabetical order is there. Apart from that, we have the option of Sort by column, where one can sort a column based on another column. The sorting option is available in visuals as well. Sort by ascending and descending option by the fields and measure present in the visual is also available.


3.How to convert pdf to excel?

Open the PDF document you want to convert in XLSX format in Acrobat DC.
Go to the right pane and click on the “Export PDF” option.
Choose spreadsheet as the Export format.
Select “Microsoft Excel Workbook.”
Now click “Export.”
Download the converted file or share it.


4. How to enable macros in excel?

Click the file tab and then click “Options.”
A dialog box will appear. In the “Excel Options” dialog box, click on the “Trust Center” and then “Trust Center Settings.”
Go to the “Macro Settings” and select “enable all macros.”
Click OK to apply the macro settings.

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ENJOY LEARNING 👍👍

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