3๏ธโฃ Microsoft Excel might be your hammer, but not every problem is a nail.
Please, please, please use Excel where it makes sense!
If you reach a point where Excel doesn't make sense, know that you can quickly move on to technologies that are better suited for your needs....
#dataanalysis
Please, please, please use Excel where it makes sense!
If you reach a point where Excel doesn't make sense, know that you can quickly move on to technologies that are better suited for your needs....
#dataanalysis
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4๏ธโฃ SQL is your friend.
If you're unfamiliar, SQL is the language used to query databases.
After Microsoft Excel, SQL is the world's most commonly used data technology.
SQL is easily integrated into Excel, allowing you to leverage the power of the database server to acquire and wrangle data.
The results of all this goodness then show up in your workbook.
Also, SQL is straightforward for Excel users to learn.
#dataanalysis
If you're unfamiliar, SQL is the language used to query databases.
After Microsoft Excel, SQL is the world's most commonly used data technology.
SQL is easily integrated into Excel, allowing you to leverage the power of the database server to acquire and wrangle data.
The results of all this goodness then show up in your workbook.
Also, SQL is straightforward for Excel users to learn.
#dataanalysis
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5๏ธโฃ Python in Excel.
Microsoft is providing you with just what you need to scale beyond Excel limitations.
At first, you use Python in Excel because it's the easiest way to scale and tap into a vast amount of DIY data science goodness.
As 99% of the code you write for Python in Excel translates to any tool, you now have a path to move off of Excel if needed.
For example, Jupyter Notebooks and VS Code.
#dataanalysis
Microsoft is providing you with just what you need to scale beyond Excel limitations.
At first, you use Python in Excel because it's the easiest way to scale and tap into a vast amount of DIY data science goodness.
As 99% of the code you write for Python in Excel translates to any tool, you now have a path to move off of Excel if needed.
For example, Jupyter Notebooks and VS Code.
#dataanalysis
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TOP CONCEPTS FOR INTERVIEW PREPARATION!!
๐TOP 10 SQL Concepts for Job Interview
1. Aggregate Functions (SUM/AVG)
2. Group By and Order By
3. JOINs (Inner/Left/Right)
4. Union and Union All
5. Date and Time processing
6. String processing
7. Window Functions (Partition by)
8. Subquery
9. View and Index
10. Common Table Expression (CTE)
๐TOP 10 Statistics Concepts for Job Interview
1. Sampling
2. Experiments (A/B tests)
3. Descriptive Statistics
4. p-value
5. Probability Distributions
6. t-test
7. ANOVA
8. Correlation
9. Linear Regression
10. Logistics Regression
๐TOP 10 Python Concepts for Job Interview
1. Reading data from file/table
2. Writing data to file/table
3. Data Types
4. Function
5. Data Preprocessing (numpy/pandas)
6. Data Visualisation (Matplotlib/seaborn/bokeh)
7. Machine Learning (sklearn)
8. Deep Learning (Tensorflow/Keras/PyTorch)
9. Distributed Processing (PySpark)
10. Functional and Object Oriented Programming
Like โค๏ธ the post if it was helpful to you!!!
๐TOP 10 SQL Concepts for Job Interview
1. Aggregate Functions (SUM/AVG)
2. Group By and Order By
3. JOINs (Inner/Left/Right)
4. Union and Union All
5. Date and Time processing
6. String processing
7. Window Functions (Partition by)
8. Subquery
9. View and Index
10. Common Table Expression (CTE)
๐TOP 10 Statistics Concepts for Job Interview
1. Sampling
2. Experiments (A/B tests)
3. Descriptive Statistics
4. p-value
5. Probability Distributions
6. t-test
7. ANOVA
8. Correlation
9. Linear Regression
10. Logistics Regression
๐TOP 10 Python Concepts for Job Interview
1. Reading data from file/table
2. Writing data to file/table
3. Data Types
4. Function
5. Data Preprocessing (numpy/pandas)
6. Data Visualisation (Matplotlib/seaborn/bokeh)
7. Machine Learning (sklearn)
8. Deep Learning (Tensorflow/Keras/PyTorch)
9. Distributed Processing (PySpark)
10. Functional and Object Oriented Programming
Like โค๏ธ the post if it was helpful to you!!!
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9 secrets about Data Storytelling every analyst should know (number 6 is a must):
1/ Start with the end in mindโwhatโs the key takeaway?
2/ Donโt just present numbersโexplain the 'so what' behind them.
3/ Data should drive decisionsโframe your analysis as a solution to a problem.
#DataAnalytics
1/ Start with the end in mindโwhatโs the key takeaway?
2/ Donโt just present numbersโexplain the 'so what' behind them.
3/ Data should drive decisionsโframe your analysis as a solution to a problem.
#DataAnalytics
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4/ Visualise trends over time to tell a story.
5/ Add context to your dataโit makes your insights relevant.
6/ Speak the language of your audienceโsimplify complex terms.
5/ Add context to your dataโit makes your insights relevant.
6/ Speak the language of your audienceโsimplify complex terms.
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7/ Use metaphors or analogies to explain difficult concepts. Don't use professional jargon.
8/ Include both the big picture and the detailsโit appeals to different stakeholders.
9/ Conclude with a call to actionโwhat should they do next?
8/ Include both the big picture and the detailsโit appeals to different stakeholders.
9/ Conclude with a call to actionโwhat should they do next?
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How Data Analytics Helps to Grow Business to Best
Analytics are the analysis of raw data to draw meaningful insights from it. In other words, applying algorithms, statistical models, or even machine learning on large volumes of data will seek to discover patterns, trends, and correlations. In this way, the bottom line is to support businesses in making much more informed, data-driven decisions.
In simple words, think about running a retail store. Youโve got years of sales data, customer feedback, and inventory reports. However, do you know which are the best-sellers or where youโre losing money? By applying data analytics, you would find out some hidden opportunities, adjust your strategies, and improve your business outcome accordingly.
read more......
Analytics are the analysis of raw data to draw meaningful insights from it. In other words, applying algorithms, statistical models, or even machine learning on large volumes of data will seek to discover patterns, trends, and correlations. In this way, the bottom line is to support businesses in making much more informed, data-driven decisions.
In simple words, think about running a retail store. Youโve got years of sales data, customer feedback, and inventory reports. However, do you know which are the best-sellers or where youโre losing money? By applying data analytics, you would find out some hidden opportunities, adjust your strategies, and improve your business outcome accordingly.
read more......
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๐Roadmap to Becoming a Data Analyst๐
Start your journey with these key steps:-
1๏ธโฃ SQL: Master querying and managing data from databases.
2๏ธโฃ Python: Use Python for data manipulation and automation.
3๏ธโฃ Visualization: Present data using Matplotlib/Seaborn.
4๏ธโฃ Excel: Handle data and create quick insights.
5๏ธโฃ Power BI/Tableau: Build interactive dashboards.
6๏ธโฃ Statistics: Understand key concepts for data interpretation.
7๏ธโฃ Data Analytics: Apply everything in real-world projects!
#DataAnalyst
Start your journey with these key steps:-
1๏ธโฃ SQL: Master querying and managing data from databases.
2๏ธโฃ Python: Use Python for data manipulation and automation.
3๏ธโฃ Visualization: Present data using Matplotlib/Seaborn.
4๏ธโฃ Excel: Handle data and create quick insights.
5๏ธโฃ Power BI/Tableau: Build interactive dashboards.
6๏ธโฃ Statistics: Understand key concepts for data interpretation.
7๏ธโฃ Data Analytics: Apply everything in real-world projects!
#DataAnalyst
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Data Analyst: Analyzes data to provide insights and reports for decision-making.
Data Scientist: Builds models to predict outcomes and uncover deeper insights from data.
Data Engineer: Creates and maintains the systems that store and process data.
Data Scientist: Builds models to predict outcomes and uncover deeper insights from data.
Data Engineer: Creates and maintains the systems that store and process data.
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Don't make this mistake as a beginner data analyst:
Not learning SQL
There's a reason it's been around for 40+ years.
Get started with:
- SQL basics (syntax + structure)
- Data Manipulation (JOINs, GROUP BY etc)
- Aggregation Functions (SUM, AVG etc)
Not learning SQL
There's a reason it's been around for 40+ years.
Get started with:
- SQL basics (syntax + structure)
- Data Manipulation (JOINs, GROUP BY etc)
- Aggregation Functions (SUM, AVG etc)
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How to annoy a data analyst in 2024:
โ Assume the analysis you're asking is "just a quick SQL thing."
โ Ask to "tweak" a finished dashboard. It's never just a small change.
โ Question why the numbers in their carefully crafted dashboard don't match your hastily pulled spreadsheet.
โ Assume all data is clean, structured, and readily available. Spoiler: it's not.
โ After receiving a detailed, interactive dashboard, ask, "Can I just get this as a printable PDF?" ๐คฆ๐ฝโ๏ธ๐คฆ๐ฝโ๏ธ
โ Assume the analysis you're asking is "just a quick SQL thing."
โ Ask to "tweak" a finished dashboard. It's never just a small change.
โ Question why the numbers in their carefully crafted dashboard don't match your hastily pulled spreadsheet.
โ Assume all data is clean, structured, and readily available. Spoiler: it's not.
โ After receiving a detailed, interactive dashboard, ask, "Can I just get this as a printable PDF?" ๐คฆ๐ฝโ๏ธ๐คฆ๐ฝโ๏ธ
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Hi guys,
Many people charge too much to teach Excel, Power BI, SQL, Python & Tableau but my mission is to break down barriers. I have shared complete learning series to start your data analytics journey from scratch.
For those of you who are new to this channel, here are some quick links to navigate this channel easily.
Data Analyst Learning Plan ๐
https://t.iss.one/sqlspecialist/752
Python Learning Plan ๐
https://t.iss.one/sqlspecialist/749
Power BI Learning Plan ๐
https://t.iss.one/sqlspecialist/745
SQL Learning Plan ๐
https://t.iss.one/sqlspecialist/738
SQL Learning Series ๐
https://t.iss.one/sqlspecialist/567
Excel Learning Series ๐
https://t.iss.one/sqlspecialist/664
Power BI Learning Series ๐
https://t.iss.one/sqlspecialist/768
Python Learning Series ๐
https://t.iss.one/sqlspecialist/615
Tableau Essential Topics ๐
https://t.iss.one/sqlspecialist/667
Best Data Analytics Resources ๐
https://heylink.me/DataAnalytics
You can find more resources on Medium & Linkedin
Like for more โค๏ธ
Thanks to all who support our channel and share it with friends & loved ones. You guys are really amazing.
Hope it helps :)
Many people charge too much to teach Excel, Power BI, SQL, Python & Tableau but my mission is to break down barriers. I have shared complete learning series to start your data analytics journey from scratch.
For those of you who are new to this channel, here are some quick links to navigate this channel easily.
Data Analyst Learning Plan ๐
https://t.iss.one/sqlspecialist/752
Python Learning Plan ๐
https://t.iss.one/sqlspecialist/749
Power BI Learning Plan ๐
https://t.iss.one/sqlspecialist/745
SQL Learning Plan ๐
https://t.iss.one/sqlspecialist/738
SQL Learning Series ๐
https://t.iss.one/sqlspecialist/567
Excel Learning Series ๐
https://t.iss.one/sqlspecialist/664
Power BI Learning Series ๐
https://t.iss.one/sqlspecialist/768
Python Learning Series ๐
https://t.iss.one/sqlspecialist/615
Tableau Essential Topics ๐
https://t.iss.one/sqlspecialist/667
Best Data Analytics Resources ๐
https://heylink.me/DataAnalytics
You can find more resources on Medium & Linkedin
Like for more โค๏ธ
Thanks to all who support our channel and share it with friends & loved ones. You guys are really amazing.
Hope it helps :)
โค9๐8๐ฅ2
โ
๐-๐๐ญ๐๐ฉ ๐๐จ๐๐๐ฆ๐๐ฉ ๐ญ๐จ ๐๐ฐ๐ข๐ญ๐๐ก ๐ข๐ง๐ญ๐จ ๐ญ๐ก๐ ๐๐๐ญ๐ ๐๐ง๐๐ฅ๐ฒ๐ญ๐ข๐๐ฌ ๐
๐ข๐๐ฅ๐โ
๐โโ๏ธ๐๐ฎ๐ข๐ฅ๐ ๐๐๐ฒ ๐๐ค๐ข๐ฅ๐ฅ๐ฌ: Focus on core skillsโExcel, SQL, Power BI, and Python.
๐โโ๏ธ๐๐๐ง๐๐ฌ-๐๐ง ๐๐ซ๐จ๐ฃ๐๐๐ญ๐ฌ: Apply your skills to real-world data sets. Projects like sales analysis or customer segmentation show your practical experience. You can find projects on Youtube.
๐โโ๏ธ๐ ๐ข๐ง๐ ๐ ๐๐๐ง๐ญ๐จ๐ซ: Connect with someone experienced in data analytics for guidance(like me ๐ ). They can provide valuable insights, feedback, and keep you on track.
๐โโ๏ธ๐๐ซ๐๐๐ญ๐ ๐๐จ๐ซ๐ญ๐๐จ๐ฅ๐ข๐จ: Compile your projects in a portfolio or on GitHub. A solid portfolio catches a recruiterโs eye.
๐โโ๏ธ๐๐ซ๐๐๐ญ๐ข๐๐ ๐๐จ๐ซ ๐๐ง๐ญ๐๐ซ๐ฏ๐ข๐๐ฐ๐ฌ: Practice SQL queries and Python coding challenges on Hackerrank & LeetCode. Strengthening your problem-solving skills will prepare you for interviews.
๐โโ๏ธ๐๐ฎ๐ข๐ฅ๐ ๐๐๐ฒ ๐๐ค๐ข๐ฅ๐ฅ๐ฌ: Focus on core skillsโExcel, SQL, Power BI, and Python.
๐โโ๏ธ๐๐๐ง๐๐ฌ-๐๐ง ๐๐ซ๐จ๐ฃ๐๐๐ญ๐ฌ: Apply your skills to real-world data sets. Projects like sales analysis or customer segmentation show your practical experience. You can find projects on Youtube.
๐โโ๏ธ๐ ๐ข๐ง๐ ๐ ๐๐๐ง๐ญ๐จ๐ซ: Connect with someone experienced in data analytics for guidance(like me ๐ ). They can provide valuable insights, feedback, and keep you on track.
๐โโ๏ธ๐๐ซ๐๐๐ญ๐ ๐๐จ๐ซ๐ญ๐๐จ๐ฅ๐ข๐จ: Compile your projects in a portfolio or on GitHub. A solid portfolio catches a recruiterโs eye.
๐โโ๏ธ๐๐ซ๐๐๐ญ๐ข๐๐ ๐๐จ๐ซ ๐๐ง๐ญ๐๐ซ๐ฏ๐ข๐๐ฐ๐ฌ: Practice SQL queries and Python coding challenges on Hackerrank & LeetCode. Strengthening your problem-solving skills will prepare you for interviews.
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