3 Trends in Data Analytics: From 2023 to 2024
Hello, friends! I hope you're well-rested and ready to work? Today, let's talk about what made 2023 memorable and what will continue to gain momentum in 2024.
#1 Artificial Intelligence in Analytics
The combination of "Analytics + AI" seems to be with us forever now.
🔸 PowerBI, Tableau, and others have implemented AI
🔸 ChatGPT released Data Analyst
🔸 Numerous startups with analytics and AI
#2 Self-Service Analytics and "Data Democratization"
People without a technical background and without the help of an analyst can now:
🔸 Access data quickly (using natural language database queries)
🔸 Perform simple analysis in seconds
All this is thanks to AI and intuitive interfaces.
Despite the disappointment with AI in 2023 and the realization of its limitations, ignoring this trend would be a mistake. Gartner predicts that by 2024, 75% of organizations will use AI for analytics.
#3 Embedded Analytics
Analytics is being integrated into various applications and processes, improving decision-making and allowing users to independently find and solve problems, as well as find ways to improve. Examples:
🔸 Kodak has embedded analytics in its software for printing machines, allowing for tracking of ink usage efficiency
🔸 Shopify offers analytics tools on its dashboard for merchants to track sales, customer behavior, and other key business metrics.
In conclusion, all these processes will not replace an analyst. They are just a powerful tool for in-depth work and reducing manual labor.
Wishing everyone successful analysis in 2024!
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
Hello, friends! I hope you're well-rested and ready to work? Today, let's talk about what made 2023 memorable and what will continue to gain momentum in 2024.
#1 Artificial Intelligence in Analytics
The combination of "Analytics + AI" seems to be with us forever now.
🔸 PowerBI, Tableau, and others have implemented AI
🔸 ChatGPT released Data Analyst
🔸 Numerous startups with analytics and AI
#2 Self-Service Analytics and "Data Democratization"
People without a technical background and without the help of an analyst can now:
🔸 Access data quickly (using natural language database queries)
🔸 Perform simple analysis in seconds
All this is thanks to AI and intuitive interfaces.
Despite the disappointment with AI in 2023 and the realization of its limitations, ignoring this trend would be a mistake. Gartner predicts that by 2024, 75% of organizations will use AI for analytics.
#3 Embedded Analytics
Analytics is being integrated into various applications and processes, improving decision-making and allowing users to independently find and solve problems, as well as find ways to improve. Examples:
🔸 Kodak has embedded analytics in its software for printing machines, allowing for tracking of ink usage efficiency
🔸 Shopify offers analytics tools on its dashboard for merchants to track sales, customer behavior, and other key business metrics.
In conclusion, all these processes will not replace an analyst. They are just a powerful tool for in-depth work and reducing manual labor.
Wishing everyone successful analysis in 2024!
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
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SimilarWeb can significantly overstate website visit statistics, so:
1. Don't fully trust when someone shows you statistics from SW
2. Don't use SW for the analysis of your website; use Google Analytics.
GA collects more accurate data. Similarweb collects data from available sources and makes estimates and predictions using machine learning.
Anyway, it's a good tool for competitor analytics.
A visit can be roughly equated to a session start in Google Analytics.
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
1. Don't fully trust when someone shows you statistics from SW
2. Don't use SW for the analysis of your website; use Google Analytics.
GA collects more accurate data. Similarweb collects data from available sources and makes estimates and predictions using machine learning.
Anyway, it's a good tool for competitor analytics.
A visit can be roughly equated to a session start in Google Analytics.
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
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I completed one of the simulators to recommend it to you.
These simulators are suitable for those who want to practice on real tasks and understand what a data analyst does at leading companies.
- Online simulators imitate a workday at top companies
- No prior knowledge is required – the necessary information is provided for task completion
- In the end, you receive a certificate and the opportunity to connect with recruiters
Register ➡️ Receive video instructions from real employees ➡️ Complete the task ➡️ Compare your work with the company’s example ➡️ Upload your resume ➡️ Receive a certificate and the opportunity to connect with recruiters.
1. Data Analytics & Visualization at Accenture (a leading consulting firm from the Fortune Global 500 list)
2. Power BI at PwC (a consulting firm from the "Big Four")
3. Data Analytics at Quantium (a company specializing in data science and AI)
4. Data Visualisation: Empowering Business with Effective Insights at Tata (a multinational conglomerate operating in 150 countries)
All data-related simulators are here.
Simulators for other skills (marketing, project management, consulting, etc.) are here.
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
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Below are popular data analysis projects from Kaggle, Github, and Medium users. They will:
- Help you gain skills in working with real data
- Introduce you to Python libraries for data analysis
- Inspire you for your own data analysis projects
#data_analyst #data_analysis #data_projects
⚡️ADIDAS Sales Analysis
⚡️ Zomato Data Analysis
🍫 Product Sales Analysis
🚕 Uber Rides Data Analysis
🎮 Video Game Sales Analysis
🤓 Is There a Trend of Increasing Geek Girls?
🏆 Let's Discover More About the Olympic Games!
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst #python
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I made 2 diagrams
_____________________________________
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst #python
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What is IT volunteering? It's about helping non-profit organizations that can't afford to hire IT specialists for tasks like data analysis, programming, and marketing. Usually, this work is project-based rather than a permanent job.
Benefits:
1. Gain experience and add to your portfolio
2. Get recommendations for your resume
3. Help others at the same time
Here is the list of platforms where you can volunteer your data analytics skills:
Сatchafire
Datakind
Statisticswithoutborders
Vizforsocialgood
Technologyvolunteers
If you can't find the right tasks on websites, you can take the initiative and offer your skills directly to a non-profit organization you know.
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
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Recently, I noticed freeCodeCamp.org has a course called "Data Analysis with Python". This course teaches Python specifically for data analysis.
freeCodeCamp.org also has other free courses with certificates to further expand your knowledge:
- Algebra with Python (which gives a deeper understanding of math and data science)
- Machine Learning (which is useful for data analysts since many companies now require machine learning skills).
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
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Below are popular data projects from Kaggle, GitHub and Medium and YouTube. They will:
- Help you gain skills in working with real data
- Introduce you to SQL for data analysis
- Inspire you to undertake your own data analysis projects
🛣 UK Road Safety Analysis Project 2015
💸 International Debt Analysis using SQL
🌍 World Population Analysis 2015 using SQL
🚍 Public Transportation Data Analysis using SQL
Other posts:
🔥 20 Step-by-Step Data Analysis Projects with Python Code
🔥 Free Data Job Simulation Programs with Certificate
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst #sql
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For example, take a mock interview or at least watch one.
A mock interview is a practice interview that closely mimics a real one. In a mock interview, an experienced data analyst tests a less experienced person's knowledge and skills.
Benefits of a Mock Interview:
⚡️ Feedback and Evaluation: It's hard to get this in a real interview.
⚡️ Understanding Weaknesses: You'll know what areas you need to improve.
⚡️ Increased Confidence: You'll feel more prepared for the real interview.
It's best to do a mock interview with an experienced mentor. To find a mentor you can try platforms like Preplaced, interviewing.io, mentorcruise.com
If you can't find a mentor, there are many mock interview videos online. These can give you a good understanding of the process and questions and help you avoid mistakes.
Examples:
- Mock Interview & Feedback: Data Analyst
- Analyze a User's Posts - Data Analyst SQL Mock Interview
- SQL Mock Interview (Data Analyst): Departments with the Highest Revenues
Google offers Interview Warmup. You can practice answering questions and get quick feedback on your answers. This helps you get better and feel more confident for real interviews.
#DataAnalyst #DataAnalytics #DataAnalysis #data_analyst
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When you start learning SQL and Python, you need lots of practice. It's great if you have real tasks at work, but if not, I recommend these free services. They will help you get the practice you need and improve your skills.
1. HackerRank
⚡️ You can practice many different languages, including SQL and Python.
⚡️ You can get certified in technical skills by taking the HackerRank Skills Certification Test.
⚡️ HackerRank is completely free.
2. StrataScratch
⚡️ It's a data science platform with over 1,000 real interview questions (coding and non-coding) from top companies like Google, Netflix, Apple, Airbnb, and Spotify.
⚡️ New interview questions come out every month, and many are free.
3. LeetCode
⚡️ It has lots of coding challenges from big companies like Google, Facebook, Amazon, and Microsoft to help you get better at algorithms and data structures.
⚡️ New problems are added all the time, and many are free.
Watch my video
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This question often comes up in the comments. Let's break it down👇🏻.
⚡️ Can you work on the simplest laptop?
In many companies, analysts work with small datasets and perform simple operations, so basic configurations are sufficient.
Even if you have a cheap laptop and need more computing power, you can solve this problem with a remote desktop. This allows you to use the computing resources of a remote device while staying on your own.
⚡️ Can you work on a tablet?
Even powerful tablets like the Apple iPad Pro are not suitable for data analysis. They do not have enough power and compatibility with the necessary software (Python, Power BI, Tableau, and Excel).
⚡️ What to look for when choosing a laptop?
👉 Processor power. An Intel Core i7 or i9, or an AMD Ryzen 7 or 9, will provide fast data processing and complex computations.
👉 RAM. At least 16 GB of RAM for working with large datasets and multitasking. For more demanding tasks, 32 GB or more is recommended.
👉 Display. High resolution (Full HD or higher) and good color reproduction. For comfortable work, a screen size of 15 to 17 inches is better.
👉 Support for the necessary operating system (Windows, macOS, Linux). For example, the visualization tool Power BI does not have a full version that works on macOS (though this problem can be solved with a virtual machine).
When it comes to specific brands, one of the most popular among data analysts is the Apple MacBook Pro (M2).
What laptop do you use? And what other factors should be considered when choosing a laptop?
❗️Subscribe: Analytics and growth mindset
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A 10-hour course prepares entry-level data analysts for the job market, providing basic employment process information. Rated 4.6/5 on Coursera.
*IBM is one of the largest IT companies in the world.
Part 1:
1. How to create a resume and portfolio
2. How to effectively present yourself
3. How to understand the different types of data analysts
Part 2:
1. How to research companies where you want to interview
2. How to evaluate a job posting
3. How to rehearse and prepare for an interview
Part 3:
1. How the interview process works
2. About the coding challenge
3. Interview questions and how to answer them
4. What to do after the interview
The course is here.
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