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Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun

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З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 53 286 підписників.

За останніми даними від 31 жовтня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 34, а за останні 24 години на -18, загальне охоплення залишається високим.

Статус верифікації: Не верифікований
Рівень залученості (ER): Середній показник залученості аудиторії становить 7.05%. Протягом перших 24 годин після публікації контент зазвичай збирає 1.16% реакцій від загальної кількості підписників.
Охоплення публікацій: В середньому кожен допис отримує 0 переглядів. Протягом першої доби публікація в середньому набирає 616 переглядів.
Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 0.
Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як analyst, |--, excel, visualization, analytic.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Data Analysis Useful Resources #dataanalysis #dataanalysisbooks #sqlbooks #pythonbooks #tableau #powerbi #datavisualization For promotions: @coderfun”

Завдяки високій частоті оновлень (останні дані отримано 01 листопада, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.

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-1824 години

-427 днів

+3430 днів

3 759

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~ 61624 години

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7.05%

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Starting as a data analyst is a great first step in your career. As you grow, you might discover new interests: • If you love working with statistics and machine learning, you could move into Data Science. • If you're excited by building data systems and pipelines, Data Engineering might be your next step. • If you're more interested in understanding the business side, you could become a Business Analyst. Even if you decide to stay in your data analyst role, there's always something new to learn, especially with advancements in AI. There are many paths to explore, but what's important is taking that first step. I have curated best 80+ top-notch Data Analytics Resources 👇👇 https://topmate.io/analyst/861634 Hope this helps you 😊

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If you can't find a data role, follow this path (that I tried and tested): 📍 1. Get skills (Excel, SQL, Power BI) 📍 2. Build projects 📍 3. Get a semi-data role (any role that only needs basic data skills e.g. Excel) Heres what you should use your data skills for in this role: 📍 1. Help your team (eg. automate reports, build dashboards) 📍 2. Add this experience to your resume 📍 3. Share this experience online This allows you to gain real world experience while practicing your skills

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Career Path for a Data Analyst Education: Start by earning a bachelor's degree in fields like math, stats, economics, or computer science. Skills Growth: Learn programming (Python/R), data tools (SQL/Excel), and visualization. Master data analysis basics. Entry-Level Role: Begin as a Junior Data Analyst. Learn data cleaning, organization, and basic analysis. Specialization: Deepen your expertise in a specific industry. Explore advanced analytics and visualization tools. Advanced Analytics: Move up to Senior Data Analyst. Tackle complex projects and predictive modeling. Machine Learning: Explore machine learning and data modeling techniques. Familiarize yourself with algorithms, and learn how to implement predictive and classification models. Domain Expertise: Develop expertise in a particular industry, such as healthcare, finance, e-commerce, etc. This knowledge will enable you to provide more valuable insights from data. Leadership Roles: As you gain experience, you can move into roles like Data Analytics Manager or Data Science Manager, where you'll oversee teams and projects. Continuous Learning: Stay updated with the latest tools, techniques, and industry trends. Attend workshops, conferences, and online courses to keep your skills relevant. Networking: Build a strong professional network within the data analytics community. This can open up opportunities and help you stay informed about industry developments. Remember, your career path can be personalized based on your interests and strengths. Continuous learning and adaptability are key in the ever-evolving field of data analysis :)

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Data Science Roadmap

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𝗚𝗲𝘁 𝗬𝗼𝘂𝗿 𝗗𝗿𝗲𝗮𝗺 𝗝𝗼𝗯 𝗜𝗻 𝗔𝗺𝗮𝘇𝗼𝗻, 𝗚𝗼𝗼𝗴𝗹𝗲, 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁, 𝗡𝗩𝗜𝗗𝗜𝗔, 𝗮𝗻𝗱 𝗠𝗲𝘁𝗮 (𝗙𝗮𝗰𝗲𝗯𝗼𝗼𝗸) 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲𝘀𝗲 𝗰𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀😍 1️⃣ Amazon Interviewing Guide 2️⃣ Google Interview Tips 3️⃣ Microsoft Hiring Tips 4️⃣ NVIDIA Hiring Process 5️⃣ Meta Onsite SWE Prep Guide 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/40OSJJ6 Crack Interview & Get Your Dream Job In Top MNCs

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7 Baby steps to start with Machine Learning: 1. Start with Python 2. Learn to use Google Colab 3. Take a Pandas tutorial 4. Then a Seaborn tutorial 5. Decision Trees are a good first algorithm 6. Finish Kaggle's "Intro to Machine Learning" 7. Solve the Titanic challenge

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𝟱 𝗙𝗥𝗘𝗘 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍 Ready to dive into the world of Machine Learning? Here are 5 powerful resources that will guide you every step of the way—from beginner concepts to advanced techniques. 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/40wyXk8 Enroll For FREE & Get Certified🎓

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Data Analyst Roadmap Like if it helps ❤️

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Data Analytics Roadmap 👆

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𝗢𝗿𝗮𝗰𝗹𝗲 𝗦𝗤𝗟 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲😍 Learn SQL in this FREE 12-part boot camp. It will help you get started with Oracle Database and SQL. Complete the course to get your free certificate. 𝐋𝐢𝐧𝐤 👇:- https://pdlink.in/3P75GaB Enroll For FREE & Get Certified🎓

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Join Biggest Telegram channel for data analysts 👇👇 https://t.me/sqlspecialist

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Repost from Data Science & Machine Learning Resources

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. ————————————————————- ENJOY LEARNING 👍👍

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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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Exploratory Data Analysis ( EDA)

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5 Data Analysis Projects ✅

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