DataSphere
https://1drv.ms/x/c/AA015A5567412470/IQCy6_bGks_-Q5E6bz8AnOFkAYM5D3RWsE8wcalI86ANxas?e=hbfgLd
I opened Microsoft Excel today and easily completed 5 hours of work in 5 minutes with the help of Claude AI. I recommend it to you too. It's amazing :)
DataSphere
#excel
MOS RAVISHDA KPI VA GRAFIKLAR IZOHI : 1.Filtrga mos mijozlar umumiy soni
2.Term deposit ochgan ("ha" degan) mijozlar
3.Subscribed ÷ Total
4.Mijoz moliyaviy salohiyati
5.O'rtacha qo'ng'iroq davomiyligi
6.O'rtacha yosh(Demografik markaz)
7.Subscription by Job (BarStacked) — har bir kasb bo'yicha Yes/No taqsimoti. → Qaysi kasb egalari ko'proq obuna bo'ladi
8.Marital Status (Pie) — oilaviy holat bo'yicha mijozlar ulushi
9.Contacts vs Conversions by Month (Line) — oylar bo'yicha qo'ng'iroqlar va konversiyalar. → May eng ko'p qo'ng'iroq qilingan oy (13,721), ammo conversion rate past. Mart, sentabr, oktabr, dekabr — kam qo'ng'iroq, lekin yuqori conversion %
10.Subscription by Age Band (ColumnStacked) — yosh guruhlari bo'yicha Yes/No.
11.Subscription by Education (AreaStacked) — ta'lim darajasi bo'yicha. → Tertiary (oliy ta'lim) eng yuqori conversion ko'rsatadi
12.Previous Campaign Outcome (Doughnut) — oldingi kampaniya natijalari
13.Housing & Loan vs Subscription % (BarStacked100) — uy/shaxsiy krediti bor/yo'qlarning conversion ulushi.
14.Contact Method (Pie) — aloqa kanali
2.Term deposit ochgan ("ha" degan) mijozlar
3.Subscribed ÷ Total
4.Mijoz moliyaviy salohiyati
5.O'rtacha qo'ng'iroq davomiyligi
6.O'rtacha yosh(Demografik markaz)
7.Subscription by Job (BarStacked) — har bir kasb bo'yicha Yes/No taqsimoti. → Qaysi kasb egalari ko'proq obuna bo'ladi
8.Marital Status (Pie) — oilaviy holat bo'yicha mijozlar ulushi
9.Contacts vs Conversions by Month (Line) — oylar bo'yicha qo'ng'iroqlar va konversiyalar. → May eng ko'p qo'ng'iroq qilingan oy (13,721), ammo conversion rate past. Mart, sentabr, oktabr, dekabr — kam qo'ng'iroq, lekin yuqori conversion %
10.Subscription by Age Band (ColumnStacked) — yosh guruhlari bo'yicha Yes/No.
11.Subscription by Education (AreaStacked) — ta'lim darajasi bo'yicha. → Tertiary (oliy ta'lim) eng yuqori conversion ko'rsatadi
12.Previous Campaign Outcome (Doughnut) — oldingi kampaniya natijalari
13.Housing & Loan vs Subscription % (BarStacked100) — uy/shaxsiy krediti bor/yo'qlarning conversion ulushi.
14.Contact Method (Pie) — aloqa kanali
DataSphere
Photo
Ushbu loyiha sug'urta sohasida sun'iy intellektni joriy etish samaradorligini o'lchovchi matematik modeling raqamli egizagidir. Unda murakkab DAX algoritmlari orqali xom ma'lumotlar strategik tushunchalarga (insights) aylantirilgan.
Forwarded from Data Analytics
🚀 Top 100 Data Analyst Interview Questions
🧠 Data Analyst Role Basics
1. What does a data analyst do in a company?
2. What is the difference between a data analyst, data scientist, and BI analyst?
3. What is the typical workflow of a data analyst (from requirement to insight)?
4. What are the main goals of data analysis (descriptive, diagnostic, predictive, prescriptive)?
5. What is KPI and why is it important?
6. What is the difference between metrics and KPIs?
7. What is a dashboard vs a report?
8. What is exploratory data analysis (EDA)?
9. What is the difference between raw data and processed data?
10. How do you prioritize which analysis to work on first?
📊 SQL Databases
11. What is SQL and why is it critical for data analysts?
12. How do SELECT, WHERE, ORDER BY, LIMIT work?
13. How do you join two tables (INNER, LEFT, RIGHT, FULL joins)?
14. How do GROUP BY and aggregate functions (SUM, AVG, COUNT, MAX, MIN) work?
15. How do you write subqueries and CTEs?
16. How do you calculate running totals or rolling averages with window functions?
17. How do you clean and filter data directly in SQL?
18. How do you handle duplicates and NULL values in SQL?
19. How do you optimize a slow query?
20. How do you design a simple schema for a business domain (e.g., orders, users)?
🧮 Excel Spreadsheets
21. How do you use Excel for quick data cleaning and analysis?
22. How do you use SUMIF, COUNTIF, VLOOKUP / XLOOKUP in Excel?
23. How do you remove duplicates and standardize text in Excel?
24. How do you use PivotTables for summarizing data?
25. How do you build simple dashboards in Excel (charts + slicers)?
26. How do you use conditional formatting for insights?
27. How do you export data to CSV or share formatted reports?
28. How do you handle large datasets in Excel vs a database?
29. How do you avoid common Excel pitfalls (e.g., hard‑coded numbers, no labels)?
30. How do you document your Excel analyses?
📈 Data Visualization BI Tools
31. What is the purpose of data visualization?
32. When do you use bar charts, line charts, pie charts, histograms?
33. What are best practices for labeling, colors, and readability?
34. How do you design a dashboard for a non‑technical stakeholder?
35. What is the difference between a report and a self‑service dashboard?
36. How do you use Power BI / Tableau / Looker / Google Data Studio for dashboards?
37. How do you filter and slice data in a BI tool?
38. How do you handle measures and dimensions in BI tools?
39. How do you share dashboards and control access?
40. How do you tell a “data story” using charts and annotations?
📊 Descriptive Statistics EDA
41. What are mean, median, and mode?
42. What is standard deviation and variance?
43. What are quartiles and IQR?
44. How do you detect outliers and what should you do with them?
45. What is a distribution and how do you inspect it (histograms, boxplots)?
46. What is skewness and kurtosis?
47. How do you calculate growth rate, percentage change, CAGR?
48. How do you compute cohort‑style metrics (e.g., retention by signup month)?
49. How do you summarize categorical vs numerical data?
50. How do you structure an EDA notebook or report?
🛠️ Python (or R) for Data Analysis
51. Why do data analysts use Python instead of (or along with) Excel?
52. How do you load data from CSV or SQL into a pandas DataFrame?
53. How do you inspect the first/last rows, shape, data types, and missing values?
54. How do you clean missing values (dropna, fillna, interpolation)?
55. How do you filter, sort, and group data with pandas?
56. How do you calculate aggregates and pivots with groupby and pivot_table?
🧠 Data Analyst Role Basics
1. What does a data analyst do in a company?
2. What is the difference between a data analyst, data scientist, and BI analyst?
3. What is the typical workflow of a data analyst (from requirement to insight)?
4. What are the main goals of data analysis (descriptive, diagnostic, predictive, prescriptive)?
5. What is KPI and why is it important?
6. What is the difference between metrics and KPIs?
7. What is a dashboard vs a report?
8. What is exploratory data analysis (EDA)?
9. What is the difference between raw data and processed data?
10. How do you prioritize which analysis to work on first?
📊 SQL Databases
11. What is SQL and why is it critical for data analysts?
12. How do SELECT, WHERE, ORDER BY, LIMIT work?
13. How do you join two tables (INNER, LEFT, RIGHT, FULL joins)?
14. How do GROUP BY and aggregate functions (SUM, AVG, COUNT, MAX, MIN) work?
15. How do you write subqueries and CTEs?
16. How do you calculate running totals or rolling averages with window functions?
17. How do you clean and filter data directly in SQL?
18. How do you handle duplicates and NULL values in SQL?
19. How do you optimize a slow query?
20. How do you design a simple schema for a business domain (e.g., orders, users)?
🧮 Excel Spreadsheets
21. How do you use Excel for quick data cleaning and analysis?
22. How do you use SUMIF, COUNTIF, VLOOKUP / XLOOKUP in Excel?
23. How do you remove duplicates and standardize text in Excel?
24. How do you use PivotTables for summarizing data?
25. How do you build simple dashboards in Excel (charts + slicers)?
26. How do you use conditional formatting for insights?
27. How do you export data to CSV or share formatted reports?
28. How do you handle large datasets in Excel vs a database?
29. How do you avoid common Excel pitfalls (e.g., hard‑coded numbers, no labels)?
30. How do you document your Excel analyses?
📈 Data Visualization BI Tools
31. What is the purpose of data visualization?
32. When do you use bar charts, line charts, pie charts, histograms?
33. What are best practices for labeling, colors, and readability?
34. How do you design a dashboard for a non‑technical stakeholder?
35. What is the difference between a report and a self‑service dashboard?
36. How do you use Power BI / Tableau / Looker / Google Data Studio for dashboards?
37. How do you filter and slice data in a BI tool?
38. How do you handle measures and dimensions in BI tools?
39. How do you share dashboards and control access?
40. How do you tell a “data story” using charts and annotations?
📊 Descriptive Statistics EDA
41. What are mean, median, and mode?
42. What is standard deviation and variance?
43. What are quartiles and IQR?
44. How do you detect outliers and what should you do with them?
45. What is a distribution and how do you inspect it (histograms, boxplots)?
46. What is skewness and kurtosis?
47. How do you calculate growth rate, percentage change, CAGR?
48. How do you compute cohort‑style metrics (e.g., retention by signup month)?
49. How do you summarize categorical vs numerical data?
50. How do you structure an EDA notebook or report?
🛠️ Python (or R) for Data Analysis
51. Why do data analysts use Python instead of (or along with) Excel?
52. How do you load data from CSV or SQL into a pandas DataFrame?
53. How do you inspect the first/last rows, shape, data types, and missing values?
54. How do you clean missing values (dropna, fillna, interpolation)?
55. How do you filter, sort, and group data with pandas?
56. How do you calculate aggregates and pivots with groupby and pivot_table?
Forwarded from Data Analytics
60. How do you compute month-on-month or week-on-week growth?
61. How do you write a query to calculate retention / churn?
62. How do you calculate LTV (lifetime value) conceptually?
63. How do you write a funnel analysis query (e.g., sign-up → activation → purchase)?
64. How do you handle time-based aggregations (daily, weekly, monthly)?
65. How do you compare cohorts (e.g., users by month of acquisition)?
66. How do you calculate lead-time, cycle-time, or other business-process metrics?
67. How do you implement A/B test-style analysis in SQL?
68. How do you approximate segmentation (RFM-style) in SQL?
69. How do you document and version your SQL queries?
🧠 Behavioral Business-Sense Questions
70. Walk me through a real-world analysis you did end-to-end.
71. Tell me about a time you presented insights to a non-technical audience.
72. Tell me about a time your analysis changed a decision or strategy.
73. Tell me about a time you found a data quality issue and how you fixed it.
74. How do you translate a vague business question into a concrete analysis?
75. How do you handle conflicting priorities from stakeholders?
76. How do you collaborate with product, marketing, and engineering teams?
77. How do you validate your analysis before sharing it?
78. How do you explain statistical or technical concepts in simple language?
79. How do you stay updated with data-analysis trends and tools?
📊 Real-World Case-Study / Scenario-Style Questions
80. Design an analysis to track product usage or feature adoption.
81. Design an analysis to evaluate marketing campaign performance.
82. Design a churn / retention dashboard for a SaaS product.
83. Design a sales-performance report for a regional team.
84. Design a customer-segmentation analysis (e.g., high-value vs low-value).
85. How would you analyze a sudden drop in website traffic or orders?
86. How would you analyze a pricing change or discount test?
87. How would you analyze customer support ticket volume and trends?
88. How would you design a simple A/B test and its success metrics?
89. How would you explain results and next steps to a manager?
🧠 Tooling, Processes Best Practices
90. What tools do you use most often as a data analyst?
91. How do you version your code and SQL (e.g., Git, folder structure)?
92. How do you document queries, dashboards, and assumptions?
93. How do you handle data privacy and PII in your analyses?
94. How do you manage permissions and access to dashboards?
95. How do you automate repetitive reports (scheduled exports, SQL jobs, etc.)?
96. How do you handle ad-hoc vs recurring analyses?
97. How do you get feedback on your dashboards and improve them?
98. What are your top 5 productivity shortcuts / habits as a data analyst?
99. What skills do you want to improve most in the next 6–12 months?
🚀 Double Tap ♥️ For Detailed Answers
61. How do you write a query to calculate retention / churn?
62. How do you calculate LTV (lifetime value) conceptually?
63. How do you write a funnel analysis query (e.g., sign-up → activation → purchase)?
64. How do you handle time-based aggregations (daily, weekly, monthly)?
65. How do you compare cohorts (e.g., users by month of acquisition)?
66. How do you calculate lead-time, cycle-time, or other business-process metrics?
67. How do you implement A/B test-style analysis in SQL?
68. How do you approximate segmentation (RFM-style) in SQL?
69. How do you document and version your SQL queries?
🧠 Behavioral Business-Sense Questions
70. Walk me through a real-world analysis you did end-to-end.
71. Tell me about a time you presented insights to a non-technical audience.
72. Tell me about a time your analysis changed a decision or strategy.
73. Tell me about a time you found a data quality issue and how you fixed it.
74. How do you translate a vague business question into a concrete analysis?
75. How do you handle conflicting priorities from stakeholders?
76. How do you collaborate with product, marketing, and engineering teams?
77. How do you validate your analysis before sharing it?
78. How do you explain statistical or technical concepts in simple language?
79. How do you stay updated with data-analysis trends and tools?
📊 Real-World Case-Study / Scenario-Style Questions
80. Design an analysis to track product usage or feature adoption.
81. Design an analysis to evaluate marketing campaign performance.
82. Design a churn / retention dashboard for a SaaS product.
83. Design a sales-performance report for a regional team.
84. Design a customer-segmentation analysis (e.g., high-value vs low-value).
85. How would you analyze a sudden drop in website traffic or orders?
86. How would you analyze a pricing change or discount test?
87. How would you analyze customer support ticket volume and trends?
88. How would you design a simple A/B test and its success metrics?
89. How would you explain results and next steps to a manager?
🧠 Tooling, Processes Best Practices
90. What tools do you use most often as a data analyst?
91. How do you version your code and SQL (e.g., Git, folder structure)?
92. How do you document queries, dashboards, and assumptions?
93. How do you handle data privacy and PII in your analyses?
94. How do you manage permissions and access to dashboards?
95. How do you automate repetitive reports (scheduled exports, SQL jobs, etc.)?
96. How do you handle ad-hoc vs recurring analyses?
97. How do you get feedback on your dashboards and improve them?
98. What are your top 5 productivity shortcuts / habits as a data analyst?
99. What skills do you want to improve most in the next 6–12 months?
🚀 Double Tap ♥️ For Detailed Answers
DataSphere
www.youtube.com/@tqqt_llc
ML o'rganaman deydiganlar uchun yaxshi kanal
Forwarded from Azim Pulat
Million inson uchun tizimlar qanday quriladi?
Videoda:
- Barcha kompaniyalarda uchraydigan kengayishdagi muammolar
- Kam xarajat bilan ko'plab insonlarga xizmat ko’rsatish
- Amazon, Facebook, Googledagi tizim dizaynidagi tajribalarim
- Tizim Dizaynini qanday tizimli o'rganish
haqida gapirdim.
Havola: youtu.be/g2g62uyBp88
Videoda:
- Barcha kompaniyalarda uchraydigan kengayishdagi muammolar
- Kam xarajat bilan ko'plab insonlarga xizmat ko’rsatish
- Amazon, Facebook, Googledagi tizim dizaynidagi tajribalarim
- Tizim Dizaynini qanday tizimli o'rganish
haqida gapirdim.
Havola: youtu.be/g2g62uyBp88
Azim Pulat
Million inson uchun tizimlar qanday quriladi? Videoda: - Barcha kompaniyalarda uchraydigan kengayishdagi muammolar - Kam xarajat bilan ko'plab insonlarga xizmat ko’rsatish - Amazon, Facebook, Googledagi tizim dizaynidagi tajribalarim - Tizim Dizaynini qanday…
menimcha it va biznes ($$) sohasidagi hammaga foydali bo'ladi
Forwarded from Rustamjonov Davron
stat.uz
O‘zbekiston Respublikasi Milliy statistika qo‘mitasi
statistika, Milliy statistika qo‘mitasi, O‘zbekiston Respublikasi Milliy statistika qo‘mitasi, Uzstat, статистика, Национальный комитет по статистике, Национальный комитет Республики Узбекистан по статистике, НацКомСтат, Узстат, Миллий статистика қўмитаси…
Forwarded from Rustamjonov Davron
Rustamjonov Davron
https://stat.uz/uz/
real data bilan ishlayman deganlar uchun (api bilan ishlasa ham bo'ladi ).