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Snow Sql Roadmap

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Day 1: Retrieve data from table

Day 2: Retrieve columns data from table

Day 3: WHERE clause

Day 4: SORT results

Day 5: LIMIT results

Day 6: INNER JOIN between two tables

Day 7: Average on numeric column

Day 8: Count rows

Day 9: Group rows

Day 10: DISTINCT keyword

Day 11: Sum of a numeric column

Day 12: Filter data

Day 13: BETWEEN operator

Day 14: Find minimum and maximum values

Day 15: Count unique values in a column

Day 16: LEFT JOIN operation

Day 17: Data from multiple tables

Day 18: IN operator

Day 19: Average and total sum in one query

Day 20: Retrieve highest values in a column

Day 21: LIKE operator

Day 22: LIMIT clause

Day 23: NULL values in a column

Day 24: OUTER JOIN operation

Day 25: NULL operators

Day 26: Median value

Day 27: INNER JOIN

Day 28: ORDER BY with multiple columns

Day 29: Standard deviation of a numeric column

Day 30: Date column operations

Day 31: EXISTS operator

Day 32: NOT LIKE operator

Day 33: Percentage using window functions

Day 34: ROW_NUMBER()

Day 35: UNION and UNION ALL set operators

Day 36: COALESCE function

Day 37: Second highest value in a column

Day 38: RANK() window function

Day 39: Cumulative sum using window functions

Day 40: Difference between consecutive rows

Day 41: Date range

Day 42: Complex filtering

Day 43: LEAD() and LAG() window functions

Day 44: 75th percentile of a numeric column

Day 45: Weighted average of a numeric column

Day 46: COALESCE function

Day 47: Top N records

Day 48: NTILE() window function

Day 49: Average with exclusion of outliers

Day 50: Self-join

Day 51: Median absolute deviation (MAD)

Day 52: FIRST_VALUE and LAST_VALUE window functions

Day 53: ROWS BETWEEN clause

Day 54: Geometric mean of a numeric column

Day 55: Date range

Day 56: Interquartile range (IQR)

Day 57: NTH_VALUE window function

Day 58: ARRAY functions

Day 59: Gini coefficient

Day 60: Top N distinct

Day 61: Moving average

Day 62: Advanced querying

Day 63: PERCENTILE_CONT and PERCENTILE_DISC

Day 64: Identify duplicates

Day 65: CAGR (Compound Annual Growth Rate)

Day 66: HISTOGRAM window function

Day 67: JSON functions

Day 68: Fuzzy text matching

Day 69: Coefficient of variation (CV)

Day 70: Advanced sorting

Day 71: Full-text search

Day 72: Create a query to handle data imputation and missing value estimation

Day 73: ARRAY_AGG and OBJECT_AGG functions

Day 74: Temporal data analysis

Day 75: Probability density function (PDF)

Day 76: Integrate machine learning predictions

Day 77: Location-based queries

Day 78: Network analysis

Day 79: Text similarity

Day 80: Time-series analysis

Day 81: Advanced statistical and mathematical functions

Day 82: Sentiment analysis

Day 83: Calculate and visualize data distribution using histogram charts

Day 84: External data sources and APIs

Day 85: Time-based data comparisons

Day 86: Custom transformations to data

Day 87: Advanced statistics

Day 88: User cohorts over time

Day 89: Anomaly detection in time-series

Day 90: Analyze trends and patterns in time-series data

Day 91: Advanced data aggregation and summarization

Day 92: Combines multiple data sources into one view

Day 93: Advanced financial metrics

Day 94: Advanced data visualization

Day 95: Natural language processing capabilities

Day 96: Advanced portfolio analysis and optimization

Day 97: Integration with external machine learning models

Day 98: Advanced marketing metrics

Day 99: Data forecasting and predictive analytics

Day 100: Advanced analytical techniques

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