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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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