Overview
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Learn how to model time series data and apply advanced analysis techniques using SQL.
Syllabus
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Introduction
- Learn time series data analysis with SQL
- What you should know
- Characteristics of time series data
- Examples of time series data
- Writing time series data
- Querying time series data
- Installing PostgreSQL
- Creating schema and tables
- Timing a query
- Evaluating query performance with EXPLAIN
- Time window queries and aggregates
- Sliding windows
- Tumbling windows
- Joining two time series
- Denormalizing time series data
- Example data set 1: Temperature by time and location
- Indexing data set 1: Time index only
- Indexing data set 1: Time and location index
- Creating a partitioned table
- Querying a partitioned table
- Example data set 2: CPU utilization and application type
- Indexing data set 2: Time and type Indexing
- Lead
- Lag
- Rank
- Percent rank
- Common Table Expressions and recursion
- Calculating aggregates over windows
- Previous day comparison
- Moving averages
- Weighted moving averages
- Forecasting with linear regression
- Exponential moving average
- Next steps
