Course Outline

Introduction

  • Overview of kdb+ and its use cases
  • Understanding column-oriented databases vs. row-oriented databases

Setting Up kdb+ Environment

  • Installation and configuration
  • Basic commands and data structures in q

Vectors and Lists in q

  • Working with vector-based operations
  • Understanding lists and dictionaries

Tables in kdb+

  • Creating and manipulating tables
  • Loading and importing data sets

Scripting in q

  • Writing simple to complex scripts
  • Defining functions and understanding their applications

Advanced q Features

  • Working with conditional operations and control flow
  • Error handling and debugging

Time Series Concepts

  • Introduction to time series data
  • Working with timestamps and time zones

Querying Time Series Data

  • Selecting and analyzing time-based records
  • Applying moving averages and other statistical functions

High-Frequency Trading Analysis

  • Using kdb+ for financial market data
  • Simulating real-time data processing

Extending kdb+ to Other Use Cases

  • Telecommunications data analysis
  • Sensor data and IoT monitoring
  • Network and machine usage monitoring

Summary and Next Steps

Requirements

  • An understanding of statistics
  • Experience in the financial industry is helpful
  • An understanding of relational databases
  • Some experience with programming is helpful, but not required

Audience

  • Developers
  • Database engineers
  • Data scientists
  • Data analysts
 21 Hours

Delivery Options

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