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EncartaLabs

Vertica - Descriptive Analytics

( Duration: 2 Days )

This Vertica - Descriptive Analytics training course provides an overview of the standard SQL aggregate and analytic functions, as well as a comprehensive introduction to the Vertica-specific extensions to SQL.

By attending Vertica - Descriptive Analytics workshop, delegates will learn to:

  • Describe the difference between aggregate and analytic tasks
  • Group data using aggregate functions
  • Use the SQL OVER() clause tperform analytic functions
  • Use the Vertica-specific SQL extensions to:
    • Perform conditional analysis on data
    • Interpolate the missing values in a data set
    • Work with data in specified time slices
    • Find patterns in your data

  • A basic understanding of UNIX (finding and changing directories, listing directory contents, editing files, etc.)
  • Intermediate understanding of SQL (creating tables, loading data, selecting specific data from a table, common column data types, SQL join functionality, etc.)

The Vertica - Descriptive Analytics class is ideal for:

  • Data analysts and business analysts.

COURSE AGENDA

1

Introduction

  • Start a database
  • Load sample data into the database
2

Introduction to Data Analysis

  • Define analytic tasks
  • Compare aggregate tasks to analytic tasks
  • Describe real-world analytic tasks
3

Aggregating Data

  • Describe the functionality of the aggregate SQL functions
  • Group data in a table using:
    • GROUP BY
    • GROUP BY ROLLUP
    • GROUP BY CUBE
    • GROUP BY GROUPING SETS
4

The OVER() Clause, Part 1

  • Review the structure of the OVER() clause
  • Examine the behavior of the common analytic functions
  • Simplify queries using named windows
5

The OVER() Clause, Part 2

  • Define a moving window within an ordered partition using the frame_clause
    • Keyword: RANGE
    • Keyword: ROWS
6

Conditional Events

  • Evaluate whether an expression’s value has changed
    • Function: CONDITIONAL_CHANGE_EVENT()
  • Evaluate whether an expression is true
    • Function: CONDITIONAL_TRUE_EVENT()
7

Event Series Joins

  • Fill in time gaps in data using the INTERPOLATE keyword
8

Time Slices

  • Evaluate data over intervals of time within a partition
    • Function: TIME_SLICE()
9

Gap Filling and Interpolation

  • Identify gaps in time-sorted data
    • Clause: TIMESERIES()
  • Interpolate the values for a column for the gaps in the time-sorted data
    • Function: TS_FIRST_VALUE()
    • Function: TS_LAST_VALUE()
10

Pattern Matching

  • Use the MATCH() clause to identify behavior patterns in data
  • Recognize restriction with using the MATCH() clause

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 6,000 various courses on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting https://www.encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

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