Tableu Prep Builder & Scaling Data Pipelines with Spark NLP

Introduction

• Spark NLP vs NLTK vs spaCy
• Overview of Spark NLP features and architecture

Getting Started

• Setup requirements
• Installing Spark NLP
• General concepts

Learning the Basics of Spark DataFrame

• Getting Started with Spark DataFrames
• Implementing Basic Operations with Spark
• Using Groupby and Aggregate Operations
• Working with Timestamps and Dates

Using Pre-trained Pipelines

• Importing required modules
• Default annotators
• Loading a pipeline model
• Transforming texts

Building NLP Pipelines

• Understanding the pipeline API
• Implementing NER models
• Choosing embeddings
• Using word, sentence, and universal embeddings

Classification and Inference

• Document classification use cases
• Sentiment analysis models
• Training a document classifier
• Using other machine learning frameworks
• Managing NLP models
• Optimizing models for low-latency inference

Introduction

• Tableau Prep Builder as an ETL (Extract, Transform and Load) tool

Setting up Tableau Prep Builder

• Activating and Register Tableau Prep Builder

Overview of Tableau Prep Builder Features and Architecture

• Tableau Prep Builder and its relation to Tableau Desktop, Tableau Server and Tableau Prep Conductor

Connecting to Data Source

• Reading from a database

Shaping Data

• Creating a Join
• Creating a Union

Pivoting Data

• Changing columns to rows

Cleaning Data

• What is dirty data?
• Changing the data type
• Filtering data
• Aggregating data
• Updating multiple values at once

Running a Flow

• Building a flow
• Refreshing a flow
• Running a flow from the command line

Outputting Data to Tableau Desktop

• Analyzing data

Publishing Data

• Packaging a Prep Builder data flow into an extract
• Publishing a flow with Prep Conductor

Prerequisites

Jobs you can get
with a Tableu Prep Builder & Scaling Data Pipelines with Spark NLP

• Data Analyst
• Data Engineer
• Database Architect
• Data Application Developer
• Data Warehouse Lead