NodeOps: A Data Odyssey
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NodeOps: A Data Odyssey

How to build a Data Engineering and Business Intelligence Stack using Node.js and Npm modules

About the Book

How to build a Data Engineering and Business Intelligence Stack using Node.js and Npm modules. It covers data sources like databases, media sources. It also includes examples on building a ETL as well as building Data Lakes and Data Warehouses. Finally, it includes examples for building Dashboards and Reports.

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  • Categories

    • Databases
    • Azure DocumentDB
    • MongoDB
    • PostgreSQL
    • SQL Server
    • Amazon Web Services
    • Microsoft Azure
    • Google Cloud Platform
    • JavaScript
    • Web Development
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About the Author

Kevin Languedoc
Kevin Languedoc

Kevin Languedoc is a professional software developer, architect with over 20 years experience in SDLC, DevOps, Data Engineering, Web Development.

Table of Contents

  • Data Sources
  • Solution 1 SQL Server using the Tedious driver:
  • Solution 2 using msnodesqlv8 driver and the mssql package:
  • Solution 3 using mssql alone:
  • Node.js connect to oracle db
  • Solution 1: Using the node-oracledb module
  • Node.js connect to postgre-sql
  • Solution 1: pg
  • Solution 2: insert, update and delete with pg
  • Solution 3: db-migrate-pg
  • Node.js to mysql connection
  • Solution 1 – mysql
  • Solution 2 – mysql2
  • Solution 3 - sequelize:
  • Node.js Connect and Query Snowflake
  • Solution 1 – using the snowflake-sdk:
  • Solution 2 - use the sequelize module
  • Node.js connect to Apache Cassandra
  • Solution 1 – using the Cassandra-driver
  • Solution 3 – using the Cassandra-cql module:
  • Solution 4 – using the Helenus module:
  • Node.js connect to Apache Hive
  • Solution 1 – node-hive module:
  • Solution 2 – using node-jdbc
  • Solution 3 – using the jshs2 module:
  • Solution 4 – using the hive-driver
  • Solution 5 – using the node-thrift module
  • Nodejs connection and Querying with Redis
  • Solution 1 – using node-redis
  • Nodejs Connect to MongoDb
  • Solution 1- using mongodb
  • Solution 2- using mongodb, express, mongoose:
  • Working with AWS Redshift in node.js
  • Solution 1- using pg:
  • Nodejs connection and Querying with Redis
  • Solution 1- using redis:
  • Working with Databricks from Node.js
  • Solution 1 - Using the @databricks/sql module:
  • Solution 2 - Using the node-hive module:
  • Solution 3-Using the spark-node module:
  • Solution 4-Use the Databricks REST API:
  • Connecting to Azure Data Lake using Node.js
  • Soluton1 – using @azure/storage-file-datalake
  • Working with Apache Spark from Node.js
  • Solution 1-using node-spark
  • Working with Social Media Sources
  • Node.js Data Extraction from Twitter (X) example code
  • Solution 1-Using the twit module
  • Solution 2- using the twitter-lite module:
  • Solution 3-using the node-twitter module:
  • Node.js Data Extraction from Facebook
  • Solution 1 – use the Graph API
  • Solution 2-Use the Facebook web scraper
  • Solution 3-using Axios:
  • Connect and Query LinkedIN
  • Solution 1-using Passport module
  • Data Extraction and Loading using an ETL
  • Develop ETL Flows using Node.js
  • Solution 1- using Nextract:
  • Solution 2- using Datapumps:
  • Solution 3 Empujar:
  • Solution 4 Extraload:
  • Solution 5- using ETL
  • Solution 6- using Proc-that
  • Solution 7 – using PM2
  • Data Lakehouse
  • Solution 1- Azure Data Lake
  • Solution 2- Amazon S3 and Lake Form
  • Solution 3. Google Cloud Platform and BigLake
  • Solution 4. Databricks Delta Lake
  • Solution 5. Snowflake
  • Solution 6. Apache Iceberg Lakehouse Platform
  • Building a Data Warehouse
  • Why Json database
  • Building a Data Warehouse with a NoSQL (Json) database
  • Solution 1 – building a data warehouse with mongodb
  • Solution 2 – building a data warehouse with Redis
  • Solution 3 – building a data warehouse with CouchDB
  • Solution 4 – Building a data warehouse with AWS DocumentDB
  • Solution 5 – Building a data warehouse with Azure CosmosDB
  • Solution 6 – GCP BigQuery
  • Solution 7 – GCP BigTable
  • Solution 8 – GCP Datastore
  • Reporting and Dashboards
  • Reporting
  • Solution 1 – Nuxt DataTable
  • Solution 2 – React Table
  • Solution 3 – jQuery Datatable
  • Solution 4 – jsReports
  • Solution 5 – Carbone IO
  • Solution 6 – React Table
  • Solution 7 – Angular table
  • Dashboards
  • Solution 1 – D3js
  • Solution 2 – React-Chart-2.js
  • Solution 3- Apache ECharts
  • Solution 4 – Google Chart.js
  • Solution 5 - ApexCharts
  • Building a dashboard app with React
  • Conclusion
  • References
  • Index
  • Appendix
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