A Journey to Data Architect ..

 Looker Architecture Looker Features: Highly Scalable Better Performance - as it uses Virtual Data Modelling Layer Better Data Governance Develop using Agile Methodology Fexible Self Service - Text Based YAML  Zero Redundant Data Storage Less Hardware procurement Enterprise wide Metric Accuracy Advantages of using Virtual Data Modelling Layer Less Hardware Zero Redundant Data Storage High Performance Data Querying Real time Analytics AI and ML  Flexible Data Pipelines Looker Helps in : Version Controlled ,unified analytical layer Single source of truth for KPIs and Metrics Content Security Scalable data access to Non Tech users Multi/Hybrid cloud support for data sources outside of google cloud What Looker lack: Selection of Columns and adding Join Columns to auto build queries for non technical users. Need to have knowledge in  LOOKML text based creation for building dashboards it Doesn't support Radio buttons and Selection on dashboard. Uploading Excel files and bu...

  What Is LookML? LookML is a language for describing dimensions, aggregates, calculations, and data relationships in a SQL database. Looker uses a model written in LookML to construct SQL queries against a particular database. LookML Projects A LookML Project is a collection of model, view, and dashboard files that are typically version controlled together via a Git repository. The model files contain information about which tables to use, and how they should be joined together. The view files contain information about how to calculate information about each table (or across multiple tables if the joins permit them). LookML separates structure from content, so the query structure (how tables are joined) is independent of the query content (the columns to access, derived fields, aggregate functions to compute, and filtering expressions to apply). LookML separates content of queries from structure of queries SQL Queries Generated by Looker For data analysts, LookML fosters DRY style...