Data warehousing guide

  • What are the four 4 stages of data warehouse?

    There are three main data warehouse architecture types: single-tier, two-tier and three-tier data warehouses.
    Every data warehouse has the same vital components within its architecture, namely: ETL tools, databases, metadata, bus & data marts and access tools..

  • What is the guiding principle of designing a data warehouse?

    General Guiding Principles
    Only data that meets the Business Requirements' needs should be included in the Enterprise Data Warehouse environment.
    This consists of the evaluation of whether all 'Business Relevant' data should be gathered.
    The System of Record for operational data sources can change over time..

  • Fundamentals of Data Warehouses.
    Three types of common data transformations within adata warehouse are: Integration – It acts as an endpoint for data from various sources such as APIs and databases.
    Cleaning – Data from various sources then gets cleaned prior to consolidation to ensure data reliability.Feb 15, 2023
Feb 15, 2023Data warehouses centralize all data within a company's data ecosystem and enable downstream consumers to drive analytical insights with it.
Feb 15, 2023Key ConceptsHosted & self-managed on the cloud. There is no need to provision hardware or software.Performance at scale. Data warehouses 

How can a data warehouse be scalable?

Solutions like Amazon Redshift, Google BigQuery and Panoply manage partitioning and scalability of the data warehouse in a transparent manner

So it’s possible to setup a petabyte-scale Enterprise Data Warehouse, holding all organizational data, without the cost and complexity of traditional data warehouse project

What is a data warehouse?

A data warehouse is a type of database that’s designed for reporting and analysis of a company’s data

It collects data from one or many sources, restructures it in a specific way, and allows business users to analyse and visualise the data

Why Do We Need a Data Warehouse?

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