Cloud Data Integration : 2020 : February Skip navigation

Choosing the Right Path to Cloud Data Warehousing

Thursday, February 27, 2020 | 10:00am PST

Data is too important to your business to risk making the wrong decision about implementing cloud data warehousing.
Join our live webinar “Cloud Data Warehouse Drivers: Migrate, Modernize, or Both?” as we explore:

  • Key business and technical drivers for cloud migration
  • The cloud data warehouse ecosystem
  • Challenges with data modernization
  • Best practices for data migration

Featured speakers:

  • Sam Tawfik, Product Marketing Manager, Informatica
  • Andrew Comstock, Senior Director, Product Management


Click here to register.

This article showcases how Informatica Cloud Data Integration supports implementation of 'Data Vault' models.


What is Data Vault Modeling?


Data Vault is a modeling method that is used to design Data Warehouses. DV mainly consists for three types of tables:

  • Hubs – Hub tables contain unique list of Business Keys
  • Links – Links include the relationships between two or more Business Keys
  • Satellites – Satellite tables include descriptive data that changes over time


Is Data Vault same as Dimensional Modeling?


No, Data Vault and Dimensional Modeling (Star and Snowflake Schema) are different modeling methods used to design Data Warehouses.


What is Data Vault 2.0 or DV 2.0?


Data Vault 2.0 is the next iteration of Data Vault modeling with enhancements made in the modeling technique such as ‘Use of Hash Keys’ to support parallel loads.


Why chose Data Vault over Dimensional Modeling?


Data Vaults are known for flexibility and scalability. The way in which DV is designed provides for long-term historical data. It is known to be very flexible to add new sources to a DV model. Data Vaults are also known to be high performant and more usable by business users since it is modeled after the business domain.


Informatica Cloud Data Integration and Data Vault model


Informatica Intelligent Cloud Services makes it easy to develop Data Warehouses using the Data Vault model for the following reasons-


  • Rich Transformation Support – Informatica Cloud Data Integration provides a rich set of transformation that supports variety of integration use cases including Data Vault implementation. Pre-built functions such as MD5 makes it very straightforward to perform hashing which is center to DV implementation


  • Comprehensive Connectivity – Building your Data Warehouse on-premise or in the cloud, you are able to easily move data over leveraging the 100’s of out-of-the-box connectors we offer


  • Reusability – Parameterization support in Informatica Cloud Data Integration allows reuse of data flow for multiple table loads.


Sample DV Implementation in IICS


Below is a simple 'Data Vault' implementation built purely to illustrate how DV can be easily implemented using Informatica Cloud Data Integration. Example below involves customer and location information.




Step 1 – Loading Hub tables


Customer Hub



Location Hub



Step 2 – Loading Customer-Location Link table



Step 3 – Loading Satellite tables


Customer Satellite Table



Location Satellite Table



Optional - Orchestration of the loads in a Taskflow



Preview of data loaded by the mappings


select * from [dbo].[DV_Cust_Hub]




select * from [dbo].[DV_Cust_Loc_Link]




In Summary, IICS continues to be the leader in the iPaaS market and as demonstrated in this article, is feature rich that makes loading your Data Vault very easy. To try out Informatica Cloud Integration for your DW implementation, you can do a free 30 day trial from here.

This document summarizes the key capabilities that were introduced in the Taskflows module of Cloud Data Integration in 2019.

Filter Blog

By date: By tag: