Data Mart

What it is, Why it Matters, Tools, and Best Practices.

What is Data Mart?

A data mart is a structured data repository purpose-built to support the analytical needs of a particular line of business, department, or geographic region within an enterprise. Typically a data mart is created as a subset of an enterprise data warehouse, in which data replicated from various operational databases across the enterprise is consolidated, cleansed, and transformed into formats optimized for analytic queries. Key challenges in enterprise data warehousing and data mart creation include designing and building the data warehouse and the data mart, loading source data into the data warehouse and the data mart, keeping the data in the warehouse and the data mart in sync with the continuously changing source database systems, and delivering in an agile way to keep pace with constantly changing business and analytical requirements.

Qlik relieves these data mart pain points with technologies that automate data mart design, build, management, and operation from end-to-end, while putting data architects and analysts in the driver's seat and minimizing reliance on resource-constrained ETL developers and database administrators.

Data Warehouse Automation

The Data Mart Foundation: Creating and Populating a Data Warehouse

Using Qlik Replicate and Qlik Compose, businesses dramatically reduce the complexity and costs of data warehouse and data mart design, creation, operation, and change management.

Qlik Replicate is a unified solution to ingest data into any major data warehouse platform (such as Teradata, Exadata, Netezza, or Sybase ASE) or cloud-based data warehouse service (such as Amazon Redshift or Azure SQL Data Warehouse) from nearly any type of database or legacy mainframe system. Qlik Replicate supports secure, high-performance bulk data loading, as well as log-based change data capture (CDC) for real-time data ingestion. Data architects and data scientists can easily configure and execute source-to-warehouse data flows through a user-friendly GUI, without need for coding or expertise in the source or destination programming interfaces.

Working seamlessly together with Qlik Replicate, Qlik Compose simplifies and expedites data warehouse and data mart design and creation. Qlik approach to DWH automation can be data-driven or model-driven, enabling teams to create their own data warehouse model by profiling source systems and using an intuitive design GUI, or importing existing data models. Qlik Compose flexibility enables teams to deploy proven design patterns including Inmon, Kimball, and Data Vault.

Once designed, Qlik Compose automatically generates the ETL code appropriate to the combination of source data structures, warehouse design model, and warehouse platform (such as AWS Redshift ETL code, for example), and automatically builds the data mart and loads source data. With a few clicks, a Qlik Compose user can create the data warehouse structures and execute the ETL code to transform data from the landing area and load it into the warehouse.

Data Mart Creation Made Easy

With your data warehouse created and populated, you can use Qlik Compose to easily create and deploy data marts to support the analytic needs of particular lines of business, departments, or geographic regions. An intuitive star schema wizard guides you through the process of selecting and organizing facts and dimensions.

Based on your configured star schema, Qlik Compose automatically generates the needed ETL commands to transform and load data into the data mart. Data marts created with Qlik Compose seamlessly support major BI visualization tools such as Microsoft PowerPivot, Tableau, and Qlik.

Popular data mart resources


Data Warehouse Automation in Azure for Dummies


Qlik Compose – Agile Data Warehousing


Streaming Change Data Capture

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