Data Warehouse platforms
A Data Warehouse is a specialised database designed to support business intelligence activities, particularly in managing and analysing large volumes of data. Unlike typical transactional databases, a data warehouse is distinct in several key ways that make it ideal for extensive data analysis and reporting.
- A DWH integrates data from various systems across time, creating a unified view of an organisation's information. This consolidation allows for comprehensive analysis that spans multiple departments and historical data, providing insights that isolated systems cannot offer.
- Data warehouses are optimized to store vast amounts of data and process complex queries efficiently. This capability is crucial for generating reports, dashboards, and insights, setting data warehouses apart from traditional databases that focus on simpler, transactional operations.
- Data warehouses use specialised strategies and structures to ensure that stored data is homogeneous and easily manipulated for analysis. Techniques like data normalisation and indexing help organise data for quick and accurate retrieval, supporting the decision-making processes within an organisation.
The data warehousing process involves designing the system's architecture, developing and implementing it, and maintaining it over time. Designing involves planning the structure and components of the warehouse, while building involves data extraction, transformation, and loading (ETL). Maintaining ensures the system remains operational, updated, and aligned with the organisation's evolving needs.
On-premises data warehouses, traditionally housed within an organisation's own infrastructure, offer control over hardware and security but often come with high maintenance costs, limited scalability, and slower adaptability to changing data needs.
In contrast, modern cloud platforms provide flexible, scalable, and cost-efficient alternatives. Cloud DWH platforms allow organisations to quickly scale resources up or down based on demand, reduce the burden of infrastructure management, and leverage advanced analytics tools. However, they may introduce concerns about data security, compliance, and potential vendor lock-in, making the choice between on-premises and cloud solutions a strategic decision based on an organisation's specific needs and priorities.
Data Warehouse platforms software
- Snowflake Cloud Data Warehouse
- Oracle Autonomous Database
- Amazon Redshift
- Databricks Data Lakehouse
- Google BigQuery Cloud data analytics platform
- Microsoft Fabric Data Warehouse
- MySQL
- InfoBright
- SAP BW - Business Information Warehouse
- Sybase IQ
- Netezza Data Warehouse
- Microsoft SQL Server
- IBM InfoSphere Warehouse (DB2)
- Oracle Data Warehousing
- Teradata Enterprise Data Warehouse