Blog | Data Intelligence | February 12, 2023 | 3 min read

Everything You Need to Know About Data Warehouses

By Actian Corporation

#Almacén de datos #Bases de datos
Tecnología Futurista Almacén Minorista: Trabajador Haciendo Inventario Camina Cuando Proceso De Digitalización Analiza Mercancías, Cajas De Cartón, Productos Con Entrega Infografía En Logística, Centro De Distribución

By Actian Corporation

#Almacén de datos #Bases de datos

Summary

  • Un almacén de datos se crea para almacenar y organizar datos con fines de análisis, elaboración de informes y toma de decisiones.
  • Su arquitectura suele constar de tres capas: almacenamiento, transformación y acceso de interfaz para herramientas de generación de informes y de inteligencia empresarial.
  • Entre las principales ventajas se incluyen la centralización de datos, el análisis histórico, la integración de múltiples fuentes y un análisis más rápido.
  • Un almacén de datos es diferente de una base de datos: las bases de datos sirven para las operaciones cotidianas, mientras que los almacenes de datos sirven para el análisis y la estrategia a largo plazo.
  • Los almacenes de datos facilitan a los usuarios empresariales y a los analistas la exploración de los datos y el seguimiento del rendimiento.
In this post:

No one doubts anymore that data has become one of the most strategic assets for a company. Competitiveness, productivity, and adaptation to the market – data and analytics have become essential to meet the challenge of performance. Business teams base their thinking and strategies on reports, dashboards, and analytic tools. Their challenge: extract information from their data, monitor business performance, and support decision-making.

The essential mission of data warehouses is to feed these reports, dashboards, and tools. How? By efficiently storing data and providing relevant results to queries in just a few minutes. As an operational and strategic tool, the data warehouse is now essential.

Want to go further? In this article, learn everything you need to know about data warehouses.

The Architecture of a Data Warehouse Broken Down

The architecture of a data warehouse is most often built around three layers: the Bottom Tier, the Middle Tier, and the Top Tier.

The Bottom Tier

The bottom tier, which is also called the storage layer, is dedicated to the storage of data. It most often gathers relational databases or distributed file management systems (DFS) that are intended to store raw data. It also includes indexes to improve query performance.

The Middle Tier

The middle tier (or transformation layer) is used for the data cleansing, transformation, and consolidation phases. To do this, the middle layer relies on ETL (Extraction, Transformation, Loading) tools. It can thus extract data from different sources, clean it, and transform it before sending it to the data warehouse.

The Top Tier

The top layer, also known as the front-end layer, is the layer that provides access to information for end users. This layer includes reporting, visualization, and BI (business intelligence) tools to allow users to create reports, dashboards, and visualizations from the data in the data warehouse.

The Benefits of a Data Warehouse

Relying on a data warehouse is a major advantage for a company that wants to leverage its data assets. Among the main benefits associated with the data warehouse, we will note in particular:

  • The ability to centralize all available data in a single location in order to benefit from an optimized analytical capability, facilitating faster and more informed decision-making.
  • The ability to store and leverage historical data and older data to identify long-term trends.
  • Integration of data from different sources to provide a 360-degree view.
  • Performance optimization using data shaping techniques.
  • The opportunity to provide access to data to different users (and profiles) or to specific businesses within your organization.

Data Warehouse vs. Database: What are the Differences?

Too often, there is confusion between the data warehouse and the database. Yet, they are indeed two different components that fulfill specific missions and functions.

Por lo tanto, se puede considerar que una base de datos es un sistema de gestión de datos que permite almacenar, organizar y acceder a los datos.
Las bases de datos almacenan información en tiempo real para aplicaciones comunes, como los sistemas CRM o de gestión de la cadena de suministro.

Data warehouses, on the other hand, are systems dedicated to data analysis that store historical data from different sources. Data warehouses are used for long-term analysis, forecasting, and strategic decisions.

Also, to enable fine-grained data exploitation, data warehouses are often designed to be used by less data-savvy profiles (such as business managers and data analysts), while databases are more dryly accessible, and often reserved for more experienced users.

In conclusion, if databases are used for short-term data management, data warehouses are rather reserved for long-term data analysis and for more strategic trade-offs.