Data Warehousing

Do you know where your data comes from? And whether your reports are based on one version of the truth? Or do you find that you have to collect, cleanse and combine data over and over again before you have a good picture? If you are in doubt, it is time to get acquainted with data warehousing.

Organisations collect huge amounts of data every day: from CRM systems, accounting, web applications, Excel files, and more. But as long as that valuable data remains scattered across separate islands, gaining reliable insights is an almost impossible task. It takes hands-on time, leads to frustrating errors and makes data-driven work unnecessarily complex. The result? Missed opportunities and decisions based on incomplete information.

Fortunately, there is a solution that transforms this chaos into clarity: the data warehouse. By bringing data from different sources together in one central, organised place, you not only create overview, structure and consistency; you lay the ultimate foundation for reliable dashboards, smart analyses and decisions you can really rely on. Read on and discover how a data warehouse takes your organisation to the next level!

What is a data warehouse?

A data warehouse is a central environment in which data from various sources is brought together, structured and stored with the aim of making this data available for analysis, reporting and data-driven decision-making. Unlike operational systems, which are set up to support day-to-day processes, a data warehouse is optimised for analysing large amounts of historical data over long periods of time.

A data warehouse helps organisations gain reliable insights, identify trends and generate management information. Because all relevant data comes together in one place, it creates a uniform and consistent basis for dashboards, reports and advanced analyses for reporting tools such as PowerBI, Qlik or Tableau, among others.

The first step in the data warehouse process is ingestion , or extraction of data from raw source systems, think ERP or CRM systems, financial packages, HR software or web applications. These data are often not standardised and contain inconsistencies or missing values. Therefore, data transformation is a crucial second step. This involves cleaning up the data, enriching it and converting it into a uniform structure suitable for analysis. In this blog, we elaborate on the main points of interest and best practices around the topic of transformation.

Solve more complex questions with data warehousing

Implementing a data warehouse brings numerous benefits. One of the most important is that you can easily answer complex questions. Imagine you want to know which types of customers generate the most turnover and how many contact moments are needed on average to issue quotes for this type. To make this insightful, you combine data from the ERP system, such as turnover and invoicing, with data from the CRM system, such as contact moments and quotation requests.

Another example is obtaining an overview of the financial situation of the entire business group. This requires bringing together financial data from multiple administrations into a single overview. Thanks to the data warehouse, it is possible to create a complete picture of the financial state of affairs on a daily basis, across all entities, despite them working in different source systems.

A data warehouse also allows you to answer questions, such as which departments are structurally facing a high workload or understaffing. By combining data from HR and project management systems, you discover patterns that help you make timely adjustments. The impact of seasonal influences on stock and sales also becomes clear by analysing historical sales and stock data, allowing you to better align stock management and purchasing to expected demand.

The 5 advantages of a data warehouse

A data warehouse offers more benefits than just answering complex questions; it increases the efficiency, reliability and security of data.

1. Single source of truth
   A data warehouse ensures that everyone in the organisation works with the same, up-to-date and validated data. This prevents misunderstandings, double interpretations and inconsistencies in reports and analyses, significantly speeding up decision-making.
2. Access to historical data and trends
   Because a data warehouse stores data for long periods, trends over longer periods can be analysed. This is essential for strategic decisions, forecasting and responding to changes in customer behaviour or market dynamics.
3. Better data security and access management
   In a data warehouse, it is possible to precisely define who gets access to which information. This allows sensitive data to be shielded from unauthorised access, while employees only see data relevant to their role.
4. Less pressure on operational systems
   Analyses, reports and data requests are processed in the data warehouse instead of primary systems. This reduces the load on operational applications, prevents delays and increases the stability of core systems.
5. Faster and more efficient reporting
   Thanks to the powerful infrastructure of a data warehouse, data transformations can be performed in advance, making dashboards and reports available much faster. This ensures that decision-makers can always rely on up-to-date and reliable information.

The basics of data warehousing

When setting up a data warehouse, you first think about some basic principles, the basic principles of data warehousing. The main principles are: symmetry, mandatory usage and mandatory delivery, granularity, data quality, privacy by design, different flavours, synchronisation, streaming first, non-volatile data warehouse BI, maintainability and extensibility, cloud-first.

To make a data warehouse a success, we can sum up the above into some basic principles:

1. Integration of data sources
   One of the main principles of data warehousing is that it brings together data from different systems such as ERP, CRM, HRM, finance and logistics. As each system has its own structure and definitions, the data is first standardised. This creates a single coherent whole suitable for analysis.
2. Cleaning and quality control
   Before data is loaded into the warehouse, it is cleaned up. Errors, duplicate values and inconsistencies are corrected. This ensures that reports are based on reliable and accurate data.
3. Historical storage
   A data warehouse stores data over longer periods. While operational systems often only show the current state of affairs, a data warehouse allows you to look back in time. This makes it possible to analyse trends, recognise seasonal influences or compare the performance of departments or products over the years.
4. Separation between storage and operations
   The data warehouse is separate from the operational systems. This means that analyses and reports do not affect the speed or operation of the systems used on a daily basis. This prevents reports from slowing down the regular work process.
5. One version of the truth (Single Source of Truth)
   By using central definitions for e.g. KPIs, calculations and data selections, the data warehouse ensures that everyone in the organisation works with the same figures. This prevents confusion and discussion about which figures are ‘right’.
6. Decision support
   Ultimately, data warehousing is about improving decision-making. By making data available in a structured and fast manner, organisations can better anticipate developments, make informed choices and steer strategically.

At Blenddata, we help organisations unlock and model their data sources according to the above principles. In this way, we create a reliable and central data platform that can be used immediately for reports, dashboards and other data-driven applications. Do you recognise the challenges and do you also want to put an end to fragmented data and unreliable insights? Then contact us today to discuss the possibilities!