Aexis ondersteunt EuroParcs met forecasting en planning


Volgens Roel Klaver, CFO bij EuroParcs Group, viel de keuze op Aexis vanwege de ruime ervaring in het adviseren, realiseren en beheren van oplossingen voor performance management. “Aexis zal het volledige implementatietraject op zich nemen en daarnaast lokale ondersteuning bieden op het gebied van beheer. Wij zijn van mening dat een goede oplossing voor rapportage en forecasting cruciaal is omdat We grote nationale en internationale groeiambities hebben.”

Met IBM Planning Analytics kan EuroParcs Group de financiële en operationele rapportageprocessen centraal beheren. “Bovendien zorgt de implementatie voor snellere maandrapportages en jaarafsluitingen”, weet Klaver. “Hierdoor hebben we goed inzicht in de financiële prestaties van de groep met de labels Droomparken en EuroParcs.”

EuroParcs Group heeft grote ambities en groeit snel, vervolgt Klaver. “Hierbij hoort een robuust IT-landschap dat deze groei kan faciliteren. Naast een nieuw ERP-systeem hebben we een oplossing nodig die ons in staat stelt om onze management stuur informatie te optimaliseren. Acquisitie van nieuwe parken betekent dat we vaak te maken hebben met legacy systemen, waarvoor een snelle integratie noodzakelijk is. Dankzij Aexis en IBM Planning Analytics kunnen we zowel per park als op geconsolideerd niveau rapportages, analyses en prognoses uitvoeren zoals wij willen.”

Christiaan van ’t Klaphek, CPM Development Lead bij Aexis, voegt daaraan toe: “Wij zijn er trots op dat onze oplossingen bijdragen om de doelstellingen van EuroParcs Groep te realiseren. Na de eerste fase zullen we EuroParcs Group in 2021 blijven ondersteunen, zodat de oplossing perfect blijft aansluiten op de ontwikkelingen binnen de organisatie. Denk hierbij aan het integreren van bijkomende bronsystemen en het verder professionaliseren van het forecastingproces met bijvoorbeeld een functionaliteit voor Artificial Intelligence.”


The Aexis CPM solutions – Scored by BARC

One of the most important elements of management control is planning. Aligning your operational business with strategic corporate objectives is key for any existing future-proof business. For your planning processes to be successful, they require comprehensive analytics and Business Intelligence (BI) functionality.

In addition to this, we are happy to share our experience with CPM-solutions and discuss your specific needs to find the best fit for your organization. We offer our advisory services to define a CPM roadmap and realize your goals. Please feel free to contact Aexis and share your thoughts.


Blog - meet the different types of OLAP

Meet the different types of OLAP

You may be overwhelmed with the various types and acronyms of OLAP that you find when looking into the OLAP technology. Don’t know what OLAP is exactly? Then we recommend you to read our previous blog The basics of OLAP data modeling.

In general, we speak of three main categories: ROLAP, MOLAP, and HOLAP. Each of these categories differentiates itself because of the technique they use for the arrangement and the storage of data. Let’s have a deeper look at the three main categories: 


MOLAP, or Multidimensional OLAP, is considered to be a standard form of OLAP. MOLAP utilizes a multidimensional database for storage and analyzing information. This is the fastest option for data retrieval but also requires the most storage space. MOLAP is optimized for fast query performance and retrieval of summarized data. But there are also limitations when using MOLAP technology. First of all, it’s not scalable and can only handle a limited amount of data. This is because the system requires pre-computation and predefined calculations before being run. 


ROLAP stands for Relational OLAP. This utilizes a relational database management system to keep and control your data. ROLAP stores all your data, including aggregations, in your relational database. This type of storage is excellent for organizations that need larger data warehousing. The advantages of using ROLAP technology are better scalability, enabling it to handle huge amounts of data and the ability to efficiently manage both numeric and textual data. ROLAP uses a SQL reporting tool to query data directly from the data warehouse. This requires a huge database and usually brings complex queries. 


Hybrid OLAP combines the best of both worlds; MOLAP and ROLAP. This way a huge amount of data can be stored in relational tables, and aggregations can be stored in pre-calculated cubes. By combining MOLAP and ROLAP, better scalability, quick data processing and flexibility in accessing your data sources can be accomplished. 

Aexis has been working with OLAP-technology for decades. Take a look at our expertise in corporate performance management (CPM) and the technology of the leading vendors IBMBoard, and Jedox we use to create value for our customers. 

Do you have questions or need more information? Our expert is happy to help you with this! Contact Christian Pauwels or drop us a line for more information. 

The basics of OLAP data modeling

The basics of OLAP data modeling are explained in this blog post.
In this data driven world, an enormous amount of data is collected and stored on a daily basis. But why is it important to collect and store these huge amounts of data? Having piles of raw data can help your organization to make better analysis. The problem is, data in its original form doesn’t always make much sense. By structuring your collected raw data, you will be able to
make more informed decisions. The process of structuring your raw data is called data modeling. This is where OLAP comes in.

Back to the basics of OLAP

OLAP is an acronym for Online Analytical Processing. Before we start explaining the basics of OLAP, you might wonder why OLAP can be handy for your organization. Well, OLAP is a multi-dimensional database   technology that permit to perform quick  data analysis on many data records. This analysis will provide relevant information aimed at better decisions taking , storytelling and planning. In summary OLAP is a software technology that allows organizations to perform multidimensional analysis of collected data. It provides the capability for complex calculations, trend analysis and data modeling with one goal: understanding your business better.

When learning about OLAP, there is no getting away from the terms dimensions, cubes, measures and hierarchies. Here are some definitions that will make it easier to understand their relevance.

1. Cubes

OLAP tools use multidimensional database structures, called cubes. An OLAP Cube, or a data cube, is a multidimensional data set that allows fast analysis of data, according to the multiple dimensions you set up. You can compare a cube with a multidimensional spreadsheet: you can collect data from users and store that data in a transparent way and calculate when needed. In order to form a cube you need dimensions.

2.  Dimensions

Dimensions are lists of related items used to organize your data in similar categories, such as products, time and/or regions. Dimensions are the basis for the data structure of an OLAP data cube. For example, the months and quarters may make up your Year dimension. You can compare dimensions with the business parameters that you normally see in the rows and columns of a report. A model can consist in multiple dimensions : example :

  • organization structure of the company
  • product structure
  • version (for simulations and final)
  • scenario (actual , budget , forecast , best case , worst case , …)
  • measure (Account list , FTE , Headcount , SKU , … )
  • currencies
  • exchange rates
  • year – period

In practice dimension need to be limited to +/- 12 in order to remain workable for end users and calculation engine. Depending on technology used the dimension can be higher without impact on performance.

3. Measures

Each cube must have at least one measure. But in reality, we see that cubes often contain multiple measures. An OLAP measure is a numeric value by which the dimensions are detailed or aggregated. It gives you the information about quantities you’re interested in. Do you have difficulties with defining you OLAP measures? Ask yourself the question ‘how much…?’ and your answer will be your OLAP measure. Measures can be financial or nonfinancial example: COA’s , KPI’s , FTE ‘s, Volumes , … .

4. Hierarchies

Hierarchies are the subcategories of your dimensions. They have multiple levels and allow you to drill down or drill up your data. What is drilling, you may ask? Drilling allows you to analyze your data at different levels of granularity. (example : total volume , volume by product group, volume by packaging by product group, volume by KSU by packaging by product group ).


OLAP is a common technology behind many Business Intelligence and CPM applications and is still most relevant today. Using OLAP can help your organization with your analyses, forecasting and planning. In short, it should contribute to better decision-making and eventually lead to more profit.

Do you have question or need more information? Our expert is happy to help you with this! Contact Christiaan Van t’ klaphek or Stijn Hermans for more information.

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