What is a Data Warehouse?

A well-prepared and flexible Data Warehouse is of great commercial value and makes it easy to meet the requirements for analysis in a successively developing business.

The importance of the right Data Warehouse

Establishment of a dynamic Business Intelligence solution requires a solid foundation, a Data Warehouse that is both dynamic and scalable.

A Data Warehouse represents the motor processing your company data, allowing you to make the relevant analyses.

Many companies find the number of data sources, and thus the amount of data, to be rapidly increasing. It might be difficult to derive meaning out of these data unless they are structured and processed before analysing or reporting.

To avoid designing and structuring data from the most commonly used sources from scratch each time, InfoSuite has built a Data Warehouse and a data model ready for implementation. This Data Warehouse ensures that all daily transactions and changes in your company are gliding smoothly through the system.

Here, we present some of the details of our Data Warehouse to give you an indication of the advantages of implementing a well prepared and flexible data model.

Proper data integration

InfoSuite consolidates, combines, and analyses data from all types of data sources in your company. It provides in-depth opportunities for exploring your data and one single basis for decision-making.

Based on our thorough knowledge of data, we have developed plug-and-play solutions for some of the most common IT systems in the market, such as Dynamics NAV and Dynamics AX.

Standardisation of dimensions and transaction types

It is crucial to compare data across the business.

However, comparing products, suppliers, and customers from different data sources may be difficult.

The InfoSuite Data Warehouse solves this issue by using consolidated dimensions to provide for the complete overview of sales from a given item group or sales to a customer existing in both systems but with different customer numbers.

Likewise, the individual systems operate with different transaction types, such as purchase, return of stock transactions, crediting etc. Consequently, the InfoSuite data model is geared for standardising these different transaction types.

Another important factor is the handling of data and dimensions in different languages. All users should be able to understand the reporting irrespective of the language being Danish, German, Spanish, English etc.

Period terms are also standardised across countries, time zones etc. in the data model. Analysing data across countries thus becomes much easier.

Standardising basic tables

A shared foreign exchange rate table guarantees the same basis for conversion, for example reporting currency at group level.

Dimension texts are placed in available languages in one joint table, simplifying management of different languages.

For financial consolidation, tables with rules for consolidation must be defined. This includes internal numbers, accounts, and dimensions etc.

All amount fields exist in transactional currency, company currency, and common reporting currency.

Conversion between company and reporting currency is always made based on the same foreign currency exchange table.

Quantity is counted in units and conversion between units is completely automatic.

Consolidation and foreign currency management

Consolidating accounts may be a complex task including several manual processes.

With the right solution, consolidation can be highly automated across different financial systems.

Consolidation in InfoSuite

Structure prepared for management of Big Data

All data in the individual Data Warehouse are placed in predefined master data tables or in transaction tables.

Through keys in the transaction table, the master data hold additional information and dimensions about account, customer, item, or supplier. All transactions document the process between the different parts, areas, functions in the entire solution.

The prepared Data Warehouse and the structure included can hold many types of Big Data for analysis. Data originating from homepages or social media need structuring, making it easy to analyse the data – for example to follow the digital sales funnel directly though successive conversions.

This structure is already embedded in the InfoSuite data model for most areas.

Easy access to additional documentation directly from the individual analysis

For documentation and support of the individual analyses, it may be necessary to grant direct access to basic data defined in tables.

Access to links, images, webpages etc. from the analyses has been prepared in the InfoSuite Data Warehouse – the only thing missing is you telling us where to find the documentation.

These were only some examples of the elements representing the InfoSuite Data Warehouse and data model. In case you would like to learn more, or if you want to hear how we would handle your data, please contact us to help you get started.

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