The SAP HANA database keeps all the data in RAM and that is why it is now possible to develop real-time analysis. Previously, for a large volume of data, Business Intelligence solutions were used: data is aggregated overnight and Business Intelligence programs display data that is already aggregated. The disadvantage of these solutions is that the aggregations have to be thought of before and the user cannot display a situation and then easily change the selection period or other selection criteria, like: remove certain products from the evaluation or exclude the turnover achieved from promotions.
The major advantage of real-time applications is that it offers the user the opportunity to analyze the results and allows them to improve their reporting based on the results obtained. A new data selection is possible and lasts only a few minutes. For Business Intelligence programs the aggregated data is displayed and a new selection is not possible immediately. The exclusion of certain products from the evaluation or the turnover achieved from promotions in the case of Business Intelligence solutions is not possible without a development task.

Although SAP HANA databases store all data in RAM, efficient data selection and aggregation techniques are required, because the application server runs on a server other than the machine running the database, and the data is transmitted over the network. The network is now the critical factor that can adversely affect the performance of the applications.

The first major project was the migration of the existing database SAP MaxDB to SAP HANA, a project that included beside the migration itself, the necessary analysis that preceded the migration.

All the programs developed by the shareholder of NOESNER SOFT SOLUTIONS, Daniel Nösner, ran in SAP HANA without modifications and much more performant than in the database MaxDB, because the programs were developed according to SAP recommendations.

Most of the programs written by other companies ran with small adaptations, most of the problems being related to displaying the results in an undesirable order, the programs developed by other companies did not have a predetermined sorting and were based on the fact that the database sorts by the primary key. However, the performance of the programs written by other companies was not substantially improved by the migration to SAP HANA. For obtaining high performance some of these have been modified at the user's request.

In the analyzed programs that were optimized for SAP HANA, it was observed that the volume of the data being processed is of tens of thousands of records, that can be grouped according to different criteria: the material group, the region the company’s clients belong to, a certain time interval, attendance at a particular event. All these groups are shown once the display is selected based on a criterion. It is possible to easily drill down from a higher group level to a basic level, for example: navigate from the turnover calculated on a particular region or group of materials to material details or details related to each collaborator.

Short time analysis of company data, grouping these according to the business requirement, facilitates trends observation and taking business decisions based on the latest changes in any area of the supply chain: Purchasing, Manufacturing, Inventory Management, Demand Planning, Warehousing, Transportation, and Customer Service.

Repeated testing of optimized applications has shown that data display is done without delay, regardless of the level from which they are accessed, the volume of records, the grouping of data.

All the company's processes can be managed in one system, the user can easily access the data and navigate at any level, grouping the data, having the possibility to select only some fields from the ones displayed for a more structured view.

Examples of real-time projects that read a large amount of data:
• Displaying a list of the materials ordered in a period of up to one year compared to the indicators obtained a year ago at organization level, on each company separately: the quantity, turnover, cost and profit margin are displayed by categories of sales, the promotions being highlighted separately. The data is displayed for the entire selected period, per month, per customer down to invoice level;
• Sales statistics with turnover at global level, by regions, customers, groups of materials, down to invoice level