Before companies start the actual migration, they should take the time to check and clean up their data in the old system. This is the only way they can take full advantage of the new ERP system.

We get the RFC module for data extraction certified by SAP® on a regular basis since 2018 to ensure that our solution dab:neXus always meets the latest standards.

In projects for our customers as well as in our dab:AnalyticSuite, the topic of "free goods" plays an important role and is frequently requested. That' s why we would like to take a closer look at this topic in a blog post.

Following SAP's announcement to discontinue support for older ERP systems from 2025, more and more of our customers are switching to S/4HANA. Since the system is based on a changed data model, we regularly encounter the question of whether there will be problems with the dab:AnalyticSuite. 

With our solution the dab: Exporter we do not only want to give our customers an easy way to their data. Our technology should integrate smoothly with all SAP solutions and give our users a good feeling about security and quality requirements.

In my last blog, I explained some fundamentals of outline agreements (value and quantity contracts, and also scheduling agreements) in SAP®. As mentioned, I will now examine outline agreement release orders. I will first briefly explain how to look up these in SAP®, before moving on to the data situation. In detailed terms, this involves logging release orders at table level.

In this blog I would like to give you an overview of outline agreements in SAP® in the purchasing module. Extra to sketching the concept itself, I will give you insight into its mapping from a viewpoint of data analytics, in other words SAP® tables and field level.

In this blog post I will discuss “free goods”. They play an important role both in projects which we implement for our customers and also in our dab:AnalyticSuite, and form the subject of many queries. Important factors include profitability in terms of calculating profit in a customer’s business, compliance (bribery through payments in kind, formation of black accounts, undue advantage) or simply monitoring possible IT interface errors which can result in proper deliveries inadvertently not being invoiced.

In this blog post, I will discuss ways in which you can use data from SAP® systems to obtain information about your data. Although the article is fairly technical because it deals with meta data, I will use brief examples to illustrate specific issues. To begin with, I will describe the starting point, before drawing on selected examples to explain how the Data Dictionary can be used, and then ending with a brief conclusion.

As the weather gets colder, you often find savory hotpots dished up, with all kinds of ingredients. But in data analytics it can be better not to put too many ingredients in a single pot for analysis. Or to know exactly which ingredients are right to enjoy a clear structure — or even to deconstruct, as you might say.

This article will demonstrate the difference between Purchasing Document Category (EKKO_BSTYP) and Purchasing Document Type (EKKO_BSART) which can be found in table EKKO. The table EKKO includes the header data of all purchasing documents. Which documents are concretely concerned, will be described in the following chapters.

This article discusses the account balance display. There are several postings per vendor respectively customer in one year. The tables LFC1 and KNC1 offer a consolidated view to vendor postings or customer postings within a period. This article describes the mentioned tables. Furthermore, the corresponding transactions in SAP® are described.