Author: Werner Dähn, rtdi.io

Companies that invest in (SAP) software products naturally want to know that what they invested in will stick around for more than just a few years. With some key numbers shrouded in mystery, how can customers reliably tell which products might vanish from the market soon?

Software development takes time, so you have to plan the solution before the first customers even ask for it. When I invented Hana Smart Data Integration (SDI), no one had such a solution on their radar - ETL tools were good enough.

Building software for the (SAP) cloud is very different from on-premises software. This obvious and trivial fact has consequences for software development rules.

Does anybody remember the SAP statement, "Hana is not a database, it is a platform"? It caused confusion back then - and even today.

Scrum can be a fantastic method to engage and motivate software development teams, but companies should beware typical pitfalls.

When it comes to software, creating, building and maintaining a User Interface (UI) might be one of the most difficult tasks.

Miracles are done immediately, impossible things take a little longer. A more detailed view of the SAP Hana Cloud story.

In a data warehouse, the data is stored in a relational database. This is expensive and accordingly there are products from the Big Data world that start here. Parquet, Hive, SAP Vora and Exasol are the best-known representatives in the SAP environment.

What exactly is meant by the term Big Data? Does Big Data simply mean mass data, i.e. "lots of data" in the data warehouse? Or is Big Data a replacement for the data warehouse?

Reportage: A short story about the long road - In-memory computing with the Hana database: When the concepts of Hana were first introduced within SAP, I thought that any database with enough memory is an in-memory computing database and correspondingly fast. But at least I wasn't the only one.

Many companies are just starting out with Big Data. They have initial ideas. The potential is being explored. SAP also has different approaches to the topic, depending on which department you talk to.

Big Data is a big topic, but the multitude of possibilities is overwhelming. Every software provider comes up with different products and different goals. I would like to bring some structure into this jungle and make it easier to get started.