Category: Best practice
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A Quick Guide to ADABAS/Natural Modernization

What are ADABAS and Natural?

ADABAS stands for “adaptable database system.” It was launched in 1971 by Software AG using an inverted index architecture and is thus a nonrelational database system. The system was known for its speed and reliability outliving many of its contemporaries (rival inverted index DBMS Datacom eventually transitioned to a relational architecture.

In 1979 Software AG developed a fourth generation (4GL) application development platform for the ADABAS ecosystem called Natural. Applications utilizing ADABAS as a database are, therefore, often built using Natural. Natural supports both procedural and event-driven programming.

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Knowing your legacy modernization options

Most companies today have a strategy for—or at least some goals surrounding—digital transformation. But as much as a coherent digital strategy is recognized as a necessity in today’s business world, many companies still struggle to achieve their digital goals. One common barrier they face is their dependence on legacy software. Removing this barrier has the potential to accelerate a company’s digital transformation, but it is important to understand that there are a number of options when dealing with legacy applications:

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The secret behind successful modernization projects

Migrating applications from aging programming environments (e.g., Cobol, Pacbase, etc.) to modern Cloud-ready technologies (Java EE, .NET…) is a challenging task both at functional and technical levels. Unlike classical software projects -usually initiated from scratch- modernization projects start with millions of lines of code to be explored, understood and transformed.

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How to start a successful Big Data Application from scratch

Let’s imagine that you are a Software Developer working in a highly innovative data-driven start-up delivering a cutting-edge product called “Data Digger Solution”. It gathers raw data from various heterogeneous sources (e.g. social medias, websites, CRM, online sales, servers, emails, etc.) and process them to gain tangible insights using fresh semantics. These insights can be used to provide concrete and profitable interpretations (e.g. in terms of sales and web presence) to the clients.

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