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In March, biGENIUS was once again a topic at the TDWI conference. Peter Welker presented our Smart Data Automation Tool to interested experts during a virtual presentation. In this blog, we revisit the most important points and explain what added value biGENIUS can create for a company.

For all those who did not have the opportunity to attend the presentation on biGENIUS by Peter Welker at the last TDWI conference, we would like to give you the opportunity to briefly read the most important points.

When is it worthwhile to use this unique tool? How does it essentially work and what are its advantages for business? According to Peter Welker’s presentation, we will get to the bottom of these questions once again.

What is biGENIUS?

With the Smart Data Automation Tool biGENIUS, mappings can be migrated to biGENIUS in a highly automated way and then new mappings can be generated fully automatically. This not only saves a company time and money, but also allows the company’s own data analytics solution to be improved and further developed in a much less time-consuming and thus more cost-effective manner. The tool can do more than just automatically generate data structures and ETL processes. It revolutionizes the entire DWH lifecycle – from analysis, design and development to operation and change management.

When does its use make sense?

There are various starting points when a company should consider switching from its old ETL tool to biGENIUS:

  1. end of life: if an ETL tool has reached its zenith, for example because it is no longer maintained or it simply does not sufficiently support the new data platforms, switching to biGENIUS can be a sensible solution that can save time and money in the long term and improve data analysis.

  2. change of target platform, migration to the cloud: the path to the cloud is attractive. However, migrating the existing DWH solution with hundreds or even thousands of mappings there manually is hardly an option. Here, too, biGENIUS can provide a remedy. Depending on the existing ETL solution, biGENIUS can take over most mapping information automatically, so that not everything has to be developed from scratch.

  3.  increasing costs: developing each ETL mapping manually is resource intensive, especially if new business requirements have to be implemented frequently. Even with this starting point, using biGENIUS brings significant benefits because it makes development and operations highly automated.

  4. consolidation necessary: When DWH or data analytics solutions are getting on in years, standardization often suffers. This means that the structures that have grown over the years need to be standardized and consolidated again. Here, automation with biGENIUS is particularly suitable for returning to a consolidated solution.

How does it work?

How the process of an automatic ETL migration works is best illustrated by this graphic:

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Replacing the existing ETL jobs is not an easy task. After all, all mappings once had to be created manually with the ETL tool in a time-consuming manner. The graphic below now uses the Oracle Warehouse Builder example to show how this process can be automated with biGENIUS.

The solution is to read the mapping information from the old ETL tool and create new mappings from it in a highly automated way. But this time, not with an old-fashioned ETL tool again, but with a data analytics automation tool.

What are the benefits of automated migration?

A high level of automation is possible, which is typically much faster, cheaper and also more reliable than manual migration. Entities & data flows can be categorized according to rules, which makes the process clear and again less error-prone. Testing can also be automated with this solution as well as the consolidation of methods and patterns. Furthermore, changes in the underlying database can be implemented with less effort.

However, this is not a “drive-by migration”, but a project that can pay off especially with large DWH. Because in principle it can be said: the larger the DWH, the more favorable the automation per object/job.