{"id":7018,"date":"2026-08-10T16:19:42","date_gmt":"2026-08-10T14:19:42","guid":{"rendered":"https:\/\/kitech.ai\/?page_id=7018"},"modified":"2026-08-18T00:14:55","modified_gmt":"2026-08-17T22:14:55","slug":"data-engineering-bi","status":"publish","type":"page","link":"https:\/\/kitech.ai\/en\/data-engineering-bi\/","title":{"rendered":"Data engineering & BI"},"content":{"rendered":"
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t
<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Data Engineering & Business Intelligence<\/h2>\n

Data platforms that hold up \u2014 from modelling to the report in the specialist team.<\/em><\/p>\n\n

The problem<\/h3>\n

Data rarely sits where you need it. It comes from different systems, is structured differently and contradicts itself in the detail. If you draw reports from sources like that, you get numbers \u2014 but nobody can say whether they are right.<\/p>\n

That becomes expensive at the latest when decisions rest on it, or when traceability is required.<\/p>\n\n

What we do<\/h3>\n

We build the path from the source to the report \u2014 and in such a way that it stays traceable.<\/p>\n

That starts with data modelling: which entities exist, how they relate, what history is needed? Then the loading: interfaces to source systems, load logic, error handling, restart points. And finally the reporting layer, from which specialist teams can work themselves.<\/p>\n

Every step is built so that it can be checked \u2014 not as documentation added afterwards, but as part of the architecture.<\/p>\n\n

How we proceed<\/h3>\n
    \n
  1. Current-state review<\/strong> \u2014 Source systems, data volume, existing reports, open pain points<\/li>\n
  2. Data model<\/strong> \u2014 Business and technical model, history, alignment with the specialist team<\/li>\n
  3. Loading<\/strong> \u2014 ETL routes, interfaces, error handling, batch control<\/li>\n
  4. Reporting<\/strong> \u2014 Marts, reports, dashboards \u2014 where the specialist teams work<\/li>\n
  5. Betrieb<\/strong> \u2014 Monitoring, quality assurance, further development<\/li>\n<\/ol>\n\n

    Technologies<\/h3>\n