2025 Gartner Magic Quadrant for Process Mining
Selecting the right process mining solution and architecture is a highly individual decision. It depends on a company’s digital maturity, IT infrastructure, business goals, and integration requirements.
Deep Learning for Attribution Modelling
AI-based Attribution Modelling in Marketing
In commerce, companies often consider cutting marketing budgets during economic uncertainty or cost-cutting efforts. However, this short-term approach can harm long-term growth and market competitiveness. Consistent marketing is vital for…
Reduce organizational costs now with AI!
The DATANOMIQ AI Assessment is the check-up for your organization. We examine how your business organization can benefit from AI, with real results and implementation blueprints.
Why you should examine your organization for AI potential now
Why you should examine your organization for AI potential to gain process efficiency now with the DATANOMIQ AI Assessment.
Lambda vs Kappa Architektur für Data Lakehousing
Should your Data Platform rely on Lambda or Kappa architecture?
Lambda vs Kappa Architektur for Data Lakehousing - Which one is the best choice for your Cloud Data Lakehouse?
Data Lakehouse by DATANOMIQ
Data Lakehouse – When does it make sense for companies?
A data lakehouse enables companies to access and process data faster and more efficiently to use data properly as a production factor.
Data Platform by DATANOMIQ
Cloud Data Platform for Shopfloor Management
Cloud Data Platform for Shopfloor Management using data from MES, ERP-Systems as well as from machine sensors directly.
What skills a Data Engineer really needs
Why data engineering has long since stolen the show from data science in terms of importance and career opportunities, but is itself subject to constant change. Data Engineer Job Profile…
Data Assessment
Nowadays, companies are not only evaluated according to their sales and profits, but also according to their data. Many organizations are far from satisfied with their data management, the business…
Merge of data from different systems using Fuzzy Matching
A fuzzy matching was used to combine the data from the two different sources. A selection of fuzzy string-matching algorithms was tested, for example Jaro-Winkler Distance, Levenshtein distance, Soundex or cosine similarity. The open-source algorithms can be very efficient and there is a selection to choose from depending on the use case.