Data Science
Consulting and
Project development

Using Data Mining und
artificial intelligence to
create data-driven solutions
and decisions.

How ...

  • can I increase my revenue?
  • will market demand evolve?
  • can I optimize my stock costs?
  • can AI help my business?

Use Data Science
to solve operational problems
in a data-driven way.

BIG DATA, Data Analytics, Whether Artifical Intelligence or Autonomous Driving. There are many trends and future topics.

But how can these help my company in its operational business? Which everyday and current problems can be solved with it, and which data-driven solutions are even possible with my data?

Together, we develop these solutions against the background of your problems using current techniques and processes. Thereby we use well-known algorithms from the areas of Business Intelligence, Data Mining, Data Pattern Recognition or Neural Networks – individually and holistically. We advise you from analysis and prototype development to deployment. We develop concepts together with you, implement the solutions technically and support you in the implementation of data-driven business models and strategies.

How we proceed? Focused.


Data is repeatedly referred to as the "oil of the 21st century" . Often as a "by-product" of any digitization measures, many companies are not even aware of the treasure they are sitting on.

Whether it's a sophisticated Data Warehouse, distributed ERP systems, digital accounting, an Excel list or a diskette: as soon as data is generated in operations, it forms the raw material from which relationships and patterns can be refined. These then form the fuel for data-driven applications, solutions or important decisions.

Data Mining

Turning oil into a fuel that can be used to power a wide variety of systems requires technology, processes and know-how. The same applies to BIG DATA. The existing data is the raw material. But in order to extract relevant knowledge, patterns or correlations and thus make the data treasure usable, suitable processes and algorithms are needed.

The Data Mining includes the extraction and visualization of relevant patterns, knowledge and relationships, in a structured or unstructured data set.

These patterns and interrelationships, beneficially processed visually, form the fuel for data-driven services or models, since they are the basis for training algorithms of machine learning.

Data mining allows insights and statements into and about one's own data, which often go far beyond the possibilities of generic BI or analytics solutions. The data mining thus already enables burdenable statements and data-driven decisions on operational problems.

Thus, data mining is of outstanding importance. Because during this step it can already be estimated, whether and which data-driven applications or solutions are at all possible based on the existing data are even possible and which patterns are available.

NET side effect: The more precise and meaningful the respective patterns are, the more accurately works the machine learning and thus also a later AI.

AI and ML development

If data mining refines "data" fuel from the raw material in the form of patterns and correlations, it needs the appropriate engine, which is driven with it.

The kind of the engine and its efficiency are thereby substantially determined by the respective problem and the quality of the patterns found.

The core is formed by a wide variety of algorithms from the field of machine learning (ML). These are selected on the basis of the problem and existing data, trained with the found patterns and finally evaluated.

These models - often only the combination and use of different methods achieve an outstanding result - thus form, extended by any expert systems, the core of a artificial intelligence with real, operational added value!

Whether forecasting model to estimate orders, the optimization of warehouse space or the automatic classification of attack patterns in real-time streams: Whenever the extraction and understanding of correlations based on of Data Mining is to be automated and extended to complex decision-making systems, the development of ML models and AI systems lends itself.

62,0 %
of retailers
gained a competitive advantage through data analytics.
Top 5 Data Science Facts in 2021

0.5 %
of all generated
data is analyzed
and used.
Facts About Data Science Analytics

51 %
inform themselves on the internet
before making a purchase.
Think with Google, 2019

Data Mining

Our services

Explorative data analysis
and reporting
data evaluation
Uni- and Bivariate
Reporting and charting
Feature selection
Data aggregation
of different sources
Your use case?
Fraud detection
Failure analysis
and spotting
Your use case?
and issue detection
Pattern recognition
and extraction
Time series analysis
Correlation analysis
Association analysis
and rule extraction
Your use case?

AI and ML development

Our services

Sales forecast
Rating forecast
Order forecast
Return forecast
Your use case?
Development of
predictive models
Model development
to solve
optimization problems.
Recommendation systems
Inventory and
stock optimization
Process Mining
and optimization
Production optimization
Your use case?
Risk evaluation
Classification and
Your use case?
Development of
recommendation systems

strategy development
and consulting.

Our services

Customer analysis
Coverage analysis (online)
Demand determination
Competiton and analysis
Market analysis
Trend identification
and determination
Demand and
customer insights
Sentiment analysis
Contextual analysis
and impact
Competition analysis
Strategy derivation and
Demand determination and
trend derivation
Automation and
API consulting
und development
Digital strategies
and consulting
Digital transformation
and business models
Subsidy consulting

Use Cases Data Science

Do you want to find out how data science can help you? Let us show you.

tisson & company use case

Umsatzsteigerung im Up- und Cross-Selling mit Data Mining

Data Mining | Empfehlungssysteme | Umsatzsteigerung | Assoziationsanalyse

Wie Bestandsdaten zu passgenauen Empfehlungen und höherem Umsatz führen.

Learn more
Unterschiedliche Daten auf einem Board

Mit Data Mining Vertragslaufzeiten vorhersagen

Data Mining | Klassifikation | CRM | Prognose

Durch Merkmalsklassifizierung Nutzerverhalten verstehen und präskriptiv handeln

Learn more
Tisson & Company - Wer sind meine Kunden?

Wer sind meine Kunden? | Data Mining im CRM

Data Mining | Kundensegmentierung | Versicherung

Mit Data Mining Wissen sichtbar machen

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Recent contributions

You want to learn more about our approaches, backgrounds and new fields of application?
Feel free to visit our blog and stay up to date.

Retourenquote mit Data Science - Pakete als Symbolbild

Die Retourenquote senken und Nachhaltigkeit steigern: Data Science macht es möglich.

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Der Onlinehandel boomt und immer mehr Kunden informieren sich und kaufen ihre Produkte online. Diese werden dann bestellt, pünktlich geliefert, …

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tisson & company - Die Welt in Zahlen.

Die Data Science schafft neue Möglichkeiten.

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Das Kauf- und Entscheidungsverhalten von Konsumenten wandelt sich zunehmend in Richtung von datengetriebenen Services und E-Commerce. Durch die zunehmende Nutzung der digitalen Portalökonomie ändert sich auch …

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Innovation - wie Unternehmen innovativ werden

Workfront | Work Management | Innovation

Um rechtzeitig und adäquat auf Krisen zu reagieren, müssen Unternehmen vor allem flexibel, agil und innovativ sein. Dies zeigt sich …

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Review eigener Geschäftsmodelle und -prozesse: Vom Benchmarking zum ‚Out-of-the-box‘-Denken...

Geschäftsmodelle | Benchmarking | Prozesse

Bei der regelmäßigen Überprüfung des eigenen Geschäftsmodells und der begleitenden Prozesse kommt in vielen Unternehmen das ‚Benchmarking‘ zum …

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Die New Workfront Experience kommt!

Workfront | New Work | Design

In enger Zusammenarbeit mit namenhaften Kunden hat Workfront an einer Nutzeroberfläche für das gesamte System gearbeitet. Die „New Workfront Experience“ …

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Integrationen zwischen Workfront und Produkten von Adobe

Workfront | Adobe | Integrationen

Workfront unterstützt Unternehmen dabei Prozesse intelligent zu nutzen und zu steuern, Projekte erfolgreich umzusetzen und die Arbeit ihrer Mitarbeiter effektiv …

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