areto offers holistic consulting for the planning, development and implementation of data science, machine learning & AI projects. We support you in the definition of use cases, develop machine learning models and implement them in your IT infrastructure. We work consistently agile. This means that we develop models algorithms and solutions together with you in short sprints.
We advise you on the way to a “data driven company”. Use the potential of your data. areto supports you in the planning and implementation of your data science, advanced analytics and big data projects. Our expertise: new technologies, complex mathematical methods and extensive experience in the development and implementation of your data science strategy.
Generate real competitive advantages through data science and advanced analytics. Use our longtime experience and expertise to develop and implement data science advanced & analytics use cases and projects successfully.
Benefit from the experience of more than 100 successful projects in the areas of data science analytics.
areto has a very broad methodological Know-how – from statistical modeling to supervised / unsupervised learning and natural language processing to deep learning.
We live and breathe agile approaches, i.e. iteratively developed models and prototypes as well as agile project management.
We work with the technologies that fit best into the customer’s enterprise architecture such as: Anaconda Enterprise, Exasol, R, Python, Spark and many more.
We develop together. So you always have the full overview of the development status and the results. We develop on your systems so you always have access to the models and algorithms developed for you.
Natural language processing has to capture language in the form of sound or character strings and extract the meaning. For this purpose NLP uses different methods and techniques which have to be passed step by step until the meaning of a text is fully captured.
The following parts of natural language processing are used in our projects.
With predictive analytics you gain new insights into customers and business processes. Better customer loyalty, reduction of returns / logistics costs and better estimation of future developments lead to increased sales potential and better products.
Predictive analytics is a fully deserved megatrend. First of all, it is important to create an adequate technological basis and sufficient data quality. The expected massive return on investment is worth the effort.
Algorithms automatically detect irregularities in payment transactions. Suspicious transactions are automatically stopped and manually checked.
Algorithms permanently analyze the behavior of machines and also include historical data for this purpose. So that the appropriate time for the next inspection is calculated and the required spare parts are also kept in stock.
Predictive analytics makes it possible to identify defective products at an early stage and remove them from the production process.
Which customers will leave, which ones do we want to keep, which ones not? – Knowing this is becoming increasingly important for companies.
With predictive analytics, companies can better estimate demand for individual products, enabling them to optimally adjust production, storage capacity and logistics.
What products and services can be offered to which customer at what price? The design of an optimal customer experience – this is possible with predictive analytics.
Often the terms Big Data, Data Science as well as Artificial Intelligence are mistakenly used as synonyms. In this video, Dr. Matthias Orlowski explains what Data Science really is and what it is not.