New technologies hold great potential for extracting new value from processes. “Intelligent monitoring and decision-making processes should provide companies with the ability to control and optimize their operations and entire value-added networks in close to real time.”
This is the official vision of the Federal Ministry of Research; however, this digital transformation has not yet fully arrived in the business world. Only a select few companies are already drawing on advanced analytics capabilities to engage in real-time market research and thus gain insights into the patterns and needs of existing and potential customers. Many companies still consider traditional reporting that focuses on past events the “gold standard,” but these companies are missing out on enormous savings and growth potential.
Our analytics services help you gain insight into your data and sharpen your competitive edge.
What our customers want:
- Gain valuable insights from a vast pool of data
- Develop a proof of concept for identifying new business opportunities
- Implement solutions in existing server or cloud systems
- Apply deep learning to text/images/audio
Data Analytics Is a Visualizer
Geographic Data
The field of geographic data science has added geographic data to the toolbox of data science. But instead of compasses and sextants, today programming languages such as R and Python are used to extract information .
Network Analysis
Many complex social and technological systems can be modeled as networks. This opens up possibilities such as gleaning information on the stability of financial markets or determining the likelihood of users having common friends in social networks.
The graph shows an arc diagram that illustrates the interrelationships of a small network – in this case, the national leagues from which players were picked for the national team at the Soccer World Cup in 1998.
Data Clustering
Clustering is a process that identifies similar groups in large data sets, such as customer groups for targeted marketing.
The graph shows how the t-SNE (t-distributed stochastic neighbor embedding) algorithm iteratively finds three different groups in a data set with multiple variables.
Text-Based Data
Text analytics and natural language processing can be used to extract information from texts, train chatbots and generate automated reports, among other things. A common first step in analyzing text is to generate a word cloud. The graphic shows a word cloud of the Wikipedia entry on “data science.” The size corresponds to the frequency of words in the text. Unsurprisingly, the two most common words in this cloud are “data” and “science.”
Our Advanced Analytics & Data Science Services
Our team combines expertise in mathematics, statistics, computer science as well as design and has longstanding experience in areas such as predictive maintenance, text analytics, fraud detection and big data. We help you all the way with services that include an initial exploration of the business opportunity and quickly setting up a proof of concept through to the development of a data-driven system that includes knowledge transfer and dissemination. In all we do, we painstakingly consider your specific needs and expectations.
Service Overview
aCRM (Analytical Customer Relationship Management)
- We analyze your data in a manner that goes beyond traditional filing.
- Using clustering or classification, we build real-time scoring models and incorporate the customer life cycle into an AI process.
- We help you plan successful campaigns and generate improved customer insights.
Fraud Detection/Prevention
- We find the pin in the haystack by applying methods such as deep learning or decision trees.
- By combining four different approaches to fraud detection, fraudulent actions are identified with unsurpassed precision.
- Effective automated detection of fraud attempts.
Predictive Maintenance
- Intelligent machine monitoring that helps to prevent failures from happening in the first place.
- Analyzing machine data such as log files makes it possible to calculate the probability of equipment failure.
- Shorter downtimes and lower mean-time-to-repair (MTTR) unlock savings and greatly amplify end customer satisfaction.
Advanced Text Analytics
- From Shakespeare to tax process documentation and from classification to sentiment analysis.
- Using our own stemming algorithm, metafinanz experts analyze unstructured data such as English texts.
- Possible fields of application include trend recognition by means of social media analytics or automated routing of inbound mail.
Smart AI
- Combining predictive analytics and robotics.
- Automated decision-making processes thanks to specialist-level data analysis based on stochastic prediction models and artificial intelligence methodologies.
- Achieve cost savings and accelerated processes while gaining more time for personalized customer relations and strategic decision-making.
Benefit from Our Strengths
We bring all key steps of the data science circle together. This allows us to offer you comprehensive services from a single source.
We can draw on a pool of certified metafinanz industry veterans who are experts in fields including mathematics, computer science, statistics and design.
We also know that technology is only part of the picture. Employee adoption is of the essence when it comes to implementing and developing data science solutions.
We are intimately familiar with various microservice solutions such as Docker and Kubernetes, allowing us to orchestrate the smooth rollout in your live server or cloud environment.
Would you like more information?
Your contact
Stefan Schwesig
metafinanz Informationssysteme GmbH
Leopoldstrasse 146 | 80804 München, Germany
Tel. +49 89 360531-5273
