In many cases the key elements to be successful in business or in solving a problem are already in the data. At Monodon as a data science team, we truly believe that the precise definition of business needs and analytics of the case are half success.
The enterprises of the 21st century have the privilege of the opportunity to base their solutions on data. While who don't utilize these methods risk their competitiveness. In the process of utilizing the data in the proper way, the collection of the adequate amount and quality data and having a broad knowledge regarding the insights of the data are cardinal steps. Therefore, these require specific competence in data science.
The Monodon Solutions team consists of dedicated data scientists who specialized to utilize the appropriate data science methods to answer even the most complex questions or to support data-based decision-making.
How can data science help you?
Artificial intelligence and machine learning
During the learning of the machine learning algorithms, numerous models are created which based on the recognized relationships and patterns in the training dataset, can make predictions. This can be a classification of a specific element or predicting a value. Moreover, certain models are able to create new clusters based on the data. These models may consist of one element however for more complex tasks can be made of hundreds of elements. Owing to this, we can explore both linear and non-linear connection between the variables.
Optimization and automatization
Continuous optimization -finding a more effective way of solving a certain task- is the engine of long-term economic growth. Owing to this better and better products are created with less time and resources. Owing to optimization there is a natural competitiveness between the companies which is even fiercer nowadays due to digitalization. In the digital world, one of the best tools to improve efficiency is automatization during which we entrust certain tasks to machines to solve it with or without human cooperation. Thanks to automatization the production could emerge to a level never seen before in parallel with the improvement of the quality. Also, automatization allows us to monitor the processes, which support optimization in various ways. Nevertheless, to collect the required data, process it and extract the information for optimization we have to use data science solutions.
Image and video processing
During image and video processing we extract information or modify pictures or videos by utilizing various algorithms. These can be classical image processing algorithms or neural networks. Main objectives of image and video processing:
- Categorizing images
- Object recognition
- Image quality improvement
- Extract characteristics
How can we help you?
We help you to better understand the availabledata and the problems at hand.
As data experts, we help you understand your data, explore the underlying relationship and real problems. Our goal is to support you in achieving measurable and tangible business value by creating data-driven solutions.
During our cooperation, we will go through the followingprocesses:
Before examining the information in the datasets, we place special emphasis on conducting interviews and workshops with experts in the domain. Our goal is to gain a deeper understanding of the company's operations, the problems and requirements that arise, aswell as aspects that would not be known based on the background research.
The first and most important task is to examine the existing data sets, to assess their quality and quantity. Without this step, it is not possible to ensure that the information that is relevant for creating our solution can be extracted from the data.
Once these studies have been performed, hypotheses are developed, taking into account business requirements, along which we define the analytical tasks to be performed and the objectives.
In this phase, our data scientists develop, set up and test models to see if we can prove or reject previous assumptions. Our goal is to test as many models as possible with knowledge of business needs and goals.
In this section, we analyze the performance metrics of the models, with the goal of gaining a deeper understanding then making the necessary corrections and adjustments. It is important to share the results with the experts of the domain, and to develop possible development proposals together.
Once the fully validated model is finalized, it is deployed on a test server that allows the models to be monitored. If the models work properly in the test environment, we deploy them in the live environment. Our goal is to provide our customers with models that provide the right foundation for their proposed software developments.