With over a decade of expertise in data science, our team at Czario merges the benefits of machine learning and statistics to probe into data mines, identify patterns, and establish value. We help relate the usability of data to the problem in hand with the help of programmed algorithmic models.
We help industries flourish with the power of cognitive data management. With our data science services, we identify hidden patterns, automate processes, make valuable predictions, and recommend alternative courses of action to prevent losses or adverse circumstances in business.
Our data scientists can apply an ARIMA model or a deep neural network to generate reliable demand predictions especially for the manufacturing and logistics industries. We can build neural networks or apply ML algorithms, such as hierarchical clustering and multi-class support vector machines, to evaluate your suppliers and assess the risks associated with each of them.
We can help you fight low overall equipment effectiveness (OEE) by identifying the root causes for low availability, poor performance, excessive downtime, and quality losses. We apply machine learning techniques to achieve predictive maintenance, undisrupted functioning, and enhanced product quality.
Our data scientists can analyze the data from sensors installed at monitored machinery parts to understand the patterns in machinery functioning using IoT so that you could plan its maintenance more efficiently. One of the ways to handle this pain point is to apply Naïve Bayes algorithm to classify normal and pre-failure events. To get more insights, we can further classify the cases based on the time left until a breakdown or criticality.
Even if the monitored parameters seem to be fine when considered individually, their association can be a matter of grave concern. With the help of data science, we can identify such hidden interdependencies and their potential consequences. As a result, operators can receive real-time alerts and solve issues themselves or escalate them promptly to the attention of the maintenance team.
Machine learning techniques are helpful when you need to identify process disruptions at each production stage. We compare the actual and expected duration of each operation, and check the vital parameters. This will help move beyond simple thresholds to really complex dependencies and identify the deviations that may affect product quality pre-emptively. Having learned at some early stages that raw materials or parts are defective, you won’t waste your time and resources on continuing with them at all the remaining production stages. This can also save the entire manufacturing process from being thwarted or slowed down by a defective part or component.
Applying machine learning techniques, such as collaborative or content-based filtering (or both), we can design a recommendation engine to boost the sales of your ecommerce store. Such an engine can help you make your customers happier with relevant product offer highlights based on their preferences or previous purchases. A webpage showing personalized content, a mobile app with promo offers that spark customers’ interest, as well as relevant email campaigns are also among the gains that you can get with data science.
We can implement machine learning-based lead generation and opportunity scoring so that you’re sure that your sales team adheres to the business plan and aligns their actions to the strategy while prioritizing their efforts.
Besides, we can create a machine learning model to make your communication with customers seamless and lucrative. Trained to detect attitude markers and recognize your customers’ mood, the model will signal your sales team if a particular customer experiences negative emotions.
We can provide you with a machine learning model to help you streamline the sales process or come up with a readily available plan by providing your sales team with clever insights and actionable recommendations.
We’ll apply machine learning algorithms to assess the customer behaviour at various occasions and tap the right opportunity to grab their attention or alter their behaviour. For example, you’ll be able to assess whether it’s likely that your customer is a late payer, how they will react to price changes or to promotions or predict cart abandonment. We can also help you identify potential churners so that you can design the strategies to prevent their loss or replace them.
Using machine-learning-based analysis, our data scientists can turn images or videos into meaningful info. You can use these insights to solve various business tasks, such as automated visual inspection, facial or emotion recognition, grading, and counting.
We engage both proven statistical methods and elaborate machine learning algorithms, including complex techniques likedeep neural networks with more than ten hidden layers.
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| Statistical methods | Descriptive statistics , ARMA, ARIMA, Bayesian inference, etc |
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| Neural networks, including deep learning | Convolutional and recurrent neural networks (including LSTM and GRU), Autoencoders, generative adversarial networks (GANs), deep Q-network (DQN), Bayesian deep learning. |
| Type | Technology |
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Our data scientists will review your data, remove duplicates, erroneous and unreliable records. We will run all the required data cleaning procedures to ensure that your data is of high quality and relevance. Additionally, we can advise what extra data can improve analysis accuracy.
Our data consultants have a close look at your data to identify outliers. As a next step, we differentiate between signals and noise. For that, we may need expanding the data set and analyzing additional parameters while consulting subject matter experts. Our experts clear unwanted noise from your data which ultimately improves the accuracy of your model.
We will scrutinize your as-in situation to find out what causes the faulty predictions. Say, deep learning is applied, and your model suffers overfitting, meaning that it provides super-accurate predictions on the training data, but fails to work properly on real data sets. In this case, we recommend a dropout as it would allow breaking happenstance correlations in the training data.
Want to embrace the unparalleled benefits of data science to your data-centric business? Connect with our experts today and see the newer light in old data.
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