Data Science is a discipline about the analysis and processing of big data and the extraction of the essential information that we will apply for your needs.
For CARRYING OUT ANALYSIS OF BIG DATAwe use modern technology and reliable tools
SSIS - is a tool for ETL database solutions, the primary instruments include SQL Server, MySQL, MongoDB, Google BigQuery and others.
Machine Learning is a tool that allows a machine to train while processing data and forecasting outcomes. This tool is considered to be a variation of artificial intelligence.
Main stepsHow do we work with data
Gathering of various data:
- Structured, semi-structured, and unstructured data
- Flat files (logs, text files, csv, json)
- Data from DBMS, Big Data, Emails, Websites, and Web APIs
- Cleaning, normalizing, analyzing text, extractor, transforming, profiling, organizing data warehouse and loading data into storages
- Primary data analysis (ABC analysis, RFM analysis)
- Time Series Analysis (General Forecast)
- Clustering (division into classes/groups)
- Regression (forecast using exposure factors)
- SWOT analysis (product evaluation before releasing it on the market)
- Optimization of supply/transportation logistics
- Fraud detection/intruders among employees or customers
- Optimization of production processes (loading, resource allocation)
- Setting of the optimal price for achieving maximum profit
- Comfortable interactive graphs and charts in a user-friendly interface
- Creation of individual reports considering all the customer’s preferences and requirements
Our servicesWhat we offer at the end
Transform your organization’s information into a business presentation. In order to make effective business decisions, provide the necessary data to key persons of interest or professionals.
We can help you to integrate forecast analytics into your business operations in order to measure any success instantly, and to predict market demand and risks.
Using Data Science, you can analyze big data, optimize operations, automate key processes, improve control schemes, measure and manage performance better, and you can simplify capacity planning and risk-management.
Reducing the number of manual operations for routine tasks, collecting valuable user data for setting up advertising campaigns and providing interesting, personalized user experience.
Take a step with us towards Data Science and artificial intelligence to provide a quantum leap in your automated operations, risk management and personalized customer service.
Using neural networks and MaschineLearning algorithms for automatic schedule generation.
To develop a system that will generate an optimal schedule and dynamically change it depending on the constantly-updating information about customers visiting the cinema.
An algorithm had been developed for schedule generation, it is based on the historical data of the cinema and the history of movie visits.
The system allows you to generate a schedule for the cinema for a given period of time, taking the limitations set by distributors into account.
The use of neural networks to analyze the similarity of films and to select an audience for newsletters using historical customer data.
To develop an algorithm for automated mailing of recommendations.
With the help of neural networks a microservice has been developed, it identifies similar films, analyzes the client’s history and sends him an email with movies that are/will be available at the box office in the near future.
Use of this system improves customer feedback, improves the formation of newsletters, and also makes it possible to identify popular directions in the film industry for further work, for example, to shape a company’s pricing policy.
Client base RFM analysis was carried out using clustering tools and Machine Learning.
To identify the main customer groups based on profitability, frequency of purchases, etc.
Applying k-means clustering method using Machine Learning.
Understanding of target groups for further work with them.
Sales analysis and basket selection
Using collaborative filtering to analyze the customer’s purchase history and to create an individual selection of goods based on it.
A personalized basket for each client.
Using neural networks, a model that determines the sequence of purchases in customer receipts, analyzes them and performs an individual selection of goods has been developed.
Usage of this model significantly improves sales, makes it possible to evaluate popular products and to develop recommendations for each client.
Ticket sales forecast
Using Machine Learning algorithms to analyze past ticket sales and to forecast sales for future events.
Develop a system for predicting ticket sales.
A set of models has been developed, they analyze past ticket sales and predicts future sales using Machine Learning.
Usage of this model significantly improves understanding of ticket sales, allows you to evaluate popular types of events and to choose the optimal sales strategies.