Predictive analytics consulting
Key applications of predictive analytics solutionsÂ
Looking to adopt predictive analytics?
About Itransition
25+ years of expertise in data analytics consulting and solution engineeringÂ
Proven expertise in artificial intelligence, data science and business intelligence
Strategic partnerships with Microsoft Azure and Amazon Web Services cloud platformsÂ
Adherence to relevant data protection laws and regulations
How we helped our clients
+8%
visitor-to-buyer conversion
BI platform for predictive analytics
We built an advanced analytics solution for an ecommerce company to analyze customer behavior in near-real time, forecast buyer conversion rates, and deliver personalized online user experience.
7x
overspending reduction
Advanced analytics solution for ad campaign optimization
We developed a solution for a digital media company to simulate promotion campaigns and generate forecasts based on their results, as well as get AI-powered recommendations on marketing campaigns changes.
Predictive analytics use cases across industries
- Predictive personalization
- Customer lifetime value modeling
- Predictive customer segmentation
- Customer churn prediction
- Predicting stock market anomalies
- Cash flow forecasting
- Credit risk scoring automation
- Financial strategy development assistance
- Employee retention prediction
- Skill gaps forecasting
- Disengaged employees prediction
- Employee performance forecasting
- Hospital readmission prediction
- Personalized treatment plans generation
- Patient deterioration prediction
- Predicting disease outbreaks
- Market trends forecasting
- Inventory demand forecasting
- Dynamic price optimization
- Supplier risk forecasting
- Equipment failure prediction
- Demand forecasting
- Remaining useful lifetime prediction
- Predict emerging market trends
Supply chain management
- Safety stock levels forecasting
- Predictive route planning
- Demand fluctuations anticipation
- Vehicle failure prediction
- Property value prediction
- Potential home buyers and sellers identification
- Building occupancy forecasting
- Predicting real estate market trends
Want to implement predictive analytics with Itransition?
Predictive analytics tools and techniques we use
As an experienced predictive analytics software vendor, we develop software leveraging all major programming languages and platforms available on the market and continuously expanding our tech stack with the new ones.
Programming languages
Programming languages
- Python
- R
- C++
ML frameworks and libraries
ML frameworks and libraries
- TensorFlow
- PyTorch
- Scikit-learn
- Keras
- Caffe
- NumPy
- pandas
- seaborn
- XGBoost
- CatBoost
- Matplotlib
- NLTK
Data visualization
Data visualization
- Microsoft Power BI
- Tableau
- Google Charts
- Grafana
- Chartist.js
- Fusion Charts
- Datawrapper
- Infogram
- D3.js
- QlikView
- Sisense
- Excel
- Streamlit
Data mining techniques
Data mining techniques
- Tracking patterns
- Classification
- Regression
- Outlier detection
- Association
- Correlation
- Clustering
- Dimensionality reduction
- Data cleaning
Machine learning algorithms
Machine learning algorithms
- Neural networks
- Decision trees
- Regression methods
- Time series analysis
Types of machine learning algorithms
Types of machine learning algorithms
- Supervised learning
- Unsupervised learning
- Reinforcement learning
Our predictive analytics development framework
Itransition’s specialists develop predictive analytics software from scratch and can take up your project from any stage, from solution planning and analysis to its deployment. As a predictive analytics service provider, we also render long-term support services for the implemented solutions to ensure its smooth functioning and on-demand scaling and improvement.
1
Requirements definition
Identification of business needs and objectives, user expectations and concerns
Assessment of the customer's technical environment
Definition of the solution's functional and non-functional requirements
2
Data analysis
Assessment of current data management workflows
Exploratory analysis of available data sources, both customer-owned and from public databases, to ensure it meets project goals
3
Design
Solution's architecture design
Definition of the implementation strategy, algorithms, and techniques
Selection of the optimal technology stack
Project's timeline and budget setup
4
Implementation
Data preprocessing, including cleaning, annotation, and transformation
Definition of the solution's evaluation criteria
Solution development in line with the selected implementation strategy
5
Integration and deployment
Solution integration into the customer's infrastructure
Solution launch into production
Technical and business documentation transfer to ensure the solution's correct operation and maintenance
6
Support and maintenance
Retraining and functional enhancement based on user feedback and new data from the production
Support of system operation under varying load
Our predictive analytics development guidelines
Compliance
Adhering to the requirements of ISO standards, Itransition delivers predictive analytics solutions that are fully compliant with industry and legal requirements (HIPAA, GDPR, PCI DSS, etc.).
In-product analytics
We equip the predictive analytics solutions with analytics to aggregate feedback and information on how people use the solution, test and evaluate new features, detect usage patterns, and plan and prioritize changes based on this data.
Data safety
When delivering predictive analytics solutions, we help you protect your data assets by implementing comprehensive data security policies, such as dynamic data masking, end-to-end data encryption, role-based access control, etc.
Data quality
We help you adopt best data quality management practices and implement cost-effective solutions to automate data validation, data cleansing, data profiling, etc.
Related services
Machine learning
Itransition delivers ML-based software solutions to process datasets, identify patterns and anomalies, and clarify the reasons behind poor performance and success.
Artificial intelligence
We create scalable AI-driven solutions to help you automate repetitive detailed-oriented tasks, enhance customer experience, and optimize business processes by accelerating evidence-based business decision-making.
Data science
Itransition provides end-to-end data science consulting services to help you leverage advanced technologies such as statistical algorithms, ML, and deep learning to mine your data for hidden insights, run root-cause analysis, forecast future outcomes, and more.
Business intelligence
We provide tailored BI solutions to integrate disparate data sources in an enterprise data warehouse and turn it into regular actionable insights, delivered to business users via interactive reports and dashboards.
Big data
Our team crafts big data business-oriented solutions to help you capture, process and analyze voluminous multi-type data to increase operational efficiency and accelerate the decision-making process.
Data analytics
We enable businesses to interpret the collected data and grow their analytics maturity, from implementing descriptive analytics to advancing to prescriptive analytics, to facilitate their decision-making processes.
FAQ about our predictive analytics consulting services
What engagement models do you offer?
At Itransition, we offer three engagement models for predictive analytics projects: a dedicated team, time and material, and a fixed-price model.
How much does a custom predictive analytics solution cost?
Predictive analytics project estimation is only possible after a thorough business needs analysis. For a ballpark estimate, you have to factor in multiple criteria, including:
- Data-related attributes (data volume, type, quality, etc.)
- The accuracy of predictive models
- Approach and methodology, and more
To get a free quote, contact our consultants.
What if we don’t have enough data for a predictive analytics solution?
The more data you have and the more diverse it is, the better. In case data volume or quality is not satisfactory, we help you collect or reuse available data sets.Â
Do we need to pay for the infrastructure to train predictive models?
No, we train predictive models on our instances.
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