# The most sought
Data Science Consulting Services
Data science services help companies run experiments on their data in search of business insights. TRC Digital renders data science consulting leveraging Machine Learning, Artificial Intelligence, and Deep Learning technologies to meet our clients’ most deliberate analytics needs.
Data Science as a Service
Data Science
TRC Digital offers data science services to businesses, which enables them to capitalize on growth opportunities and improve their processes, without having to invest in developing in-house data science capabilities. These services leverage advanced analytics technologies such as deep learning, providing companies with valuable business insights.
Data science has become a critical component for businesses to stay competitive in today’s market. However, building and maintaining a dedicated data science team can be expensive and time-consuming. This is where data science as a service (DSaaS) comes in, offering organizations access to data science expertise without the need for a large investment.
- By leveraging the expertise of experienced data scientists, businesses can gain insights into their operations, improve decision-making, and drive growth.
- More specialized services and advanced tools than an organization might be able to develop in-house.
Data Science as a Service Usecases
DSaaS is a cost-effective and efficient way for organizations to leverage the power of data science to gain insights, make informed decisions, and drive business growth.
Our range of data science services
Business needs analysis
Outlining business objectives to meet with data science. Defining issues with the existing data science solution (if any). Deciding on data science deliverables.
Machine learning (ML) model design and development.
Data science insights ready for business use in the form of reports and dashboards. Custom ML-driven app for self-service use (optional). ML model integration into other applications (optional).
User & admin training, data science support consultations.
Data Preparation
Determining data source for data science. Data collection, transformation and cleansing.
ML model evaluation and tuning
Choice of the optimal data science techniques and methods. Defining the criteria for the future ML model(s) evaluation. ML model development, training, testing and deployment.
Machine learning (ML) model design and development.
Our Colloboration Models
Colloboration
Data science solution implementation
- We offer convenient access to the necessary expertise and resources
- creating a seamlessly operating data science solution that is customized to your specific business requirements.
Data science improvement consulting
- Our data science consulting services provide both strategic and tactical guidance
- Help you tackle issues such as noisy or dirty data, inaccurate predictions, and other challenges that may arise during your data science project.
Data science as a service (DSaaS)
- By utilizing our data science consulting services, you can avoid the need to invest in in-house data science competencies
- Gaining access to advanced data analytics insights through the use of cutting-edge data science technologies
Methods and Technologies We Use
We use a combination of established statistical methods and sophisticated machine learning algorithms, such as complex techniques like deep neural networks with over 10 hidden layers, to extract valuable insights from your data.
Methods
Frequently asked questions
By utilizing data science as a service, you can swiftly adopt data science capabilities without the need to build in-house data science competencies. This approach also provides advanced analytics insights that can be easily accessible to end business users.
DSaaS delivery is determined by service quality KPIs that are agreed upon, which can encompass the following:
Output quality KPIs:
- Insights by value (high / average / low).
- Forecast accuracy.
- Missing alerts.
Business result-related KPIs (e.g., improvements in energy consumption or service delivery time).
User satisfaction score.
To ensure the safety of data, we employ the following measures:
- Storing and processing data on secure cloud facilities such as Azure, AWS, and Google Cloud.
- Providing 24/7 in-house data security monitoring.
- Employing secure data transfer methods such as FTP and VPN, which are subject to regular health checks.
Why turn to DSaaS?
What are the reasons to consider DSaaS at this moment?
By leveraging the expertise of a data science team, you can rapidly adopt data science and achieve specific advanced analytics goals, resulting in the following benefits: