Data science services & solutions
Data is the engine of innovation and growth for businesses in the public and private sectors. By helping you uncover hidden relationships and patterns in your data, we uncover insights and future-proof your investment by progressively monitoring our solutions.
We offer a wide range of consulting and implementation solutions in data science, machine learning, including deep learning and artificial intelligence. Fundamentally, we believe that data science is more than algorithms and models; it is about transforming data into actionable insights that enable organizations to make informed decisions.
By partnering with Data Oracle, you will be able to harness the full power of AI and data science in your current work practices, helping you increase productivity, increase efficiency, and create a data-driven future for your organization.
Our Data science solutions
- Predictive analytics, forecasting and risk modelling
- Machine learning, deep learning and reinforcement learning
- Natural language processing (NLP)
- Statistical analysis and task automation
- Generative AI and large language models (LLMs)
Benefits of data science services
- Innovation and agility
- Sustainability and social responsibility
- Improved decision making
- Better recruitment.
- Raise Sales
- Enhance efficiency
- Mitigate risks and identify new opportunities
- Informed decision-making
- Enhancing productivity and efficiency
- Risk management and fraud detection
- Social impact and sustainability
Our Data Science Services
- Churn Management
- ClickStream Analytics (Mobile/ Web)
- Recommendation engines
- Security and Risk Analysis
- Demand forecasting
- Inventory optimization
- Supply chain management
- Hyper-personalization
- Multi-touch attribution
- Ecommerce campaign optimization
- Customer lifetime value
- 360 Customer journey
- Sentiment analysis
Our Data science solutions
Data science’s interdisciplinary approach to analyzing large amounts of data combines the principles and practices of mathematics, statistics, economics, artificial intelligence and computing.
By combining tools, techniques and technologies such as data analysis/modelling, human-machine interaction and algorithms, data scientists ask and answer questions such as what happened, why it happened, what will happen next and how can the results be extrapolated and used for planning and decision-making?
Data science therefore drives innovation and helps to identify new opportunities.
Our preferred tools and technologies
Data Capture: The first step, data is acquired, entered and extracted from different sources which involves gathering raw structured, semi-structured and unstructured data.
Data Storage and Maintenance: Here, data is stored, cleansed and organized in a way that can be used.
Data Processing: During this phase, the goal is to uncover patterns, trends, and relationships that can provide valuable insights for decision-making.
Data Analysis: In this stage, the processed data is analyzed using various techniques that help understand past trends, making future predictions, and identifying areas for improvement.
Communication: Finally, the results of the analysis is visualized in different forms such as charts, graphs, and reports.






