When it comes to our consulting services, Retainers AI and Analytics services combines end-to-end AI solutions with domain and industry insight to harness the power of human-machine collaboration.
Our approach to AI solutions combines strategic thinking, industry know-how, and deep AI knowledge to deliver insights that help clients realize their complex ambitions.
How do we do it:
Data Strategy and Consulting:
- Collaborate with clients to develop a comprehensive data strategy aligned with their business objectives.
- Provide consulting services to identify data sources, define key performance indicators (KPIs), and establish data governance policies.
Data Warehousing and ETL (Extract, Transform, Load):
- Design, implement, and manage data warehouses to consolidate and organize large volumes of structured and unstructured data for analytics purposes.
- Optimize data storage and retrieval for fast and efficient querying.
- Integrate data from diverse sources, ensuring consistency and accuracy.
- Implement ETL processes to transform raw data into a format suitable for analysis.
Big Data Analytics:
- Utilize big data technologies such as Hadoop, Spark, SQL and NoSQL databases to analyze large and complex datasets.
- Implementing cloud based analytics solutions as well as Databricks unified platform solutions for batch and real time data analysis.
Data Visualization:
- Create interactive and intuitive data visualizations to make complex insights more accessible.
- Use tools like Tableau, Power BI, or custom-built dashboards to present data in a user-friendly manner.
Custom Machine Learning Models:
- Design and develop custom machine learning models tailored to specific business needs.
- Implement supervised and unsupervised learning algorithms based on the nature of the problem.
Predictive Analytics and Recommendation Systems:
- Develop models and algorithms to predict future trends and outcomes based on historical data.
- Implement machine learning techniques for predictive analytics.
- Build recommendation engines for personalized content, product recommendations, and user experience optimization.
Descriptive Analytics and Prescriptive Analytics :
- Analyze historical data to provide insights into past performance and trends. Summarize and interpret data to support decision-making processes.
- Offer recommendations and strategies based on data analysis to optimize decision-making.
- Provide actionable insights for improving business processes.
Data Quality Management and Governance Strategy:
- Implement processes to ensure data quality, accuracy, and consistency. Provide data cleansing and enrichment services.
- Establish a comprehensive data governance framework that defines the roles, responsibilities, and processes for managing data within the organization.
- Conduct data profiling and quality assessments to identify and address data quality issues. Implement MDM strategies to create a single, authoritative source for key business data (e.g., customer, product, employee).
- Define and enforce policies for the entire data lifecycle, including data creation, storage, archiving, and deletion.
Custom Analytics Solutions:
- Develop customized analytics solutions tailored to specific industry needs and client requirements.
- Address unique challenges through innovative analytics approaches.
Training and Education:
- Provide training programs to empower client teams in using analytics tools and interpreting insights.
- Offer workshops and educational sessions on best practices in data analytics.