Preparing Data for Analytics, Decision-Making and AI
TinAI Data is the data management and preparation module of the TinAI Core framework. It gathers scattered, inconsistent or raw data from different sources and converts it into organised, reliable data that AI and analytics systems can use.
The quality of an AI system's performance depends directly on the quality of the data it receives. TinAI Data therefore does more than transfer data: it also checks its validity, structure, consistency and usability.
This module can receive information from databases, files, APIs, business software, equipment and other sources. After cleaning and standardising the data, it can pass it to other TinAI modules or the customer's existing systems.
TinAI Data Capabilities
- Collection of data from different sources
- Connections to databases and business software
- Data cleaning and standardisation
- Identification of missing, duplicate or inconsistent data
- Combination of data from multiple sources
- Conversion of raw data into usable structures
- Creation of automated data processing workflows
- Preparation of data for model training and evaluation
- Creation of features required by AI models
- Data quality checks and evaluation
- Change logging and monitoring of data processes
- Preparation of analytics data and management reports
TinAI Data Applications
TinAI Data can be used to integrate information, prepare training data, establish an analytics infrastructure, automate data flows and provide the information AI systems need.
This module is particularly valuable when an organisation's information is held across several applications, databases or files. TinAI Data connects these sources so that organised, reliable information can be delivered to the final system.