Every company which aspire to become data-driven organization must own modern Data Platform.
Data Platforms are software applications or systems that are used to collect, store, process, and analyze large amounts of data. These platforms typically consist of several components, including a database for storing data, tools for cleaning and preprocessing data, algorithms for analyzing data, and visualization tools for presenting the results of data analysis.
The need for Data Platforms, Data Warehouses, Data Lakes, and other types of data repositories is driven by the increasing amount of data that organizations are generating and collecting. As businesses generate more data from a variety of sources, such as transactions, sensors, and social media, they need a way to store and manage this data in a way that allows them to access and analyze it.
Take advantage of our cutting-edge technology and make your data an asset. With TT PSC, you can easily organize, clean, and pre-process your data while also ensuring the highest levels of security and governance.
Data Analytics PlatformsVisualize data and create holistic reporting systems with Data Visualization and Reporting.
The main purpose of BI is to provide organizations with the information they need to make better-informed decisions. By using BI, organizations can identify trends and patterns in their data, make predictions about the future, and take action based on sophisticated reports that can be created upfront or generated on-demand based on user input.
Data visualization and reportingIn order to apply AI you must consider Data Science and Machine Learning Platforms.
The main purpose of data science and machine learning platforms is to provide organizations with the tools and resources they need to gain insights from their data and develop and deploy machine learning models. By using these platforms, organizations can collect and store large amounts of data, analyze this data to identify trends and patterns and develop and deploy machine learning models that can make predictions or take other types of action based on this data.An MLOps platform provides the infrastructure and tools needed to manage the lifecycle of ML models. This typically includes features such as version control for ML models, automation tools for building and training models, and monitoring and alerting tools for monitoring the performance of models in production.
By using an MLOps platform, organizations can automate and streamline many of the tasks involved in managing machine learning models. This can save time and effort, and reduce the risk of errors and issues with ML models. It can also help organizations ensure that their ML models continue to perform well in production, and enable them to quickly and easily update and improve their models.
Improve your business with end-to-end AI Solutions from Industrial, Supply Chain and Product Lifecycle areas
Our AI solutions offering is focused on most critical aspects of each potential business area, from product design enhancements, via manufacturing process improvements to supply chain, logistics and customer satisfaction optimization.
| Industrial Analytics | Supply Chain Intelligence | Product Lifecycle Intelligence |
| Anomaly Detection | Demand Forecasting & Warehouse Optimization | Change Management Optimization |
| Predictive Quality | Allocation & Replenishment | |
| Predictive Maintenance | Inventory Optimization | |
| Delivery Optimization | ||
| Fraud Detection |
Discovery of a wide range of Data Services we are offering to help businesses of all sizes succeed in today's data-driven world:
To become a data-driven organization, you must prioritize the collection, analysis, and use of data in your decision-making processes. This can be achieved through the following steps:
We understand that every organization has its own unique needs and challenges. We can help you in a variety of ways, and we provide platforms and services to drive better business outcomes. Easily find out if your data is ready for AI.
