Predictive Modeling & Data Mining
Make the right Business Decisions with Data Predictions
Using predictive analytics with data derived from data mining is a powerful technique to assist estimate what may happen later in the organization, allowing executives and key decision makers to plan accordingly. It makes peering into the future more accurate and dependable than prior technologies. Almost every sector now employs predictive analytics.
Crafsol provides businesses with the technology to forecast various forms of customer behaviour and trends, as well as how to adequately prepare based on company demands. There is no doubting that the volume of web data is only going to increase. Data is being used by organizations in more ways than ever before. Predictive analytics has gained the backing of a wide spectrum of enterprises, with a global market expected to reach $10.95 billion by 2022.
Web data is becoming increasingly important. Capturing that critical online data may provide your sales and marketing teams with the additional insight they require to properly plan and maximize their outcomes. Crafsol helps marketing and sales succeed and develop by offering vital online data insights.
What Predictive analysis & Data mining can offer
- Valuable insight
- Increase competitive edge
- Predict trends
- Identify new business opportunities in time
About Service
Predictive modelling is a statistical approach for predicting future behaviour that is widely employed. Predictive modelling solutions are a type of data-mining technology that analyses past and current data to create a model that can be used to forecast future results.
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A versatile platform for Developing predictive analytics
Scalability
We automate data science and data processes. Models may be trained, tested, and deployed across many corporate applications in real-time. Extend standard data science capabilities across hybrid and multi-cloud settings.
Speed
We utilize pre-built apps and trained models. With cutting-edge open-source tools, we can help data scientists and business teams communicate and expedite model construction.
Simplicity
To handle the complete data science lifecycle, we use a centralized platform. Processes for development and deployment are standardized. We develop a unified framework for data governance and security throughout the enterprise.
Predictive Modelling & Data Analytics
Predictive analytics is another term for predictive modelling. In general, “predictive modelling” is chosen in academic contexts, but “predictive analytics” is favoured in commercial uses of predictive modelling. The successful use of predictive analytics is strongly reliant on having unrestricted access to large amounts of accurate, clean, and relevant data. While predictive models utilizing decision trees and k-means clustering can be quite complicated, the most difficult aspect is usually the neural network; that is, the model by which computers are trained to anticipate outcomes. A neural network is used in machine learning to uncover connections in extremely large data sets and to “learn” and recognize patterns within the data.
Predictive analytics & Data Mining Use Cases
Banking
Machine learning and quantitative technologies are used in financial services to forecast credit risk and detect fraud.
Healthcare
In health care, predictive analytics is used to detect and manage the treatment of chronically unwell patients.
Human resources (HR)
HR teams use predictive analytics to identify and hire employees, determine labour markets and predict an employee’s performance level.
Marketing and sales
Predictive analytics may be utilized in marketing campaigns and cross-sell tactics throughout the customer lifetime.
Retail
Predictive analytics is used by retailers to create product suggestions, anticipate sales, assess markets, and manage seasonal inventories.
Feature
Businesses utilize predictive analytics to improve inventory management, allowing them to fulfil demand while reducing inventories.