Enterprises across the world are adopting big data Analytics technologies to identify insights, patterns and improve decision making. DEFTeam enables customer into Big Data, Advanced Analytics Offerings, and Data Sciences journey. Our Advanced Analytics Offerings or Data Sciences team helps companies in solving complex business problems using both structured and unstructured data.
All the models built with Big Data, Advanced Analytics Offerings can be deployed on-cloud, on-premise, in-Hadoop or in-database. Using Web services, we can help a customer in deploying real-time scoring for predictive modeling.
- Marketing Analytics
- Customer Analytics
- Anomaly detection
- Forecasting
- Customer Segmentation
- Unstructured data Analysis
- Recommendation
- Churn Prediction
- Click Stream Analytics
- Image Classification
DEFTeam leverages both open-source and proprietary tool for solving analytical problems. We also help organizations in selecting right set of tools based on the requirements.
Our Data Sciences offering helps organization in:
- Building Predictive Models
- Deploying Predicting models for batch and real time processing.
- IoT Analytics
- Integrate Analytics with Existing Business Intelligence tools.
DEFTeam provides corporate training on Open Source R, Python, Microsoft ML Server and Azure ML.
Trainings are provided by certificated professionals either on-site or on-demand.
DEFTeam partnered with a leading bank and developed web-based R Editor and converted their existing SAS code to Microsoft R script.
As part of this engagement, a Java based web application was build which utilized the APIs of DeployR using the below features available in R-Editor.
- Script Window
- Terminal Window
- Plot area
- Managing Projects
- Downloading and uploading files
- Scheduling of R Scripts
Multiple users were able to login into Microsoft R Server using browser which helped in the full utilization of the server capacity. Various scripts written in SAS related to data preparation, data visualization and predictive modelling were converted to R scripts using RevoScaleR library provided by Microsoft ML Server.
Market share and profits get eroded with increase in competition and commoditizing of generic products. Retail pharmacy analytics can help in understanding needs of customers and which products drive financial performance.
Retails pharmacy analytics can also help in figuring out which products are slow or fast moving. Slow moving product in one pharmacy could be fast moving on other pharmacy.
So, we need to build drug recommendation engine for each pharmacy so that MR can build their strategies accordingly.
Approach: Sales related data was provided for each pharmacy. Data also contained information for each drug, geography, MR etc.
After preparing the data recommendation engine was build using R.
Analytical solution for Call Center Analytics based on various KPIs across different categories.
TOP KPIs : This dashboard provides a comprehensive view of call center performance for Top management. To further investigate details, end users can drill down in other tabs.
Availability : This dashboard contains all the important KPI related to Availability along with trends. End users can drill down to into more granular details using Date, Location and Designation filters.
Efficiency : This dashboard helps the end user to assess the efficiency of a call center.
Time Distribution Analysis : This Dashboard includes survival analysis charts which assist in determining how long customers are willing to wait in queue.
myLOGISTICZ is a Supply Chain Management Analytics & IoT driven technology agnostic solution, which uses powerful visualizations to help improve key business areas. It is flexible to run on-Cloud or on-Premise using client’s existing technology & infrastructure stack.
Demand Forecasting : This report provides demand forecasting based on various algorithms. Algorithm with best accuracy gets plotted automatically.
Supplier Performance : Provides overview of supplier performance over period of time based on delivering parts on time.
Damage and Loss Analysis: These reports provides trends for various losses and damages for different warehouse across various loss categories and reasons.
Fraud Analytics : This dashboard helps in finding fraud related activities for different warehouses.
