The growing infrastructural development in the sake of urbanization is evident today. On account of such huge demand from the infrastructure side, the hot rolled coils market has paced up inadvertently.
This company is US based, market leader in supply chain and logistics management of the hot rolled coils.
It has 100% contract performance rate by facilitating sophisticated pricing models. The astute process and risk management capabilities set the company ahead of its competitors in various parameters. In compliance with just-in-time delivery, the company maintains the record of consistent inventory engagement and improvements. This way the company has created a big hub in the US market.
Since the company is the market leader and doing very well in it's geography of operation, it gets orders every now and then. With such a vast involvement in multiple tasks, it generates a flood of data.
To proceed with, we did the exhaustive requirement gathering of the infrastructural set up of the organization. Post requirement gathering, we did the connectivity check and found that their source system (ERP System) was on public cloud whereas the reporting system was on-premise. The first challenge was to move the data from cloud to on-premise. To replicate the data, we moved forward with two approaches: -
Hadoop Platform:- Apache Kafka, Apache Spark, Apache Parquet
Programming Languages:- Python
Cloud :- private cloud
DATA LAKE :- Apache Parquet, Apache Spark SQL
DATABASE :- PostgreSQL, Oracle
CDC tool :- Debezium
BI/Search :- Superset, Elasticsearch
To arrive at the root cause of any issue involving cell studies, the ultra research-oriented work at the DNA level is required.
Our Client is one of the premier research institutes, aided by the Department of Biotechnology, Government of India.
Cell-culture, cell repository & immunology are some of the areas where the organization holds exceptional expertise.
The high-end results produced by this body after exhaustive research work has got immense relevance in the healthcare & pharmaceutical industry. The upgrading research techniques & methodologies adopted by this organization is paving new dimensions to enhance the output constantly.
Since the company is into the research task, many processes are in the pipeline that needs sequential execution. To ease and accelerate the process of tasks, the organization was looking for smart automation. The pain areas that needed quick mitigation were as follows:-
We initiated with a series of steps. The very first step was CTF Estimation followed by its assessment. After assessment, particle picking is done where the model are trained for more accurate results. The particle extraction process helps in obtaining stable particles. The 2-D Clustering helps in sorting out the bad samples from the good samples. To enhance the visualization, beautifier is deployed. After the creation of the stack subset, the 3-D Model process is initiated. The creation of intermediate resolution using best stack subset is part of the 3-D model process. The final step is the 3-D Refinement process that enhances the 3-D model result.
Platform :- Tensorflow/Keras
Programming Language :- Python
Model/Technique :- YOLO
Programming Suits :- CR-YOLO/Sphire