Data Anlytic Training Center in Noida

Posted by aashibali on March 20th, 2020

Data Anlytic Training Center in Noida ;- if Data is the new oil, then AI and Automation is the new industrial revolution. Be it your Big Data & Analytics code, architecture or as complex as AI models, a lot of automation, orchestration and optimization is required for your particular needs.

However, this can be an issue due to various challenges and expertise issues. Conventional methods require data analysts and developers to spend a lot of time and manual effort. Reducing the costs associated with automation engines allows companies to utilize their resources without the prohibitive costs. Using technology solutions to improve big data anlytics platform efficiency and automating code generation is the proven way to reduce those costs.

Code review and automation

As Big Data and AI technology continues to mature, organizations face issues of instability of their big data analytics and AI systems. The instability is due to lack of code quality and lot of processes which are done manually. This can be improved by reviewing the existing code and improving it by following the best practices. All this done manually is fine, but given the volume of code and need for faster agile development, organizations should look out for a point and click tool for reviwing their code and getting instant report to fix them as soon as possible.

Apart from coding practices, lack of proper training and deficiencies of algorithms make the AI models unusable or inaccurate. Accuracy and predictability of Models can be improved with deep learning and in depth understanding. In depth undersanding is in terms of tuning the algorithm paramaters, applying various algorithms for the same dataset, also doing hings like cross validation, ROC curves, etc. This comes with extensive R&D experience.

Infrastructure and Architecture improvement

The landscape of Big Data Analytics and AI keeps changing every now and them. Organizations are mostly late to adopt the latest available tools and techniques. This leads to depreciation loss and competitive backwardness. This gap can be bridged by improving the infrastructure and the data architecture by integrating latest state of the art systems.

Platform configurations should not be kept as default but should be tuned according to the hardware infrastructure being present for the organization.

DevOps automation

B - 85, sector- 64, Noida, India.                     

E-47 Sector 3, Noida, India.        

+91 - 8802820025

0120-433-0760

+91 - 8810252423

012 - 04204716

EMAIL: info@webtrackker.com