Enterprises need to adapt tech strategy to address complex business environment: Report

Mindtree’s annual report, Tech Beacon 2019, focuses on seven emerging technologies that will drive enterprises’ technology strategy in the next 12 months.

Mindtree

Mindtree has published the fifth annual edition of Tech Beacon, an annual report from Mindtree to offer technology guidance for enterprises. 

The report identifies seven key technology categories: application development, cloud computing, IoT, AI, conversational apps, blockchain and eXtended Reality (XR), and projects its impact on enterprises over the next year.

Tech Beacon identifies a need for organizations to adapt their IT architecture to address evolving business challenges. It also recommends the most important emerging technologies and tools for enterprises to invest in, experiment with or watch for future application (Invest, Experiment and Watch) based on the maturity & production readiness
 
“Today, with aggressive digital disruption proliferating, the global business environment is transforming faster than ever. It is therefore important for enterprises to better understand how emerging technologies offer a compelling value proposition to keep pace with this dynamic reality,” said Madhusudhan KM, Chief Technology Officer, Mindtree. “Tech Beacon offers technology guidance to enterprises based on the industry requirement, changing business dynamics, and anticipated technology evolution.” 
 
Here are some key recommendations from Tech Beacon:

 
Systems interacting with systems

· The challenge behind scalability in micro-services can be addressed with distributed architecture and service mesh due to its consistent discovery, security, tracing, monitoring and failure handling service.

· Reactive autonomic architecture should be at the top of chief technology officers’ priority list as it simplifies and improves the end user experience by predicting their needs in a complex, dynamic and uncertain business environment and avoids system failure in unplanned situations.
 
Turning Information into insights

· The role of machine learning is limited in the data harvesting process. Organizations use humans for manual tasks like data cleanup, outlier removal, etc. There is a need for integrating exploratory data analysis tasks as part of a processing pipeline.
·  Organizations should utilize Lambda and Kappa data processing techniques to generate useful insights from available data. Lambda offers a consistent pattern and a real-time view into the generated insight, storing the data and then generating the insight in the batch layer. Kappa is the next iteration in this evolution, generating insights as the data arrives within its ‘streaming layer.’
 
Interaction with Humans

·  Organizations are increasingly using conversational systems as a channel to enable machines to interact with humans. These systems offer Natural Language Processing (NLP) and integration capabilities in the IT environment, in addition to mobile and web. Organizations should use libraries like Rasa, Wit.ai, and Microsoft's LUIS, which provide core language processing capabilities and enable “human-like” conversations with existing systems.

·  Enterprises need a renewed architecture to deliver cognitive experiences to their customers, enabling systems to interact with users seamlessly. To enable these cognitive experiences, enterprises should explore computer vision capabilities and tasks such as recognizing objects and characters, combining/matching/analyzing images or video with product details, and even superimposing objects with three dimensional images on to live video. This enables machines to extract data from and understand the content of digital images and video.

· CTOs, while adopting machine learning and AI in their processes, should also carefully draw in boundaries of interaction and responsibility between humans and machines. Human intervention is often a better solution than one that’s fully automated, where machines have too much control.
 

Enterprises need to adapt tech strategy to address complex business environment: Report

Mindtree’s annual report, Tech Beacon 2019, focuses on seven emerging technologies that will drive enterprises’ technology strategy in the next 12 months.

Mindtree Jun 25th 2019

Mindtree has published the fifth annual edition of Tech Beacon, an annual report from Mindtree to offer technology guidance for enterprises. 

The report identifies seven key technology categories: application development, cloud computing, IoT, AI, conversational apps, blockchain and eXtended Reality (XR), and projects its impact on enterprises over the next year.

Tech Beacon identifies a need for organizations to adapt their IT architecture to address evolving business challenges. It also recommends the most important emerging technologies and tools for enterprises to invest in, experiment with or watch for future application (Invest, Experiment and Watch) based on the maturity & production readiness
 
“Today, with aggressive digital disruption proliferating, the global business environment is transforming faster than ever. It is therefore important for enterprises to better understand how emerging technologies offer a compelling value proposition to keep pace with this dynamic reality,” said Madhusudhan KM, Chief Technology Officer, Mindtree. “Tech Beacon offers technology guidance to enterprises based on the industry requirement, changing business dynamics, and anticipated technology evolution.” 
 
Here are some key recommendations from Tech Beacon:

 
Systems interacting with systems

· The challenge behind scalability in micro-services can be addressed with distributed architecture and service mesh due to its consistent discovery, security, tracing, monitoring and failure handling service.

· Reactive autonomic architecture should be at the top of chief technology officers’ priority list as it simplifies and improves the end user experience by predicting their needs in a complex, dynamic and uncertain business environment and avoids system failure in unplanned situations.
 
Turning Information into insights

· The role of machine learning is limited in the data harvesting process. Organizations use humans for manual tasks like data cleanup, outlier removal, etc. There is a need for integrating exploratory data analysis tasks as part of a processing pipeline.
·  Organizations should utilize Lambda and Kappa data processing techniques to generate useful insights from available data. Lambda offers a consistent pattern and a real-time view into the generated insight, storing the data and then generating the insight in the batch layer. Kappa is the next iteration in this evolution, generating insights as the data arrives within its ‘streaming layer.’
 
Interaction with Humans

·  Organizations are increasingly using conversational systems as a channel to enable machines to interact with humans. These systems offer Natural Language Processing (NLP) and integration capabilities in the IT environment, in addition to mobile and web. Organizations should use libraries like Rasa, Wit.ai, and Microsoft's LUIS, which provide core language processing capabilities and enable “human-like” conversations with existing systems.

·  Enterprises need a renewed architecture to deliver cognitive experiences to their customers, enabling systems to interact with users seamlessly. To enable these cognitive experiences, enterprises should explore computer vision capabilities and tasks such as recognizing objects and characters, combining/matching/analyzing images or video with product details, and even superimposing objects with three dimensional images on to live video. This enables machines to extract data from and understand the content of digital images and video.

· CTOs, while adopting machine learning and AI in their processes, should also carefully draw in boundaries of interaction and responsibility between humans and machines. Human intervention is often a better solution than one that’s fully automated, where machines have too much control.