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Technology | Big Data and Analytics

Blog Category Listing

Data Quality
346
The blog aims at providing an insight as to why Data Quality is crucial for Industrial manufacturing segment talking about three major reasons in detail, and how we at HCL-ERS-Technology Office have addressed it.
Cognitive Solutions
6,644

Feb 01, 2019

Cognitive Solutions Powering Data Marketplaces

Venkata Krishna C Global Solutions Lead - Data and Analytics

Digital data ecosystems are undergoing a paradigm shift. We need to adopt a Data Fabric approach to make data more accessible and actionable across the enterprise. Data marketplaces in a cognitive world don’t have to simply be “one stop shops” but...
Future Testing
657
Next Generation Technologies like Cloud computing, AI, robotics, big data, and analytics have substantially impacted the way QA and testing are performed. Digital disruption is forcing organisations to innovate as the delivery cycle time is...
Customer Experience
553
The centuries-old utilities model is declining as quickly as digital technology is advancing. First, smart grids began to monitor home-energy usage, generating a massive volume of data-driven insight. Then smart devices allowed customers to control...
Bi
1,373

Nov 28, 2018

Data Analytics – Self Service BI Journey

Deepak Kansal SENIOR TECHNICAL SPECIALIST

Utilities have Big Data and it is a huge thing in utilities to analyze those data sets and patterns to really understand there customer behavior pattern, changes in business due to weather, enhance their customer satisfaction ratios, and enhance...
Big Data
3,440

Nov 28, 2018

Big Data & Analytics in the Energy & Utilities industry

Amit Handoo CLIENT PARTNER & REGIONAL SALES DIRECTOR (US)

The energy and utility industry typically comprises power plants generating electricity, transmitted over long-distance transmission lines and then finally supplied over distribution lines to residences and businesses.
The energy and utility...
Big Data and Analytics
716
India faced one of the major blackouts in July 2012. The entire northern half of the country was devoid of electricity for two full days. More than half a decade later, whereby India now ranks as the sixth largest economy and third largest producer...
Bigdata
296
No sector can claim to be as crucial to customers as the utility sector. Simple reasons: they are responsible for the most essential ingredients of our modern life and eventually our existence. But no sector can also claim to be so slow in...
Open Innovation
312
A new generation of users is fast emerging; a customer demographic that is pushing financial services industry to change itself exponentially at a pace never experienced before. Meet the Gen Z, the first time bankers/users who are now joining the...
Covid -19
284

May 05, 2020

Is COVID-19 the watershed moment for Artificial Intelligence?

Ved Parkash Pati Business Manager, Digital & Analytics

Technology has seen several advances over the last decade, with developments in AI particularly showing promise of a more sustainable world. As we deal with the wide-ranging ramifications of the COVID-19 pandemic, we must look toward technology,...
Data driven decision making in the banking industry
939
In today’s banking landscape, business is driven by data. Data provides valuable insights for businesses to focus on key areas that need valuable resources such as people and money. 
Future Testing
657
Next Generation Technologies like Cloud computing, AI, robotics, big data, and analytics have substantially impacted the way QA and testing are performed. Digital disruption is forcing organisations to innovate as the delivery cycle time is...
Role of Patient Sentiment Analysis during Pandemics
84

Jul 24, 2020

Role of Patient Sentiment Analysis during Pandemics

Shama S Pillai Associate Business Manager, Digital & Analytics

Patient Sentiment Analysis is a text analytics or data mining process that is engaged to understand patient emotions and clinical care experience. It provides deep insight into the patient care experience or treatment experience, helps reduce costs...
Data Analytics Game
1,925
How can we use machine learning in the insurance industry? Machine Learning could change the dynamics of the insurance industry sector. As an essential tool for insurers, it could help in improving underwriting, pricing policies and detecting fraud.
Wildlife Poaching
453

Jul 20, 2020

Protecting the Indian forests using Internet of Things

Subir Dhar Director & Business Development Head, APAC, IoT WoRKSᵀᴹ

Indian forests have always been under pressure, but in the recent years, it has been more so. While the coverage has grown per the ISFR 2019 (Indian State of Forest Resources), protecting the forests has never been easy. In a recent conversation...
Automation
366

Jul 29, 2019

Implementing Process Automation at the Right Time

Bhavdeep Singh Sethi AVP & Head Intelligent Automation Practice

The constant evolution of smart technologies and changing customer expectations has irrevocably transformed the business landscape. Artificial intelligence (AI), machine learning (ML), and analytics have fundamentally changed business processes and...
cobots
624
Organizations, today, are to adopting new innovative technologies to stay ahead of the competition. One such technology is collaborative robots (cobots), which help manufactures learn about the benefits of sharing the work space by humans and robots...
Artificial Intelligence
1,608

Dec 26, 2017

Master or Slave? The role of Artificial Intelligence

Vijay Guntur Corporate Vice President - ERS HiTech and Communications

AI Assistants are the go-to things today. People from all age-groups are taking to AI assistants in a big way to get things done. The more we use AI assistants, the better they are getting at their job.AI and related technologies will play a big...

Financial Services Personalization - Improving Customer Experience
HCL Marketing | April 26, 2019
192 Views

The issue of relevance in today’s era of instant gratification is remarkably pronounced as consumers are swamped with messages, most of which are off target. Across sectors, including the financial landscape, personalization—or reaching customers with tailored offerings at the right time—promises to address this issue.


Artificial Intelligence in Tech Industry
Sandip Bhattacharya - ASSOCIATE VICE PRESIDENT SAP Practice | April 8, 2019
256 Views

There are many concepts within the domain of artificial intelligence (AI), including machine learning (ML), deep learning, neural networks, natural learning processing (NLP), virtual reality (VR), Augmented Reality (AR), LSTM, and a few others. All of these deal with a vast amount of data in various shapes and forms - sound, image, video, electrical pulses, temperature, pH values, viscosity, biome markers, structured and unstructured data, and so on. Various techniques (like modeling) are used to process such data or a combination thereof using oversimplified as learning and scoring. AI is enabling facial recognition on your phone. Conversational AI is reducing the tactile footprint of human interaction, creating increased “naturalness” in ever increasing user surface area. Advancements in AI is transferring cognitive burden from user to the device. We are experiencing AI every day in some shape or form.

Edge computing puts low-level compute power in front of end devices, rather than sending all the data to a centralized hub. Instead of sending terabytes of data generated by an F1 car to a central server, each device (like tire pressure sensor) has small compute capacity and sends only relevant data to the next sensor or the central server. LSTM, on the other hand, handles large chunks of data by breaking into smaller relevant pieces with the ability to forget and pass-on.


Role of IoT and Data Mining in the Tech Industry
Saravana Nallakamu - SAP Digital CX Practice Lead – North America | April 8, 2019
746 Views

The Internet of Things (IoT) is the network connecting the world of tangibles to that of the intangibles, that is, a network of physical objects connected to the software cloud. With the increasing popularity of IoT, new solutions are designed using IoT which have an overwhelming amount of data pouring from all directions. Data mining algorithms are being developed to tackle these problems. With the smartphone revolution, app developers needed a smartphone platform like iOS and Android created by Apple and Google. Similarly, in the case of IoT, tech giants have been expected to set the protocols, infrastructure, and an established framework for the future development of IoT and data mining techniques.