Tag: Business Analytics

Executive Programme in Data & Decision Sciences Consulting | IIT Delhi | 2021

Executive Programme in Data and Decision Sciences Consulting

 (Jan to Jun, 2021. Weekend classes. Batch size 35)

A classroom based programme under CEP, IIT Delhi for working professionals. Become an expert in data science and machine learning.

Download the Brochure now from IIT Delhi Website!

Continue reading “Executive Programme in Data & Decision Sciences Consulting | IIT Delhi | 2021”

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5 Great Ways Big Data can Help Small Businesses Thrive

Achieving success as a small business owner is no longer just about delivering quality service with a smile. Sure, these factors are still important, but in order to stay competitive and even grow your business in the long run, you need to crunch the numbers, gather valuable data, and put the insights into actionable reports. Nowadays, though, there is so much important data that you need to process on a daily basis, that doing it manually becomes an insurmountable task.

Continue reading “5 Great Ways Big Data can Help Small Businesses Thrive”

Courses @ IIT Delhi 2020 – EMP in Strategic Innovation, Digital Marketing & Business Analytics

Executive Management Programme

in

Strategic Innovations, Digital Marketing, & Business Analytics

Department of Management Studies,

Indian Institute of Technology Delhi

4th Jan – 7th Jun 2020, Classes on Weekends / National Holidays

Apply Online

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Set Up International Websites To Get More Online Business

In this day and age almost every business has gone online. This is because they can do their business beyond their local demographics and geo limits. However, doing business on a global scale is not easy especially when you have to reach out to people of different cultural and traditional background. All will have different needs, choices and preferences that you will need to cater to.

Continue reading “Set Up International Websites To Get More Online Business”

Impact of Corporate Social Responsibility on Reputation – Insights from Tweets on Sustainable Development Goals by CEOs

International Journal of Information Management, Volume 48, October 2019, Pages 39-52

Abstract
Social media had been extensively used for communication and networking purposes among corporates. Literature indicates social media platforms had also been used by the firms for building relationship with different stakeholders (i.e. customers, employees, investors and neighbouring communities). But there exists a gap in literature, whether social capital present on social media can be used for building corporate reputation (CR) in the society. Literature indicates corporate social responsibility (CSR) impacts CR. Therefore this study explores how CSR messages on social media impacts CR. For this study assumption was made that all the concerns and issues raised by Sustainable Development Goals (SDGs) are the social responsibilities of the CEOs. The study tries to explore this gap by analysing the tweets posted by two group of CEOs, i.e. CEOs in top 200 fortune companies and top 100 social influencer CEOs. Continue reading “Impact of Corporate Social Responsibility on Reputation – Insights from Tweets on Sustainable Development Goals by CEOs”

2019 EMP in Strategic Innovations, Digital Marketing, & Business Analytics | IIT Delhi

Executive Management Programme

in

Strategic Innovations, Digital Marketing, & Business Analytics

Department of Management Studies,

Indian Institute of Technology Delhi

5th Jan – 9th Jun 2019, Classes on Weekends / National Holidays

Continue reading “2019 EMP in Strategic Innovations, Digital Marketing, & Business Analytics | IIT Delhi”

Big data with cognitive computing: A review for the future

Abstract : Analysis of data by humans can be a time-consuming activity and thus use of sophisticated cognitive systems can be utilized to crunch this enormous amount of data. Cognitive computing can be utilized to reduce the shortcomings of the concerns faced during big data analytics. The aim of the study is to provide readers a complete understanding of past, present and future directions in the domain big data and cognitive computing. A systematic literature review has been adopted for this study by using the Scopus, DBLP and Web of Science databases. The work done in the field of big data and cognitive computing is currently at the nascent stage and this is evident from the publication record. The characteristics of cognitive computing, namely observation, interpretation, evaluation and decision were mapped to the five V’s of big data namely volume, variety, veracity, velocity and value. Perspectives which touch all these parameters are yet to be widely explored in existing literature.

Journal: International Journal of Information Management (Elsevier)

Authors: Shivam Gupta, Arpan Kumar Kar, Abdullah Baabdullah, Wassan A.A Al-Khowaiter

Download the article here at Elsevier.

5 Present-Day Applications of Artificial Intelligence

Artificial intelligence was officially founded as a discipline in 1956, and in the years since, it has experienced tremendous growth and development—allowing AI systems to do a lot more things in ways we could only just imagine in the past. Let’s take a look at some of the best applications of artificial intelligence in the world today.

Personal Tasks

Among the many applications of artificial intelligence these days, smartphone virtual assistants are definitely at the vanguard, since these are the types of AI people are familiar with the most. Examples of these are voice activated assistants like Siri on the Apple iPhone, Bixby on the Samsung Galaxy S8, and Cortana on Microsoft devices. As you may very well know, these personal assistants can perform tasks and services for the user, facilitating the use of device features that would take much longer to access without AI aid. These include reading emails and messages aloud, scheduling events, looking up and dialing contact details, performing internet searches, and other duties that were traditionally performed by actual personal assistants or secretaries.

In the future, smart personal assistants are likely to become more ubiquitous, especially in homes, where they can act as automation hubs for smart houses. There are already a few such AI technologies operating today, including the likes of Amazon Alexa on the Amazon Echo device, Siri on the Apple HomePod, and the Google Assistant on the Google Home device.

Healthcare

In a world that is slowly transitioning to value-based care—a healthcare delivery model where providers and compensated according to the quality of patient health outcomes—it is important for health payers, providers, and public health agencies to become more sophisticated when it comes to handling data. With the help of artificial intelligence solutions, it become possible for these organizations to sift through and analyze voluminous amounts of data, which they can then use to empower their policies and practices. What are the implications? Consider being able to detect healthcare fraud, reduce resource wastage, develop the best healthcare plans, improve population health, and even cure diseases. In short, health organizations are poised to benefit a lot.

Financial Services

The financial services sector is one of the most data-driven industries in the world, with financial organizations exchanging large amounts internal documents and customer transaction information on a daily basis. Because banks and other financial institutions are also confronted with numerous regulations and compliance standards, they should see to it that that they are not failing on their legal and institutional obligations.

By analyzing data with the proper artificial intelligence tools, financial organizations will be able to understand the risks, comply with regulations, and meet customer needs effectively. They’ll be able to perform specialized tasks, whether it’s building regulatory risk models or predicting and preventing criminal activities like fraud and money laundering.

Transportation and Navigation

Have you ever wondered how map services like Google Maps and Waze calculate the best routes from your location to a certain destination? Or how about the methods by which ridesharing applications like Uber and Lyft determine the price for your ride? If you guessed artificial intelligence and machine learning, then you are correct.

Google Maps, which acquired Waze from the Israeli company Waze Mobile in 2013, efficiently makes use of crowdsourced data from the latter in order to help commuters avoid traffic jams caused by roadwork, accidents, and other disturbances, while also providing estimated times of arrival. Uber, on the other hand, uses machine learning in its proprietary algorithms in order to predict which areas will have increased rider demands at which hours. This way, they are able to implement what they call surge pricing, a strategy in which ride prices are increased at certain locations and at certain hours in order to bring down rider demand while also encouraging more drivers to pick up riders from those locations.

Aviation

Aviation has always been an early adopter of AI technologies, and autopilot systems are one of them. Autopilot is a technology employed to control the flight path of an aircraft without constant intervention by a human agent. Although an autopilot system is not a complete substitute for human operators, it does help them significantly by allowing them to place their attention on other important aspects of aircraft operations, whether it’s monitoring weather conditions or reviewing and configuring instruments.

Surprisingly, autopilot systems have been in existence since the 1912, when the Sperry Corporation developed the first aircraft autopilot technology. Modern aviation AI systems, however, are much more advanced and are powered by computers—from coupled autopilot systems and full authority digital engine control systems to more recent developments such as digital cockpit assistants and next-generation autoflight systems that use machine learning to mimic expert pilots.

Without a shadow of doubt, artificial intelligence and machine learning will become more important in our daily lives as these technologies advance. What sort of challenges do you think AI will solve in the future?

7 ways how big data is changing marketing

Over the last few years, technological advancement has really changed the way marketing data is used. It has become more specific and marketers now focus on individual preferences instead of market trends. Historic action has paved way for a customized one-on-one engagement between the seller and the buyer. Gone are the days when people used to replace their mobile phones only after they stopped working. The younger generation replaces their android phones within 3-4 months after finding some new features in a newer model. Continue reading “7 ways how big data is changing marketing”