In its quest to offer financial freedom to people, Intuit is home to products that include TurboTax, QuickBooks, Mint, Credit Karma, and Mailchimp. What makes all of these products special is that they have successfully integrated AI and data on the side of their customers.
Analytics India Magazine brings the list of leading analytics and data science products for the year 2020 that have positively impacted businesses across the globe, helping them make decisions. To source the best 10 products, we reached out to more than 25 companies. Ranging from serving financial sectors to manufacturing, retail, solar and other industries, these products have made a significant impact on driving business value for the companies.
_Please note that this is not a ranking and the list is in no particular order. _
Cora Finance Analytic by Genpact is a comprehensive and persona-based financial analytics suite that enables data-driven decision making for finance professionals across all business units and functions. It aims at driving faster business outcomes by augmenting the evidence-based decision making cycle through Robust Data Foundation Layer, Advanced Analytics, Data Science Application, Domain Expertise and Smart Processes. It is built on a domain-centric data platform and can do real-time and API-based integration, including semi-structured and unstructured data.
**Key Differentiation Factor: **It is a technology platform agnostic and can be easily embedded into clients’ business workflows in any production environment — On-Prem, Cloud or Hybrid.
**Client, Sectors and Geographies Served: **It is being used by over 25 clients across sectors such as hi-tech, manufacturing and services, consumer packaged goods and retail. It serves across geographies such as the US, Europe, Asia, Australia.
About the Company: A global professional services firm, Genpact drives digital-led innovation and digitally-enabled intelligent operations for clients guided by deep experience in data and analytics. Headquartered in New York, it operates in more than 25 countries, accelerating the digital transformation to create bold, lasting results.
Working with the Renewable Industry (right now only Solar), Prediction by Quadrical AI helps companies maximise their returns on solar fields by assisting them in predicting with much higher precision exactly how much energy they will produce. It also points out faults, fissures and failures so they can be fixed. Using AI, they can track degradations to turn unplanned maintenance to planned maintenance. The platform further keeps learning and improving with time, reducing maintenance costs, and allowing for greater Return-on-Assets for the Solar companies.
Key Differentiation Factor: With Digital Twin technology, it aims to build an identical digital twin of the plant to make it an energy-efficient world.
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For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.
“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.
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COVID-19 has upended almost all businesses, and one of the worst-hit sectors is customer service .
On the one hand, anxious and emotionally-charged customers are calling companies night-and-day to make travel cancellations, ask for refunds, inquire about bill payment extensions, and so on. Naturally, the volume and intensity of calls have sky-rocketed, leaving **customer support ** teams to fend for themselves. Additionally, the lack of proper infrastructure is making things worse for the team and the company at large. The logical solution?
It would be fair to assume that the pandemic is _forcing _ companies to move towards online support such as the use of AI chatbots , live chat, etc. – a great move, in my opinion. In this blog, we will look at the top-5 ways to enhance customer service for support agents working from home by using chatbots. Let’s jump right in.
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I loved to work as a scientist. There is a deep feeling of completion and happiness when you manage to answer why. Finding out why such animal would go there, why would they do this at that time of the year, why is that place so diverse… This applies to any kind of field. This is the reason why I want to advocate that if you are a scientist, you might want to have a look at what is called Data Science in the technological field. Be aware, I will not dwell in the details of titles such as Data engineer, data analyst, data scientist, AI researcher. Here, when I refer to Data Science, I mean the science of finding insights from data collected about a subject.
So, back to our **_why. _**In science, in order to answer your why, you will introduce the whole context surrounding it and then formulate an hypothesis. “The timing of the diapause in copepods is regulated through their respiration, ammonia excretion and water column temperature”. Behaviour of subject is the result of internal and external processes.
In marketing, you would have to formulate similar hypothesis in order to start your investigation: “3-days old users un-suscribes due to the lack of direct path towards the check-out”. Behaviour of subject is the result of internal (frustration) and external (not optimized UE/UI) processes.
Although I would have wanted to put that part at the end, as for any scientific paper, it goes without saying that your introduction would present the current ideas, results, and hypotheses of your field of research. So, as a researcher, you need to accumulate knowledge about your subject, and you go looking for scientific articles. The same is true for techs as well. There are plenty of scientific and non-scientific resources out-there that will allow you to better understand, interpret and improve your product. Take this article, for instance, Medium is a wonderful base of knowledge on so many topics! But you could also find passionating articles on PloS One on Users Experience or Marketing Design and etc.
2. Material and Methods
As a Marine biologist and later an Oceanographer, I took great pleasure to go at the field and collect data (platyhelminths, fish counts, zooplankton , etc…). Then we needed to translate the living “data” into numeric data. In the technological industry, it is the same idea. Instead of nets, quadrats, and terrain coverage, you will setup tracking event, collect postbacks from your partners and pull third-parties data. The idea is the same, “how do I get the information that will help me answer my why”. So a field sampling mission and a data collection planning have a lot in common.
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