Shamayita Acharya

In this day and age, you probably encountered a few topics about AI or Artificial Intelligence on the internet. You may have also experienced interacting with them in some business website with their chatbots. AI is not only exclusive to desktop and laptops, though. They are also available and are deployed in smartphones such as Siri and in homes such as Amazon’s Alexa. Additionally, they are also utilized in self-driving cars and delivery drones. With the widespread use of AI and how its applications are branching out to different industries, what can it do to User Experience or UX design? The Role of Current AIs in UX Design AI has plenty of benefits that improve how people usually perform a task. Moreover, it has already been deployed in the digital designing world that can benefit and improve the user experience. Here are some of the examples how AI has incorporated itself in UX Designing. TheGrid.io TheGrid’s concept was made in 2014 and spent the years in beta phase

Introduction Apache Hadoop YARN is well known as the general resource-management platform for big-data applications such as MapReduce, Hive / Tez and Spark. It abstracts the complicated cluster resource management and scheduling from higher level applications and enables them to focus solely on their own application specific logic. In addition to big-data apps, another broad […] The post First-Class Support for Long Running Services on Apache Hadoop YARN appeared first on Hortonworks .

At Exago, we are always looking for ways to further improve the application’s user experience. While these advances are most noticeable in major enhancements such as our newly-released dashboard designer and formula code completion, upgrades to client- and server-side performance are just as important. For Exago’s v2017.2 release, I was tasked with speeding up our client-side application and so became familiar with a number of performance improvement tools. Web technologies such as Flexbox, better in-browser performance profiling, and particularly jsPerf.com have helped us reach our usability goals. JsPerf is a free, open-source JavaScript benchmarking tool that encourages collaboration and sharing of performance testing. The website uses Benchmark.js along with an embedded Java applet to record execution times of JavaScript code snippets at a high precision. Benchmarks of many commonly used JS web functions have already been cataloged on jsPerf. Most of these tests show results from

The concept of a smart society has been around for a long time, but the progress we have seen towards achieving it in the last decade has really been a giant leap for mankind. For those of us who are unaware, the smart society which looms over us is the future of mankind. We are about to enter a phase where living smart is the baseline, and everything else just falls into the jigsaw to complement that lifestyle. In smart societies, we are blessed with smart cities that run through the application of smart accessories and smart buildings.  In smart societies, we have smart cars (also known as self-driven cars or autonomous vehicles). We expected a better flow of traffic with traffic management that is propelled through extensive and authentic data provided by these vehicles and analysed with smart algorithms (e.g. based on AI). The most prominent detail about smart societies as we know them now is the pervasiveness of the Internet of Things (IoT) at the smallest level. The implementat

The typical scenario of a customer calling up a customer service agent to answer a query is passé. The expectations of customers have risen with time, which requires the customer service agents to be available round the clock for any enquiry, complain and other information. As a result, enterprises are having to invest more into acquiring the adequate amount of team members and training to get the job done. The other possible solution is enterprise chatbots, which can make the 24/7 customer service a reality. These chatbots can provide fast solutions.With the help of Artificial Intelligence, they can perceive data well and give more accurate and personalised solutions. They cut costs of businesses and can do repetitive work. Not only do they keep their end users happy, but they also take off the workload from customer service counterparts, allowing them to concentrate on more complex tasks. 4 Impressive Chatbot Statistics According to a study by Gartner, by 2020, 85% of all cu

As data storage options become exponentially more accessible and simultaneously more complex, business owners and individuals are left to wonder where to store their sensitive data. Cloud storage services, physical backup drive manufacturers and off-site data storage centres are all competing for your data storage business. With high competition in the data storage services market, consumers have several excellent options for storing large and sensitive files today. Read on to find out where you should be storing your data among the plethora of data storage solutions available this year. Cloud-Based Data Storage Solutions There are several benefits of storing your data in the cloud. Whether your a business owner or an individual with lots of media, information and financial data to keep secure, then you'll appreciate the newer cloud-based storage solutions from companies like Amazon and Microsoft. Amazon's cloud storage solution, AWS, is a scalable, pay-as-you-go option for

Conversion rate optimisation is very important, but it is also a very imprecise science. The biggest challenge is that customer behaviour is constantly evolving. The practices that customers responded to five years ago may not be effective today. Marketers must use the latest tools and strategies to maintain a decent ROI. Predictive analytics models are highly effective, but they aren’t foolproof by any means. If you are planning on using predictive analytics to boost your online conversion rate, you will want to avoid making the following mistakes. 1. Be Wary of Your Ability to Understand Changes in Social Psychology at a Macro-Level Some experts attempt to use predictive analytics models to identify future fads or predict changes in customer behaviour. You need to be cautious with these models because they are notoriously unreliable. Even the most insightful predictive analytics model cannot account for unplanned variables. New events or product offerings can change customer

Each minute Google records 3.8 million different queries on its search engine, and Facebook as many "likes". For twenty years, new information technologies have increased the ability for businesses to collect, store, read, share and use the personal information of individuals. These activities have had many positive effects on the economy in general and some benefits for consumers, including greater personalization and better targeting of products and services. However, undesirable effects due to the knowledge of these data have also emerged, the most important being the one related to the invasion of privacy. Today, according to the annual barometer of the intrusion conducted for the fifth consecutive year by the Publicis ETO agency, nearly 78% of French people are inconvenienced by the fact that their information is collected and stored in databases. So what are the end-users' perceptions of the violation of their privacy in a Big Data environment? The Challenge

Small things often come in big packages, and this is something that the enterprise world is starting to realise as it continues to adjust to the Big Data paradigm. Data analysis must be conducted before making strategic business decisions these days, and this analysis is likely to come from one of the many tools provided by the Big Data industry, a sector expected to generate sales more than $187 billion next year. It is safe to assume that Big Data is here to stay; however, the enterprise focus is likely to shift towards reducing the size of the massive data sets being collected and processed for the purpose of perfecting the analysis and making even better decisions. The Problem With Big Data In the world of Big Data, one size does not fit all. Over the last few years, the enthusiasm of being able to collect infinite amounts of information has overshadowed analytical implementation. The problem with Big Data is that it has grown out of proportion for many businesses. There is n

My name is Yesha Vora. My early acquaintance to computer engineering happened when I was handed off a book called “Learning C” by my school teacher. I pursued a Bachelor’s degree in computer engineering from my hometown in India and completed my Masters in the United States. During my Masters program at San Jose State […] The post Women in Tech: Part 1 – Sr SQA Automation Engineer appeared first on Hortonworks .

As the world is progressing towards an age of development in the Internet of Things (IoT) and other aspects related to it, the concept of the digital consumer is on the rise. Consumers of today want to experience the feasibility that is promised through this method. From experiencing customer support resources that fulfil their needs to having a seamless experience across platforms, consumers really want to experience the full taste of this development in technology. The high expectations of the digital consumer have meant that Telcos now have to understand consumer preferences and give a solution that is aligned with the needs of today’s consumer. Not only is this expected of Telcos operating currently, but they can also increase their revenue streams.  One way to fulfil the needs of consumers flawlessly is through the use of the IoT and ecosystems. Today, I will talk in depth about how Telcos can use these concepts to their benefit. I recently had the opportunity to join a few othe

Nearly ten years ago, I was presented with an amazing opportunity. I was fortunate enough to join a team of three incredibly talented engineers to build a new platform. It would be responsible for handling the ever-increasing volumes of data that would be streamed through my organization. The platform would have to allow users to […] The post Introduction to Apache NiFi appeared first on Hortonworks .

In the past, when you required some work done, you would ask a local craftsman to do so. You were confident that you could trust the craftsman as it was a small village and any betrayal by him or her would result in loss of business. On the other hand, the craftsman knew he/she could trust you as when you would betray the craftsman it would mean that no one in the village wanted to work for you again. It was a system that worked very well. Unfortunately, with the internet turning the world into a small global village, that system pretty much disappeared. As a result, it has become increasingly difficult to trust someone you don’t know. What is reputation? To understand the challenges we face with reputation, it is important to understand what reputation is and how it is created. Reputation, or image, is a certain opinion about that person, company or device. A reputation is created over time, based on a set of criteria. It is a mechanism of control within societies and increasingly

Guest post by Boni Bruno. Originally published for the Dell EMC Community.  Many organizations use traditional, direct attached storage (DAS) Hadoop clusters for storing big data. As data requirements grow, organizations are finding traditional Hadoop storage architecture inefficient, costly, and difficult to manage. With most Hadoop deployments, as more and more data is stored for […] The post HDFS Tiering with Isilon and ECS without tiering policies appeared first on Hortonworks .

The International Consumer Electronics Show took place last week in Las Vegas, Nevada. CES is an annual trade show that showcases the newest products and technologies in the consumer electronics space. This year there were over 184,000 total attendees and 4,000 exhibiting companies. One of the hottest topics at the show was the connected car, […] The post How Big Data is Paving the Way for the Connected Car appeared first on Hortonworks .

If you’ve been following the direction of expert opinion in data science and predictive analytics, you’ve likely come across the resolute recommendation to embark on machine learning. As James Hodson in Harvard Business Review recommends, the smartest move is to reach for the “low hanging fruit” and then scale for expertise in heavier operations. Just recently we talked about machine-learning-as-a-service (MLaaS) platforms. The main takeaway from the current trends is simple. Machine learning becomes more approachable for midsize and small businesses as it gradually turns into a commodity. The leading vendors – Google, Amazon, and Microsoft – provide APIs and platforms to run basic ML operations without a private infrastructure and deep data science expertise. In the early stages, taking this lean and frugal approach would be the smartest move. As analytics capabilities scale, a team structure can be reshaped to boost operational speed and extend an analytics arsenal. How to implem

Once we start delving into the concepts behind Artificial Intelligence (AI) and Machine Learning (ML), we come across copious amounts of jargon related to this field of study. Understanding this jargon and how it can have an impact on the study related to ML goes a long way in comprehending the study that has been conducted by researchers and data scientists to get AI to the state it now is.  In this article, I will be providing you with a comprehensive definition of supervised, unsupervised and reinforcement learning in the broader field of Machine Learning. You must have encountered these terms while hovering over articles pertaining to the progress made in AI and the role played by ML in propelling this success forward. Understanding these concepts is a given fact, and should not be compromised at any cost. Here we discuss the concepts in detail, while making sure that the time you spend understanding these concepts pays off and that you are constantly aware of what is happening d

Many government bodies, regulators, investors and banks see Bitcoin, or even the whole cryptocurrency market, as a speculative bubble. Some say it is a fraud, while others speculate that it will continue to rise in 2018. Earlier, I wrote an article why I believe that Bitcoin will fail. Not because it is a fraud, but because it is flawed. Despite my belief that Bitcoin will eventually fail, blockchain and some, not all, cryptocurrencies will likely reach mass adoption and bring significant change to how we run organisations and societies. Since the innovation of blockchain and cryptocurrencies is too important, I do not believe that considering banning cryptocurrencies is a solution as is now being considered by multiple countries. Cryptocurrencies are a completely new way of doing business, raising money, transferring money, making transactions etc. Bitcoin is only nine years old, and as such, we are still learning how the underlying technology, blockchain, works; how we should deal

Happy New Year! We have been looking back at some of the great achievements of the past year and one thing which really stands out is the important contributions we have had from Women at Hortonworks. We have women engineers contributing to Hortonworks products in various different ways – be it in engineering, customer support, […] The post New Series: Women @ Hortonworks appeared first on Hortonworks .

The value of data-driven Customer Value Management or CVM cannot be underrated. Data and other algorithms/analytics that shape data are an imperative part of customer value management in a telecom company. With enhanced customer expectations, it is up to the ability of telecom companies to provide customers with a seamless experience and to also ensure that they help boost revenue in the process.  To understand this concept in a more functional manner, I recently interviewed the chief of CVM at Mahindra Comviva, Amit Sanyal. With so much on hand to discuss, I got to the crux of the matter straight away and asked Amit about the pillars he considered to be important for a customer value management program being driven by analytics.  The prodigy responded to my questions by commenting that all methods of CVM being driven by the force of analytics should be dedicated towards these three pillars.  Analytics themselves have an important part to play, which is why they form the first

Without any doubt, IoT is improving the quality of our lives every day. More companies invest in IoT solutions in order for their business to run smoothly, and more people invest in technology that helps them save time and make their lives easier. If you are one of the people who want to start building IoT solutions, you should ask yourself a very important question: how much does it actually cost? Validate Your Idea Before talking about the actual costs of building the IoT solution, you have to make sure that you have a target audience for your idea and also build a minimum viable product, in order to decide whether it’s worth it or not. First of all, it’s very important to study your competition, to search for similar solutions that already exist on the market and figure out a way to make your product stand out and bring something different in the game. Maybe you could build a website to see customer response. The next step would be to create a PoC (Proof of Concept), which is

Stories are how people make sense of the world, so it follows that they’d also be our way of making sense of data. As much as technology can facilitate data storytelling, it cannot (yet) perform the pivotal step of placing data into the human context. That’s our job, and we’re really good at it. We’re such natural storytellers, in fact, that most of us already use a story format for presenting information. Take the standard scientific research paper format. After the title and authors (our main cast of characters), we get a summary of the story in the article abstract. It’s like one of Shakespeare’s spoiler-laden prologues, a quick preview of what’s to come. After that comes the Introduction, complete with the scientific problem and research question that incites the story’s action, the experiment itself. The Materials and Methods sections chronicle the heros’ journey as they conduct the experiment, and the Results and Discussion sections are when we find out how they fared. Beginnin

The fast-changing, uncertain and ambiguous environments that organisations operate in today, requires organisations to re-think all their internal business processes and customer touch points. In addition, due to the availability of emerging (information) technologies such as big data, blockchain and artificial intelligence, it has become easier for startups to compete with existing organisations. Often these startups are more flexible and agile than Fortune 1000 companies and they can become a significant threat if not paid attention to. Therefore, focusing purely on the day-to-day operation is simply not and organisations have to become innovative and adaptive to change if they wish to remain competitive. The Paradigm Shift The key characteristic of these new startups is that they are, at its core, a data company, regardless of the product or service they offer. Companies such as Google, Facebook, WeChat or Amazon have long understood the importance of data, but, unfortunately, m

A new year is upon us, bringing refreshed optimism and new resolutions for many looking to the 12 months ahead. I’ve spent the holiday break reflecting on our past year and wanted to take a moment to share with you the tremendous confidence I have for our company and what we can achieve in 2018. […] The post 2017 Year In Review appeared first on Hortonworks .

By: Balaji Ganesan, CEO of Privacera How to leverage data discovery, control, anonymization and monitoring using Privacera, Apache Atlas and Ranger Data is growing in data lakes, so are security and compliance risks. These risks stem from storing and processing sensitive data. Forrester defines toxic data (its definition of sensitive data) as a combination of […] The post 4 essential steps for managing sensitive data in your data lake appeared first on Hortonworks .

Open strategy is the decentralisation of strategy formulation across, previously excluded, internal and external stakeholders. Traditionally, companies focused on control and ownership of an organisation’s assets to ensure competitive advantage. However, this focus on control of resources is no longer the key to success. In today’s data-driven societies, knowledge, i.e. data, is widespread and easily accessible and organisations are increasingly turning into data companies. Access to this knowledge can fuel innovation, especially when it is used to embrace external ideas and data and when these insights are combined with internal R&D. This enables organisations to find new opportunities, develop a new business model and remain competitive in this digital age.  The process of open strategizing is possible thanks to the plummeting costs of communication and the availability of new technologies such as big data, blockchain and artificial intelligence.  These technologies allow organ

IoT, the Internet of Things, has been a buzzword for the past five years. Literally everyone across all industries – business executives, line of business owners, operation staff, mechanical engineers, even retail marketers – has been eyeing the benefits and market opportunities IoT initiatives can bring. Yet there are so many points of view on […] The post Applying Big Data Streaming Analytics in the Real World appeared first on Hortonworks .