Qubole provides a Big Data on the cloud service. The main idea behind the product is to make data-driven insights easily accessible to anyone. The platform is industry’s first autonomous data platform which self-manages, self-optimizes and learns to improve automatically and as a result delivers unbeatable agility, flexibility, and TCO.
I head the design group at Qubole and am responsible for formulating the design strategy and vision, apart from being more hand-on and designing key features. My ability to see the big picture while dwelling in the details allows me to execute tasks at any level of detail, guide the team towards the goal, set priorities and achieve business objectives with limited resources.
Qubole Data Service Platform
Since I joined my main task has been to upgrade the user experience of the platform to be more simple, efficient, modern and clean.
Given the small team size, it was important to strike the balance between fixing the current interface and introducing new features. In order to address this, I quickly identified the major problem areas and divided them into 2 buckets: low hanging high impact fixes and long term strategic upgrades. This allowed for accommodating small changes in the sprints while focussing on working on new features.
An example of incremental changes leading to a new better experience is the Data Science experience,
I also designed a number of features around intelligent agents like data discovery previews, data insights and data structure recommendations,
Oracle cloud provides the most comprehensive set of services and applications to the customer across the three layers, SaaS, PaaS and IaaS. I have been working with the PaaS and IaaS side of things since the very beginning and have been involved in a lot of key design decisions including selecting the design direction, visual language and defining cutting edge enterprise UI.
I also designed and continue to evolve more than 10+ service management consoles including Database, Java, Compute and Big Data. During the design phase, I greatly reduced the complexity of booting up, running and managing instances, letting users create instances 3.7x times faster than competitors. This was a competitive advantage and highlighted multiple times during Keynotes and product launches.
A New Design Language
When I joined, the cloud was just starting. The UI was primitive and was built on legacy designs templates. My earliest work included redefining the UI to brainstorms not only the enhanced feature set but to have a modern look and feel and a consistent design language that would be used for all new services that get on-boarded.
There was a lot of work involved including market research, competitor analysis, low fidelity mockups and high fidelity prototypes through which we came up with the next generation enterprise UI based on the principles of simplicity, clean, free flowing, engaging and progressive disclosure.
This evolved into a company wide initiative and is being used by the entire company to design new services. See samples of the latest on altaui.com
Evolution of Cloud UI
Alta App Demo
To see the live demo of an app following Alta patterns, click the image below
Other notable works
Trial Flow redesign (increasing signups by 27%)
User Assistance Features (company wide initiative to help users getting started and obtain in-context help)
Wolfram|Alpha is a computational engine which returns direct results to a query rather than a bunch of links. When launched in 2009, it was one of a kind platform and got some rave reviews. It is fairly popular in the academic community as well as for casual internet users. It is available on the desktop as well as on mobile.
Wolfram Alpha App
I worked on the Mobile part of Wolfram|Alpha. Apart from the main Wolfram|Alpha(WA) app, where I designed a host of features including the Image as Input feature, where a user could upload an image from their device and perform a set of image processing operations on the image. Below is a flow diagram I created to outline the functionality.
Also, as part of the partnership with Apple I worked on the free WA app to work with Siri. The app was a stripped down version of the full app and had limited functionality. The idea was to allow users to get more details of an answer than what Siri could provide while at the same time making the free app useful for other non-Siri users.
I also designed 30+ mobile applications for different domains including mathematics, science, personal assistants and professional assistants. Some of these apps have been in the top 5 of their respective categories and regularly featured by Apple in their App Store. The key to developing so many apps in such a short period was to design the apps in such a way that they could be standardized into templates for other apps of the same category to use.
The development of these apps and their restrictions on user input, lead us to master the science of designing suitable keyboards for each one of them. As trivial as this may seem, design for some of these keyboards was very challenging. For example consider the chemistry app where a whooping 108 elements needed to be put on a single iphone keyboard!
Mathematica (M-) is a mathematical computation software, used for research and development purposes. It is widely used in industry, research and academia but is a heavy desktop software. In order to make Mathematica available to more users, a version running in the cloud was necessary.
Research, brainstorm and design potential use cases, actions, features and functionality for a cloud version of Mathematica.
Provide a light weight way for users to try Mathematica. No installations.
Provide a better way for users to access Mathematica through mobile devices.
Provide a good way for users to share their Mathematica output with others.
Motivation and Users
The motivation for the project came from the fact that we saw a steep increase in the use of demonstrations which is a light weight consumable format of Mathematica. A number of users wanted to create these demonstrations quickly and on the go without having to download a heavy desktop application. We therefore started building a cloud version of M-.
We realized that we had a good opportunity to target not only new users who have never user M- before but in a way support the long time users of M- by utilizing the cloud aspects of sharing and collaboration.
This was also an opportunity to innovate by leaving behind the constraints of the desktop version (including compatibility to older versions). We started adding a number of features that would cater to the new users including code completion, predictive interface(patent pending) and starting points.
Mathematica(M-) had behind 25 years of development experience and there were many features which the UX team was not aware of. We started with a survey of the features in M- and tried making sense of features which were relevant to the cloud version.
We also did a number of competitive reviews of primary and secondary systems to get an idea of what is out there and what features are other systems providing.
Next up I started prototyping the overall look and feel of the system, carefully iterating after each team review to get the best ideas forward. A number of times the prototypes required modification as the current technology could not support these. After this each feature was detailed to specify the intricate interactions. These were then passed over to design and development for implementation.
With increasing emphasis on growing environmental degradation and with more and more people becoming environmentally conscious, there is a need for a system which can address both the trends. We developed a system which is based on the iPhone and enables users to monitor their environment affecting activities thereby reducing their adverse effects. All this, in turn, leads to lower personal impact on the environment and also encourages other people in the network to adopt such practices. Footprints as we call it, is therefore a smart application on a smart platform for smart people.
We started by identifying our core audience where we interviewed 8 users to understand the users’ understanding and behavioral thoughts about environmental degradation.
We realized that even though people say that they want to be environmental conscious but are not. This is due to the fact that they just don’t know how to do it, how much they can commute in their own vehicles, how much they are already saving the environment, what is the best way of commuting, and lack the motivation factor to take the little complicated solution.
Our survey had overwhelming and satisfactory results- 216 complete responses, 100 partial responses. We came up with a set of research questions, mainly targeting towards environmental degradation concerns, commuting ways and understanding about the environment concerns. From the survey it was clear that,
1) 56.4% of our target users have “Somewhat knowledge” about the effects/concerns of environmental degradation,
2) 76.14% of our target users will be ready to walk / take public transport/ carpool to save the environment.
3) Nearly 80% of our target users did not know any tool that can identify their impact on the environment
4) 73 respondents ranked “Commuting” as their first choice in which they can help to ensure a stable climate for future generation.
Three main user personas
1) Environment conscious people who actually care about the environment and would definitely use our product even without expectation of rewards.
2) Users with free attitude who are only concerned about their personal and social lives. The application will provide for functionalities to connect to their online social networks and create a prestige. These will act as rewards which will motivate users to use the application.
3) The third group of users is conscious in some way about sustainable living but is not aware of how they can be environmentally friendly. The application has specific feedback systems of health, money etc to show how sustainable they are.
The development followed a learner centered design process where the needs and goals of learners are emphasized. We heavily realized on data gathered through Learner Interviews and Survey to ideate the final design. According to our survey, nearly 80% of our target users did not know any tool that can identify their impact on the environment.
We therefore concluded that our app should appeal to our target users, by providing them
More knowledge on our environment – Facts, numerical evidence and clear visualization.
Different modes of transport for a specific route – Public transport/Car pooling and walking.
Footprints important features
Footprints was made with focus on the following: (Full Report)
Scaffold and Personalization (Smart knowledge)
Socially networked (The power of group)
Facilitate understanding by using facts and visuals (Multimedia learning)
I worked at the Synthetic, Perceptive, Emotive and Cognitive Systems (SPECS) group at the Universitat Pompeu Fabra, Barcelona, Spain during the summer of 2007. The project involved integration of bio-feedback of stroke patients into the Virtual Reality based Rehabilitation game. Two main feedbacks of Electro Cardio Gram (ECG) and Electro Dermal Response (EDR) were recorded using mobile bio-sensors. The main purpose of recording these was to adjust the game difficulty levels based on the patients bio systems enabling real time adaptation of the game to accommodate for fatigue and disinterest.
About Rehabilitation Gaming System
The Rehabilitation Gaming System (RGS) is a novel and highly innovative ICT Virtual Reality (VR) tool for the rehabilitation of motor deficits of the upper extremities after a brain lesion due to stroke. The system deploys an individualized and specific deficit oriented game training that combines movement execution with the observation of a correlated action by virtual limbs that are displayed in a first-person perspective. The RGS is based on the neurobiological considerations that plasticity of the brain remains motor areas affected by stroke remains throughout life and can thus be utilized to achieve functional reorganization of areas affected by stroke by means of the activation of secondary motor areas such as the so called mirror neurons system. As a multi-level adaptive tool, the RGS provides a task oriented game training with individualized graded complexity. Additionally, the system retains qualitative and quantitative information of the performance of the subject/player during the tasks, hence allowing for a detailed assessment of the deficits of the patient player and their recovery dynamics. The RGS approach is currently being evaluated in a randomized clinical studyand the initial results with 14 patients have demonstrated positive impact.
The RGS platform
Rehabilitation Gaming System set up
Virtual Reality tools (graphics, game design, game engine Unity…)
Monica S. Cameirao, Sergi Bermudez i Badia, Kumar Mayank, Christoph Guger, Paul F.M.J. Verschure (2007). “Physiological Responses during Performance within a Virtual Scenario for Rehabilitation of Motor Deficits”, PRESSENCE, Barcelona, Oct’07.
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