UXINDIA18 - UX in Big Data Analytics

18 min Ted Talk - Day 2

Transcript

2. 1 CONFIDENTIAL CONFIDENTIAL © Guavus, Inc. All rights reserved. UX in Big Data Analytics By: Paramjit Jolly Senior Manager Engineering
3. 2 CONFIDENTIAL Agenda • Big data – What, Who, Why • Our real examples of Big data applications • Our learning in Big data space • How to Simplify – Big data problems • Key skills you need to enter in Big data space as UX/UI • Future in Big data analytics
4. 3 CONFIDENTIAL What is Big data Four V’S of Big data • Volume • Variety • Velocity • Veracity
5. 4 CONFIDENTIAL Who creates Big data
6. 5 CONFIDENTIAL Who creates Big data Current State Big data
7. 6 CONFIDENTIAL Why - UX in Big data UX is the bridge between big data analytics and the end user.
8. 7 CONFIDENTIAL Our real world examples of Big data applications • Load Advisor • Marketing Reflex • GSI
9. 8 CONFIDENTIAL Load Advisor - Demo
10. 9 CONFIDENTIAL Marketing Reflex - Demo
11. 10 CONFIDENTIAL Guavus helping Customers
12. 11 CONFIDENTIAL
13. 12 CONFIDENTIAL Our Learnings in Big data space Life life of Guavus Big data analytics UI
14. 13 CONFIDENTIAL Our Learnings in Big data space • UX role is key in defining the product. • Involve UX from start – while defining the product. • Understand User & user needs • Dashboard design • It’s a key element – give the key insights which can impact business. • Data visualization • Don’t complicate visuals for no reason. • But’ Sometime you needs do out of box visualization– connecting multiple aspects of data. • Customer problem is changing in big data space so design should be adaptive, extendable & agile. • Power to user - capability to do data exploration. • UX of product is the key – differentiator in existing market tools
15. 14 CONFIDENTIAL How to simplify Big data Problems • Focus on decision • Build personas – understand the users • Key decisions - use case
16. 15 CONFIDENTIAL How to simplify Big data Problems • Summarize but don’t hide • Summarize key facts or analytics • Reduces cognitive load on user • Quick decisions • Deep dive into the data that was summarized • Build trust on your system
17. 16 CONFIDENTIAL How to simplify Big data Problems • Use domain specific terms • Learn the domain specific words • Use them in the appropriate places. • System is for users of that domain • User acceptance will increase
18. 17 CONFIDENTIAL How to simplify Big data Problems • Don’t sacrifice everything for simplicity • Big Data apps are for expert for a small, specific user base. • Explain more if needed, don’t hide to just make simple UI. • Handle more complexity - if it helps them do their job faster and better. • Usability tests and interviews help you define where you need complex UI. Simple Complex
19. 18 CONFIDENTIAL How to enter in Big data space as UX/UI My Last 6 Months Experience of Hiring UX people
20. 19 CONFIDENTIAL How to enter in Big data space as UX/UI • Good understanding of UX fundamentals • Data visualization skills • What data to show in what kind of visualization • Able to think out of box to create something new • Make some samples visuals to showcase • Learn about domain you are entering like Telecom, AI etc. study market products. • Industry needs deadly combination for UI & UX both. (Startup mode) • Problem solving skills • Sample Portfolio – showcase above capabilities
21. 20 CONFIDENTIAL Future of Big data
22. 21 CONFIDENTIAL Future of Big data
23. 22 CONFIDENTIAL Future of UX in Big data analytics • Big data isn’t just an important part of the future, it is the future. • Everything moving to Cloud, means everything generates data. • Simplification of big data platforms is a primary objective for almost all analytics software vendors. – Big scope • Everyone wants to explore big data, not only data scientist – ease of use for normal user – 400% increase by 2020 • UX folks had really bright future in Big data field.
24. 23 CONFIDENTIAL Questions ?
25. 24 CONFIDENTIAL Contact me: jollyp@gmail.com | jolly.paramjit@guavus.com Linkedin : https://www.linkedin.com/in/jolly/ Company : www.guavus.com Love to discuss - Any UX problem in Big data field. Presentation Credits: Guavus team, some UX internet links & pictures etc.