Analyticon is an Amazon-wide Analytics conference dedicated to the fields of Business Intelligence, Data Science, and Data Engineering. Analyticon focuses on real-world architectures, analytical tools, data pipelines, and practical examples of data science.
The Analyticon Viz Contest is a Amazon-wide data-visualization competition where Amazonians express creativity in the field of analytics by sharing exceptional visualizations that combine conceptualization, visual form and functions, and story-telling to help people understand the data more effectively. The contestants publish their visualization submissions internally for Amazonians to view and learn from them.
The competition is split into two divisions (standard and advanced), based on dataset complexity. The contestants fill out registration form when submitting an entry as an individual or as a member of a team with up to 4 members. The competition is held in three regions and each region has its own winners along with a worldwide winner.
The submissions are evaluated by a panel of judges who are SMEs and enthusiasts in Data ML, Analytics or Science on below criteria:
Impact : How effective is this visualization at helping people understand the underlying story?
Innovative : Does the visualization showcase novel techniques?
Inclusive : How usable and relatable is the visualization?
Engaging and Clear : Does the display of data convey key points clearly?
Design Aesthetics : Is the visualization visually appealing with right story lines?
With 70+ of contestants submitting visualizations utilizing one of two datasets - Pokemon or FIFA, this year’s submissions were highly interactive with abundance of creativity. The regional contests were exciting and with Global showdown the attendees were treated to a great show. The global winners were enshrined in the VizCon Hall of Fame, where future visualization stars will be able to draw inspiration for their submissions.
The Literal QuickSight Pokédex dashboard invites you to begin your adventure and explore the original 151 Kanto Pokémon. A single dataset engineered in Python allowed parameterised use of Heat Maps, Tables, Radar Charts, and a Geo Map wrapped around graphics edited in Paint.
@latent-lamb is a long term Amazonian working in Europe Seller Services Marketplace where as a Business Intelligence Engineer, he is improving data infrastructure to support the service offered to Selling Partners. Lam is passionate about Pokémon and is currently enjoying Pokémon Go to truly Catch em’ All.
Pokémon Universe Explorer by V Muralidhar Reddy, Shatakshi Pandey, and Dipesh Pipariya.
Pokémon Universe Explorer dashboard includes a Pokémon deck, history of each Pokémon, a repository to find best Pokémon, and a battle field using QuickSight features such as conditional rendering of visuals to show animations, calculated fields, ML forecasting in visuals and parameters developed for ‘Point and Click’ game.
The authors of the dashboard, @mureddy , @shatakp , and @pipariya are Cloud Computing Consultants from AWS Professional Services Data Analytics that enable customers in their enterprise cloud adoption journey to AWS cloud.