OVERVIEW:
As technology continues to grow, we are generating more data than ever before. Data scientists, analysts, developers, and “business users” want to leverage that data to answer business questions and make more informed decisions.
However, many of the questions people ask requires data that might not be available to them, or requires heavy data curation. For example, you might have internal sales and revenue data that if combined with external financial market data could generate new insights. These analysts thus have a need to find sets (within their business or from trusted sources) that extend and amplify their existing data.
There is enormous amount of data being created, and that is growing day by day. But our ability to find what we need in that massive mountain of data and make effective use of it has not kept up. Our project doesn't focus on today. It envisions the future experience of a data marketplace that makes all this data available in a consumable way.
Our team was tasked with creating a data first marketplace. A place where data is the core value and also the driver to attracting new users to IBM tools and services.TEAM:
Bhavika Shah (Design Lead), Megan Corbett (Research), Mallory Anderson (Research), Kacie Eberhart (UX Designer), Chris Befeld (Visual Designer), Cris Gonzales (Visual Designer), Ben Resnick (Front-end Developer), Shy Dhanani (Front-end Developer)
Erin Hauber (Incubator Lead), Greggor Ottoson (Incubator Lead)
Meet our two users: Sally and Daniel. They both work with data to meet their company’s strategic objectives.
Sally’s process is more iterative, she might do multiple searches to find what she needs. Daniel, on the other hand, knows exactly what he wants and wants to get it immediately. While their processes are different, they both struggle with finding quality data sets in the massive volume that is available. If we can solve for Sally’s more complex, iterative process, we can solve for Daniel to find exactly what he needs.
Top 5 Pain POINTS:
Constant Churn within Workflow Progress
No Preview of Data before Download
Prepping Data for Use Takes Too Much Time
Merging Datasets Relies on a Common Axis
Detecting Trends and Insights is a Manual Process
Dataplace connects analysts and developers to the most complete and credible data sets and data products in the world.
The platform enables users to discover and work with curated IBM and IBM Partner data to build custom data sets that provide new insights for their business.
Unlike other data providers, Dataplace takes the guesswork out of data relevance and compatibility by leveraging the power of Watson Analytics and Dataworks to provide robust and highly visual custom sets for easy integration.
Leveraged Capabilities:
But it’s not just about Watson Analytic’s visualizations. We can leverage many of IBM’s existing capabilities to make this marketplace a reality. Leveraging these capabilities will lower the cost of implementation. More importantly, we envision our market going beyond simple call-to-actions that funnel users into our products. We want to get users hooked on our interaction patterns and capabilities.
Within this huge explosion of data, organizations have stated that they understand the value of Big Data and using it to develop and share insights helps meet strategic objectives.
However, there are two big issues in dealing with data: quality and volume. Quality in terms of how the data is structured and formatted. Volume in terms of finding what is relevant in the vast mountain of data.
