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IBM Expands Data Discovery and Q&A Power of Watson Analytics
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December 11, 2015 Blog big data

In a move to make it even easier for users to extract insights from their data, IBM has introduced new data discovery and question-and-answer capabilities for Watson Analytics.

IBM also announced widespread adoption, with half a million professionals registering for this groundbreaking data exploration and visualisation service since its introduction less than a year ago.

IBM Watson Analytics helps individuals unlock the value of data they already have in their systems, as well as new valuable external data sources they may not even know they need.

By bringing as much data as possible to the problem at hand, professionals can answer their toughest questions and embed insight and expertise into every decision they make.

By understanding natural language, reasoning and generating hypotheses, cognitive computing is helping people understand, reason and learn from their data in new ways.

The expanded data discovery and question-and-answer capabilities for Watson Analytics help professionals ask questions, uncover patterns and build predictions, including:

Access to New Data Connectors: Watson Analytics allows users to bring more external data sources to a business question, helping to ensure the right data is collected and curated to add context, depth and confidence to every decision. This includes access to data from IBM DB2, IBM Informix, IBM Netezza, IBM SQL Database, IBM dashDB and popular third party data sources.

A New Secure Connection to Corporate Data: The ability to securely connect to corporate data from the cloud is being enhanced with a new functionality from IBM’s cloud-based data refinement and access service, Dataworks. The new capability calls on Secure Gateway technology to establish a tunnel between the user’s on-premise databases and Watson Analytics, automatically encrypting data, and using Docker containers to transport it through a dedicated connection to allow for secure analysis.

Interactive Data Discovery with Expert Storybooks: In collaboration with industry partners, IBM is introducing new data discovery models – called Expert Storybooks – that will help guide users on how to understand, learn and reason with different types of data sources to surface the most relevant facts and uncover patterns and relationships for predictive decision making.

Examples of the types of Storybooks IBM will make available are as follows:

  • AriBall – a Storybook that will help users analyse the performance of baseball players to build predictions about player performance that they can use to gain an edge in their fantasy lineup.
  • Deloitte – a Storybook that measures the effectiveness of incentive programs to help sales leadership determine how and when to effectively deploy short term incentives for revenue uplift.
  • The Weather Company – a Storybook that helps users incorporate weather data into their revenue analysis to understand how weather is impacting their business.
  • OgilvyOne – a Storybook that shows users how to analyse marketing campaign data while integrating disparate data points such as weather information to bring creative inputs into campaign planning.
  • Twitter – a Storybook that helps users analyse social media data from Twitter to measure reputational risk, and also get a better understanding about how social sentiment could reveal drivers behind fluctuations in stock prices in real time.
  • American Marketing Association – a Storybook that helps users identify and analyse the key drivers of customer profitability.
  • Nucleus Research – a Storybook that enables users to benchmark projects for return on investment (ROI) and to project expected returns for proposed technology projects based on Nucleus Research data from more than 500 ROI case studies.
  • MarketShare – a Storybook that helps users achieve a clear understanding of how their investment strategy compares to industry standards, as well as a view into how to optimise investments across online and offline media channels such as TV, paid search, digital display, online video, radio, print, and others.
  • Intangent a Storybook that will help finance managers examine the relationships between pay, performance, and credit risk in lending to better align incentive compensation with risk taking.

The rapid adoption of Watson Analytics comes as more data analysis is shifting to a self-service model.

By 2018, “smart data discovery,” which includes natural-language query and search, automated advanced analytics and interactive data discovery capabilities, will be the most in-demand BI platform data discovery user experience paradigm, enabling mainstream business consumers to get insights such as clusters, segments, predictions, outliers and anomalies from data.*

By moving analysis to a self-service cloud-based model, business users can streamline analytics projects without investing in expensive and complex IT infrastructure, and ultimately gain insights on critical data, faster.

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