Data Analytics

Introducing the Watson Discovery Service: Content full of lemons? Turn it into lemonade.

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As I prepared to write this post, I reflected on my favorite Christmas memory as a child — the year Santa brought me my first computer — an Apple IIe (I later learned to code on an IBM XT but I’ll save that story for another day). Kris Kringle was kind enough to also deliver a stack of 5.25” floppy disks loaded with hottest games of the era, like Oregon Trail and Lode Runner. There was one game which caught my imagination and would end up consuming many hours of my childhood: Lemonade Stand.

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The premise of Lemonade Stand, was addictively simple – run a lemonade stand where each choice I made determined my stand’s success … or failure. Each “day” in the game, I decided how many glasses of lemonade to produce, how many advertising signs to make and what price to charge for each glass – with only one very important, but sometimes inaccurate, piece of data to base my decisions on – the day’s weather prediction.

Today, the era of the lemonade stand types of businesses—where decisions on what to produce, how many to produce and how to go to market are driven by guesses and few pieces of data—are no more. Instead, businesses face an explosion of customer feedback that fuels their ability to rapidly make decisions, quickly adjust direction and ultimately increase velocity.

However, a pervasive challenge remains: unstructured content. The analysis of structured content – numbers, dates, organized groupings of words, which tell us WHAT is happening – has been largely conquered with traditional analytics systems; however, the analysis of unstructured content presents continuing challenges.  But it’s precisely unstructured content, like product reviews, social media and images, that tells us WHY things are happening.

For example, I may know that my business is getting a tremendous amount of reviews for a newly launched product—all of that interest must be a great thing, right? Actually, it’s the text in those reviews that tells me why there’s a lot of interest. Maybe people love it … or maybe the product doesn’t meet customer’s expectations. What I need is an engine that will scour those reviews to reveal insights for my next decisions. Kind of like turning lemons into lemonade.

Turn Your Lemons into Lemonade with the Watson Discovery Service

Watson Discovery Service tackles this challenge head on. Now generally available, it lets developers rapidly build cognitive apps that extract value from structured and unstructured data. With the Watson Discovery Service, developers spend less time cleaning up and acquiring their data, and much more time analyzing and exploring it.

  • Easily ingest and normalize enormous amounts of unstructured proprietary and publicly available content—even if you have little or no systems engineering and machine learning skills
  • Exploit third-party pre-enriched news data to enable highly targeted search and trend analysis
  • Apply natural language processing and artificial intelligence capabilities to go far beyond simple keyword searches
  • Perform multiple query types including boolean, filter and aggregation to discover patterns, trends and answers
  • Easily add your Watson Discovery Service data to existing applications using REST APIs

Watson Discovery Service brings together core Watson capabilities—like AlchemyLanguage and Document Conversion APIs, and Watson Knowledge Studio —into an integrated cognitive service that simply and efficiently ingests documents so you can identify critical correlations in vast amounts of unstructured content.

Use Watson Discovery Service in any situation where you want to reveal value in unstructured and structured content, like these:

  • Aid customer service representatives in delivering answers to complex customer questions
  • Help researchers understand insights from vast numbers of research documents, industry journals and news content
  • Extend Watson Conversation Service-based apps to find answers when modeled intents are insufficient to cover the breadth of possible questions

 

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