Jeffrey Schwartz of Redmond Magazine recently wrote, “Nearly a year after launching its Hadoop-based Azure HDInsight cloud analytics service, Microsoft believes it’s a better and broader solution for real-time analytics and predictive analysis than IBM’s widely touted Watson. Big Blue this year has begun commercializing its Watson technology, made famous in 2011 when it came out of the research labs to appear and win on the television game show Jeopardy. Both companies had a large presence at this year’s Strata + Hadoop World Conference in New York, attended by 5,000 Big Data geeks. At the Microsoft booth, Eron Kelly, general manager for SQL Server product marketing, highlighted some key improvements to Microsoft’s overall Big Data portfolio since last year’s release of Azure HDInsight including SQL Server 2014 with support for in-memory processing, PowerBI and the launch in June of Azure Machine Learning.” Read more
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Research firm Forrester at the end of September issued its Forrester Wave: NoSQL Key-Value Databases, Q3 2014 report. The report looked at seven enterprise-class vendors in the space: Amazon Web Services, Aerospike, Basho Technologies, Couchbase, DataStax, MapR Technologies, and Oracle.
Noting that the current adoption of NoSQL is at 20 percent and is likely to double by 2017, Forrester principal analyst and report author Noel Yuhanna and his co-authors explain that top use cases for key-value database include social and mobile apps, scale-out apps, Web 2.0, line-of-business apps, big data apps, and operational and analytical apps.
That said, he also notes that the lines between key-value store, document database and graph database NoSQL solutions are blurring, as vendors look to satisfy broader enterprise needs and better appeal to app developers. “Relational database management system vendors, such as Oracle, IBM, Microsoft and SAP, will broaden their current relational database products to include key-value, graph and document features and functionality to deliver more comprehensive data management platforms in the coming years,” the report states.
What do you get when you mix two parts natural language processing with a little personalization, and add in a dash of the cloud? The answer is Whisk, a U.K. company building a service that lets users purchase the ingredients for any recipe they find on the Internet.
“The crux of it is that you can take any recipe on the ‘Net and turn it into a transaction in on online market,” says co-founder Craig Edmunds. “There’s a machine translation problem from the recipe up through to our internal language, which is one NLP problem, and then another is from our internal language into online markets.” Another leg of the work is that the service seeks to not match to just one item at a market but as many as possible, and consider user preferences as to which is the optimal product, too.
At the upcoming Semantic Technology and Business Conference in the U.K., Edmunds will be considering how the issues of machine translation, manual intervention, personalization and the cloud intersect in creating a service that adds all the ingredients they need for dishes they find online straight into their online shopping basket.