If you’re a millennial, you don’t remember the bad old days of enterprise search. It was high on the scale of frustration. You often couldn’t find what you were looking for. And, if you did, it probably took a long time. But then, thankfully, Google happened.
Take a look at this unbelievable Marketing stack from Cisco. I’m assuming that this all stands behind Cisco.com and is representative, but not exhaustive. Even so, have you ever seen anything so well thought out, open, and cutting edge – let alone so well laid out? Can you imagine the infrastructure budget that Marketing Ops team has – mercy!
Users want relevant results from their search queries. But, in addition, they want their search tool to “understand” what their queries mean based on context. In other words, know the difference between what was expressed in the query and what was intended.
Attivio is pleased to announce its Managed Services offering for Cognitive Search and Insight in the cloud. Now you can have the full power of Attivio without having to buy hardware or manage software. Attivio will handle everything for you. With the Attivio Managed Services for Cognitive Search, you get the complete platform hosted on AWS and managed by Attivio.
It’s hard to imagine a function that requires access to a broader and more diverse set of information than investment research. After all, the typical research analyst pours through an endless amount of data as they strive to produce timely, accurate, and relevant investment recommendations. Annual reports, company filings, security analytics, risk analytics, industry blogs, social media, and market news are just a few of the many data points leveraged as part of the research process.
One of the biggest changes in the upcoming Sherlock release of the Attivio Platform is moving to a Hadoop-based architecture for big data applications. Hadoop provides us with a number of low level capabilities that we no longer have to manage at this scale, such as resource management (YARN), coordination (Zookeeper), storage (HDFS) and bookkeeping (HBase). One of the side benefits of YARN based resource allocation is the ability to scale up or down your system’s footprint with a few simple YARN commands.
Remember the frustrations of key word search? If you need a refresher, just check out If Google Was a Guy. It’s funny—in a way that makes you kind of squirm in your seat. Of course, in the early days of search engines, power searchers used Boolean query operators. We have George Boole, 18th-century English mathematician, to thank for that.
Some days, it seems that new machine learningapplications are popping up everywhere you look in the news. In this author’s opinion, the search market seems to have anointed machine learning as the new hotness. This is a fascinating realization, because anyone who has spent more than a couple years deploying search in the enterprise knows that machine learning has been used and applied in exciting and unique ways for years and years.
Sir Arthur Conan Doyle’s 1886 fictional “consulting detective,” Sherlock Holmes, was a great mind renowned for his highly advanced powers of observation and reasoning. He was often assisted by Dr Watson, who was unfailingly loyal, if noticeably less bright. At the end of each thrilling tale starring the duo, the anxious reader would always be delighted to hear Sherlock announce that he had solved the latest mind-bending riddle, inevitably characterizing the solution to his trusty helper as, “Elementary, my dear Watson!”