Microsoft and Its Latest Search Innovation: Moving Past Fast? Nope
May 22, 2020
I read “Microsoft Search: Search Your Document Like You Search the Web.” Perhaps Microsoft did not get the reports about the demise of the Google Search Appliance. That “invention” made clear that searching a corporate content collection like you search the Web was not exactly the greatest thing since sliced bread. There were a number of reasons for the failure of the GSA. It was a black box. You know that mere mortals could not tune the relevance component. You know that it produced results that left employees wondering, “Where is the document I wrote yesterday?” You know that the corpus of Web content is different from the fruit cake of corporate content. Web search returns something because the system is rigged to find a way to display ads to the hapless searcher.
Contrast this with documents in the cloud, in different systems like that old AS/400 Ironsides application used by the warehouse supervisors, and content tucked away on employees’ USB drives, mobile phones, the oldest kid’s iPad, and on services a go to sales professional uses to store PowerPoints for “special” customers. Then there are the documents in the corporate legal office. The consultants’ reports scanned and stored on the Market Department’s computer kept for interns.
Nevertheless, the article explains:
We’re utilizing well-established web search technologies, such as query and document understanding, and adding deep learning based natural language models. This allows us to handle a much broader set of search queries beyond “exact match.”
Okay, query expansion, synonym look up, and Fast Search’s concept feature. But there’s more:
With the recent breakthroughs in deep learning techniques, you can now go beyond the common search term-based queries. The result is answers to your questions based on the document content. This opens a whole new way of finding knowledge. When you’re looking at a water quality report, you can answer questions like “where does the city water originate from? How to reduce the amount of lead in water?”
May I suggest that Microsoft and dozens of other enterprise search vendors have promised magical retrieval?
May I point out that the following content types are usually outside the ken of the latest and great enterprise search confection; for example:
- Quality control data on parts stored in an Autodesk engineering document
- Real time data flowing into an organization from sensors
- Video content, audio content, and rich media like photographs
- Classified or content restricted by certain constraints. (Access controls are often best implemented by specialized systems unknown to the greedy enterprise search indexing system.)
- Documents obtained through an eDiscovery process for legal matters.
Has Microsoft solved these problems? Sure, if everything (note the logically impossible categorical affirmative) is in an Azure repository, it is conceivable that a user query could return a particular content object.
But that’s Microsoft fantasy land, and it is about as likely as Mr. Nadella arriving at work on the back of a unicorn.
Microsoft feels compelled to reinvent search every year or two. The longest journey begins with a single step. It is just that Microsoft took those steps decades ago and still has not reached the now rubbelized Fred Harvey’s.
Stephen E Arnold, May 22, 2020
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