Living in a globalized world where business operates with an evolving set of practices and norms, there are many areas where enterprise technology is impacted. Several recent articles that point to this idea caught our attention in The Trend Point over the past week.
There is an imminent need for solutions that are geared towards large businesses that are operating on a global scale, and have to deal with large amounts of data. “Getting a Global Perspective on Enterprise Search” echoes this idea:
The first day of the conference started with Ed Dale of Ernst & Young talking about implementing enterprise search for a truly global organisation. E&Y’s search is over a surprisingly small number of documents (only 2 million or so) but they are lucky enough to have a relatively large and experienced team running their search as an ongoing operation – no ‘fire and forget’ here (an approach often taken and seldom successfully).
It is no surprise that we are seeing an article like “Sage Advice for Data Storage and Analytics” call for consideration towards scalability and searchability. The following information was relayed in this post:
The repository should be highly scalable with respect to the storage capacity and amount of requests it can handle. Because of ever generating digital content out of various business processes, size of the stored content can grow rapidly and the storage limit should not be a roadblock for any content repository. Similarly, the architecture should be capable enough of handling a varying number of user requests.
Many terms like semantic search, natural language processing and text analysis are popping up everywhere in regards to enterprise software. We saw the following summary in “SAP HANA Project Addresses Text Analysis” break down some of these definitions:
The two terms are used interchangeably by a lot of people. There is a lot of gray area in defining ‘Text Analysis’ and differentiating it from ‘Text Mining.’ But from the SAP perspective, ‘Text Analysis,’ refers to the ability to do Natural Language Processing, linguistically understand the text and apply statistical techniques to refine the results. Text Mining is applying algorithms, like predictive analytics, for post-processing of data (akin to data mining).
As successful businesses become global they often need increased scalability and text analysis capabilities. One unique feature to Sinequa’s Unified Information Access is that in addition to the semantic search and text analysis functionality (“Natural Language Processing”), this solution also has the capability to interpret text in multiple languages, and it scales to very large volumes. An enterprise search solution is not prepared to enter the globalized market without such technology. Sinequa is particularly poised to address this aspect because their research continues every day. Just as language naturally evolves, Sinequa’s methods also evolve to mirror such changes.
Jane Smith, June 12, 2013