4 Enterprise Search Myths & their Reality

Enterprise search has been there for quite a while now and we’ve witnessed several breakthroughs in the field over the years. Today, we have enterprise search engines powered by advanced technology like semantic search, natural language processing, artificial intelligence and so on. An enterprise search engine like 3RDi Search or Coveo, offer all the features one would need for quick yet effective analysis of even the most complex organizational data. However, enterprise search is still not quite well understood and there are a handful of myths that surround it today. Here are some of the most common myths, along with their respective solutions.

1] Enterprise Search is not very different from Web Search

The Myth: Now, this one is a very common myth. Many people out there are confused because they are not able to comprehend the need for a separate enterprise search engine in the first place. They feel that organizations can very well work with Google or Bing.

The Reality: The reality is that enterprise search and web search are entirely different in the way they function. To begin with, the latter is designed to fetch results from content that is optimized for a set of keywords. Keywords are nothing but the most popular search terms. However, the former is not dependent on keywords as organizational data is largely unstructured data which is raw and unoptimized. Also, the data types are more varied when it comes to organizational data as compared to web content. Also, web search is linear while organizational data needs various advanced concepts.

2] There’s More Data on the Web than Organizations Can Ever Have

The Myth: This myth is pretty common too and most people believe that the Internet is the only place where you find billions and trillions of gigabytes of data. People have a perception that organizational data is much smaller in volume and can never be compared to data on the Web in terms of volume.

The Reality: While it’s true that the total data on the Internet today runs into millions of terabytes (1 terabyte = 1000 gigabyte), and the number of webpages are increasing every minute, it will be incorrect to say that organizations have very less data to work with. In fact, data driven organizations often have data that runs into thousands of terabytes and sometimes, even a few petabytes (1 petabyte = 1000 terabytes). Basically, the conclusion is that organizational data can also be huge and a major portion of this data is unstructured.

3] A Single Relevancy Model works for Everyone.https://www.entreprise-sans-fautes.com/

The Myth: Many people believe that enterprise search engines are all the same and that relevancy models are universal – what works for one, works for all.

The Reality: The reality is that the enterprise search engine is a fairly recent concept that came into existence only in the late 90s. Before that, it was all about the keywords based approach and there was no distinction between approaches for the enterprise and the Web. Since it is pretty new, there is a still a long way to go before we have a single tool that works for every business. As of now, not every tool brings the same results for everyone and the tool that a business chooses depends on the requirements of the business, the kind of projects, and so on.

4] The Application of Enterprise Search Engines is limited to Enterprises alone

The Myth: When we hear of the term ‘enterprise search’, many people imagine it is a tool that is only used by corporate professionals to find out information from their organizations data.

The Reality: The reality is that enterprise search engines find a wide variety of applications, which include ecommerce and research as well. The search that one finds in ecommerce sites is powered by an enterprise search engine, which makes it possible to implement advanced options. Also, research platforms (refer to ResearchNet) are powered by an enterprise search engine to help students and professionals find the most relevant results from the huge repository of data.