With the history of becoming difficult to manage non-structured data. Wait? In order to get our heads turned around the unstructured data, we'll explore the short history of Data. The world began digitizing data in the 20th century. The process began with transactional data, and accounting, which is neatly organized into columns and rows. Several decades after, we're digitizing everything data and sharing it across organizations as well as personal connections and partners. 

This raises the question of what format does this data available? It's a big question because of the huge quantity of information from enterprises which is contained in the text, emails, documents presentations, graphics videos, audio, and websites… It's not compatible with the relational model of data. In 20 seconds, you can also schedule a free consultation with our  blockchain solutions for substrate development services!



May be an image of text that says


Do We Have The Tools To Solve It?

There are some powerful kinds of data management and search tools. Text search tools such as SOLR, Elastic Search, and Amazon web cloud search as well as the third eye, -3rdi, are a few examples of how to manage amorphous text information which is commonplace in business today. Let's look at a brief tour of these tools at an upper level.

Solr as well as Elastic Search are both based on Lucene and provide advanced search capabilities, and the capability to grow according to the needs. They are open source licenses. Solr indexing has advanced pre-processing capabilities, including tokenization and query support, spell-checking, and highlight. It effectively searches for parts of documents such as full search and multi-faceted search. Elastic Search stores documents in JSON format and text fields are indexable. It doesn't need an explicit scheme to load the documents. Instead, it can determine the structure of documents in JSON documents straight away. Additional support and services can be found for SOLR along with Elastic search.