Converting Unstructured Data into Useful Information Straive

Posted on : October 29th 2021

Posted by : Sudhakaran Jampala

The Story behind Converting Unstructured Data into Useful Information

The Growing Focus on Unstructured Data

Good things can come from unstructured data—if you can automate data acquisition, enrichment, and delivery operations in a way that requires minimal manual intervention. Unstructured data are notoriously hard to define and leverage. What is the story behind its conversion into usable information and insights? The volume of data defined as unstructured grows 55-65 percent each year. Moreover, unstructured data are projected to account for approximately 80 percent of the data enterprises will process daily by 2025. It is present in diverse sources and formats, and it lacks consistent data definition (Exhibit 1).

Exhibit1Explosion.png

Source: Straive

Unstructured data provide a layer of insights that fill the gaps in the big picture. Combining unstructured data with structured data improves business decisions, making them better informed and more robust. Unstructured data go mostly unused; industry analysts IDC note that more than 90 percent of unstructured data is never examined. Large portions of business data floating around unsecured and underutilized. We must learn to understand from where unstructured data have been sourced. Why is it so hard to pin down? What are the risks of unsecured, unstructured data? What are the rewards of bringing that data into a structured environment?

Challenges with Unstructured Data

Unstructured data can't be stored in a traditional column-row database or a Microsoft Excel spreadsheet. The challenges of analyzing and searching it have made it useless until recent years. Unstructured data can come from almost any source. Nearly every asset or piece of content created or shared by a device in the cloud carries unstructured data. Therefore, Data loss prevention (DLP) is critical Straive’s data platform, powered by artificial intelligence (AI), can extract and enrich unstructured data to provide insights.

The Need for Innovative Solutions

How are unstructured data converted into usable information and insights? Straive’s text intelligence solution enables enterprises to turn unstructured textual data into actionable insights (Exhibit 2).

Exhibtion 2: Unstructured Data and Straive's Text Intelligence Solutions

Unstructured Data Into Usefull.png

Source: Straive

The Straive Data Platform (SDP) innovatively tackles these challenges. This sophisticated platform uses a three-step approach involving AI and machine learning (ML), to discover, classify, and read unstructured data for downstream consumption. Our solution makes sense of unstructured data, whereas traditional security solutions rely solely on users to help categorize data through conventional methods like regular expressions (regex). These have limited accuracy in unstructured environments.

The AI/ML edge

Straive advocates a platform-led approach with AI/ML at its core to convert unstructured data into usable insights. AI/ML-led platforms interface with enterprise applications to process massive amounts of unstructured data at scale, leading to smart automation (Exhibit 3).

Exhibit 3: The Straive Data Platform

PlatformEnablers.png

Source: Straive

SDP automates the data acquisition, enrichment, and delivery operations in a way that scales with minimal manual intervention. SDP's auto-extraction feature uses both a rules-based and an ML engine to deal with the data variability, sources, and volume while maintaining quality. The platform-led AI/ML approach underpins Straive’s specialized data solutions. We solve complex data intelligence problems in the unstructured data domain for our customers.

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