Turning unstructured data into actionable insights – By 2025, the world’s data will likely reach 175 zettabytes. Of which 80-90% is unstructured, text intelligence is likely to experience unprecedented growth of ~26% by 2026.
No data can be the same or can be created equal. Data exists in two main formats— structured and unstructured— and although structured data is straightforward and can be used and reused in several ways, it’s unstructured data which is way more than required and common. According to International Data Corporation (IDC), by 2025, 80% of all enterprise data will be unstructured in nature. Of this, text data will be the largest component. This is going to be a major challenge for businesses.
Data formats matter, as they play a key role in the extraction of valuable insights required to power business decisions. If enterprises fail to utilize both the nature and volume of data to improve business growth and profitability, then there is a need to evaluate the data strategy in-hand. Understanding the difference between structured and unstructured data is key to any enterprises data strategy, post which necessary investment decisions are made to extract relevant insights from the aggregated data.
What is unstructured data?
Unstructured data does not have a definite format and cannot reside logically in a tabular row and column format. Consider unstructured data as “subjective” data, in the sense that it has data that you need now and which you may need later. It can be generated by both machines and humans, and typically does not have a pre-defined data model.
Examples of unstructured data include sources such as annual reports, press releases, scientific publications, blogs, mobile transactions, customer transcripts, title deeds, and more. Other sources of unstructured data include web pages, images (JPEG, GIF, PNG, etc.), videos, word documents and PowerPoint presentations, survey data, and more. It’s not only difficult to analyse unstructured data but is also time-consuming and laborious with manual processes limiting scalability. Although structured data can be easily processed by machines, it’s challenging to build automated tools to analyze unstructured data, as doing so may require the use of machine learning (ML) technologies like natural language processing (NLP). There’s only a thin line of difference between structured and unstructured data. That’s because data that seem unstructured can be processed in a structured way. That’s where Text Intelligence solutions can help.
Sifting Unstructured data with Text Intelligence Solution
Text intelligence solutions make it easy to extract data from documents for deep analysis, insights, and business applications.
SPi’s text intelligence solutions, enabled by its end-to-end technology platform Spark, helps companies to benefit from these opportunities by bringing a suite of advanced solutions to extract, enrich, and deliver data and actionable insights from text-heavy documents in any formats such as text PDF, emails, word files, scanned PDF’s, and more.
Spark enables organizations to support the knowledge discovery process and text intelligence by ingesting raw source documents and providing curated structured data as output by leveraging cognitive technologies layered with SME intervention to deliver highly accurate datasets. The platform and its modules work well when processing unstructured data— which causes challenges for enterprises of all kinds.
Backed by a machine learning engine, Spark’s extraction module leverages cognitive models to achieve industry-leading accuracy in extracting unstructured data. The extraction module also uses SPi’s next-generation web harvesting platform, powered by AI and NLP accelerators, to extract information and monitor websites for raw, standardized data.
Why you should be using Spark for text intelligence
There are four reasons why you should be using a text intelligence tool:
How does Spark help meet customer expectations –
Benefits of SPi’s Text Intelligence solutions
Get started with SPI’s Spark
SPi’s Spark Text intelligence helps you get the most out of your unstructured data by taking on time-consuming, tedious tasks and frees you to focus on more important parts of the business.
With text intelligence, you gain a deeper understanding of your customers so that you can improve the customer experience and listen to your customers at every step of the way.