As data-driven culture is spreading, enterprises are struggling to tame the deluge of information that is mostly unstructured but stores valuable business insights.
According to estimates, 80-90 percent of the data in any organization is unstructured.
This information is created in formats such as emails, business documents, social media content, or sensor data, and is buried in complex infrastructure and silos.
And many today describe unstructured data as the new oil. Like a few centuries back, however, this oil remains hidden, being largely unsearchable and difficult to evaluate.
Unlocking value from unstructured data is posing a challenge.
But leading companies that know how to make sense of their digital mess are turning this data into actionable intelligence. A variety of artificial intelligence (AI) and machine learning (ML) tools are emerging to help extract insights about customers, markets and trends from dark data.
What is unstructured data?
Every click, search, swipe, share, or stream becomes data. This data may be structured, semi-structured, or unstructured.
- Structured data can be easily organized into a table or a set of tables such as a relational data model (e.g., dates, credit card numbers or geolocation).
- Semi-structured data is a form of information that does not reside in relational tables but contains some semantic tags and other markers such as XML.
- Unstructured data is everything else. This information either does not have a pre-defined data model or is not organized. It cannot be analyzed using conventional tools.
Unstructured data examples
- Social media content (incl. posts and tweets)
- Sensor data (incl. IoT devices)
- Log data (incl. servers, websites and application logs)
- Communications (incl. emails, chats and messaging)
- Text files (incl. business documents)
- Audio files (incl. customer calls)
- Video files ( incl. streams and surveillance data)
- Images (incl. photos and scans)
Big Data is Getting Bigger, Less Structured …and More Rewarding
- In 2020, the amount of newly created data is predicted to grow 44X compared with a decade ago
- More than 80 percent of enterprise data is unstructured
- 99.5% of collected data never gets used or analyzed
- 79% of executives believe that failing to embrace big data may lead to their companies’ extinction. That’s why 83% of companies invest in big data projects
- The amount of unstructured data is increasing at an incredible rate of 55-65 percent each year
- Revenue from big data is expected to generate $274.3 billion globally in 2022
Outplaying the Matrix
Remember thе scene from The Matrix when Morpheus beat Neo? “Do you think that's the air you're breathing?” he asked his student.
That wasn’t.
What they were breathing in was unstructured data, and Morpheus knew how to outplay it to be “faster and stronger”.
Human beings, unless they have escaped the Matrix, live in unstructured data they cannot get their hands on.
And, since grasping this data is beyond the capacity of the human mind, its value is never discovered – let alone tapped into.
However, there are martial arts to combat unstructured data. They are called AI and ML.
Machine Learning & Artificial Intelligence in Action
While the ambition of AI pioneers to recreate the human brain is still far from being realized, ML is demonstrating impressive performance across an increasing number of applications.
AI/ML technologies help organizations extract, interpret and report business insights from raw data, with use cases ranging from customer analytics to predictive models.
With the help of ML, which enables computers to learn for themselves, you can find patterns in your unstructured data sets and decipher important information.
There are many benefits of unstructured data. They include reduced cost, higher productivity, new product development, fraud detention – and better business decisions.
According to 451 Research, 42% of enterprises are already incorporating unstructured data into their ML projects. Looking ahead, 50% of respondents plan to use unstructured rich media data in the next couple of years.
Over the last decade, the ITRex team has designed a range of successful ML-driven projects to help our clients unlock value from their avalanches of data. These unstructured data use cases include:
- AI-powered decision support to predict costs based on multiple parameters (Logistics)
- Graph-based decision-making tool to detect and remove duplicate entities when processing customer requests, and to suggest better carrier matching options (Logistics)
- AI-driven platform to collect, manage and present patient-related data for newly diagnosed cancer patients at the time of diagnosis and throughout the entire survivorship experience (Healthcare)
- Interactive predictive tool to generate visually compelling survival curves for newly diagnosed cancer patients. To enhance its predictive algorithms, we have added multiple patient-specific factors such as age, gender, comorbidity, cancer site, cancer stage and tumor grade (Healthcare)
- Predictive analytics model to predict game schemes during football matches depending on inputs and process data from sensors inserted into players' shoulder pads (Fantasy Sports)
- AI-powered big data platform to enable a 360-degree view of all data sources and data across the organization for better decision-making (Retail)
Bottom Line
With technologies advancing at an unprecedented pace in a highly competitive environment, data will be for many the key to success in the digital era.
Are you disrupting the competition or among those disrupted? Contact us for assistance in turning your unstructured data into actionable insights that will help you address your business needs now and beyond.
