Frequently Asked Questions

Companies collect massive amounts of digital transaction data pertaining to their customers, orders, product use, install base, service tickets, crash logs, and market intelligence, but have no good way of creating a 360 degree view of each customer or their business.

With overall data volume, the number of data sources, and data complexity only poised to grow, AI is an opportunity to unlock business value from your data to both optimise automation and efficiency and open up new innovation possibilities.

The benefits of AI are wide. The ability to replicate decisions and actions of humans without human intervention is key. Humans inherently experience fatigue, emotions, biases and limited time. It is also easier to get consistent performance from multiple AI machines than it is to achieve the same from multiple human workers. AI also reduces the errors giving us more accurate results.

AI systems are better equipped to detect anomalies, match datasets, match people to products, predict outcomes based on multiple variables and identify other specifics from among large amounts of data. From a data onboarding perspective, machines are far quicker than humans to onboard data in near real time and so can accelerate the process from weeks and months to just days or even hours and scaling is made easy.

80 to 90 percent of data generated and collected by organisations is unstructured, and volumes are growing rapidly — many times faster than the rate of growth for structured databases.

Unstructured data stores contain a wealth of information that can be used to guide business decisions. However, unstructured data has historically been very difficult to analyse. With the help of AI and machine learning, new software tools are emerging that can search through vast quantities of it to uncover beneficial and actionable business intelligence.

While structured data is important, unstructured data is even more valuable to businesses if analysed correctly. It can provide a wealth of insights that statistics and numbers just can’t explain and can help organisations prosper in highly competitive environments. If this information is ignored, organisations aren’t using everything that’s available to them to be successful.

Unstructured data (or unstructured information) is information that either does not have a pre-defined data model or is not organised in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in fielded form in databases or annotated (semantically tagged) in documents. Many business documents are unstructured, as are multimedia files, email messages, videos, photos, webpages, x-rays, forms, lab results, pdfs, audio files and more.

Think about any kind of data that doesn’t have a recognisable structure and you have identified an example of unstructured data. Here are some of the most common examples of unstructured data:

  • Emails: Although emails include date, sender and recipient addresses and subject information, the text in the body of the mail doesn’t follow a format. Some refer to emails as semi-structured data.
  • Text files
  • Books, journals, documents, metadata,
  • Health records, x-rays
  • Photos
  • Video files
  • Audio files
  • Web Pages and blog posts
  • Social media sites
  • Presentations
  • Call center transcripts/recordings
  • Forms, lease agreements and contracts
  • Open-ended survey responses

Business Intelligence has been around for decades but only since the early 2000’s has the technology caught up with the research interest. The emergence of Big Data in the late 2000s led to a heightened interest in the applications of unstructured data analytics in contemporary fields such as predictive analytics and root cause analysis.

Digital transformation has been a big driver recently in organisations looking to work smarter and streamline data across disparate business functions in order to gain insights and make more informed decisions.

Being a data-driven organisation means ensuring each business function has access to the right data, to the right person at the right time. As unstructured data accounts for a large proportion of untapped information in the business, organisations are now utilising Artificial Intelligence to derive insights that may lead to significant improvements in automation and operational efficiency and scale it quickly.

Powered by AI and machine learning, such platforms function at near real-time speed and educate themselves based on the patterns and insights they uncover. These systems are being employed against large unstructured datasets to enable never-before-possible applications like:

  • Using predictive maintenance to help organisations analyse sensor data to detect potential issues or risks before they occur within core IT infrastructure systems.
  • Analysing and tracking communications and announcements of regulatory changes and compliance updates to ensure organisations remain compliant.
  • Following trends in the market and anticipating changes before your competition.
  • Monitoring news reports, social media, and online reviews of your competitors, and compare the results to your own data.
  • Tracking and analyzing customer social media conversations and interactions
  • Gaining reliable insights into widespread customer behavior and preferences through analysing multiple data sets and interpreting, matching and predicting outcomes.
  • Analysing unstructured data to better understand customers and identify attitudes towards products, services and brands in Retail. Enabling retailers to improve the customer experience and personalise marketing to specific target groups.
  • Aggregating and automatically extracting drug name, dosage, demographic, and other biomedical data from healthcare laboratories.
  • Optimising back office processes through automatic reading and loading of Housing Association notices, Tenant Letters, Conveyancers reports to reduce overheads or avoid missed fines within Real Estate.
  • Onboarding new client data to your systems by loading, extracting and matching entities from large volumes of financial or accounting data.

The ability to extract unstructured data is made possible through machine learning and artificial intelligence algorithms that employ techniques such as data mining, natural language processing (NLP), sentiment analysis and text analytics to provide different methods to find patterns in, or otherwise interpret, unstructured information.

Natural language processing technology is a form of artificial intelligence that seeks to understand meaning and context in text and human speech, increasingly with the aid of deep learning algorithms that use neural networks to analyze data.

Text analytics tools look for patterns, keywords and sentiment in textual data.

Common techniques for structuring text usually involve some early manual annotation and labelling of data that is deemed useful and want to integrate into the business.

From a small number of annotations, the system can quickly learn and then automate the data onboarding function with the human in the loop as the reviewer for quality assurance.

Once all data is onboarded AI can be used to structure and match data to gain useful insights or make predictions which can be directly integrated into the business.

Almost all global industries can benefit from using AI to unlock unstructured data to bring meaningful insights into their decision making from improving competitor intelligence to keeping regulatory compliant, to better understanding customers and matching people to products, to predicting potential insurance risks, finding the perfect candidate for a job and detecting potential fraud or missed payments which incur a fine.

The healthcare industry generates a large amount of unstructured data. Clinical trial data, lab documents, patient records, medical forms and medical research papers may yield important links between technical and medical studies and clues regarding new disease therapies.

In much the same way that LinkedIn matches a query to its massive semi-structured data stores, cross-referencing data to hiring trends and sharing the resulting recommendations with job seekers, AI can help recruiters more closely match specific roles to available candidates. AI can therefore accelerate the process of hiring, removing tedious, manual tasks from the staff and thus making them more productive.

Huge amounts of unstructured data go unexploited within the housing sector. Lease agreements, forms and other legal documents are often printed, in pdfs, spreadsheets, images or XML files. This makes analysis very difficult and extremely time consuming without advanced AI technology.

For organisations that are heavily regulated, compliance issues can be costly in time, money and reputation. With the insight provided by unstructured data when analysing emails, web, multimedia and chatbot conversations, for example, organisations could uncover regulatory issues earlier and before there is a significant negative business impact.

The move from digital transformation to data driven business transformation is seen as the next industrial revolution. With the global Artificial Intelligence (AI) market size expected to gain momentum, reaching USD 360.36 billion by 2028, the future of AI is bright.

Not only that, according to IDC's Worldwide Global DataSphere Forecast, 2021–2025, the total amount of data created, captured, copied, and consumed globally will reach over 180 zettabytes by 2025.

So how do organisations manage and utilise these growing volumes of data and unlock those valuable insights that give faster time to value?

Industries across the globe are rapidly incorporating Artificial Intelligence into their processes to improve business operations and customer experience but also to track competition, regulatory compliance and support innovation. The good news is that this technology is accessible to not only the big companies but also small and medium businesses.

No matter what your business specifics are, the end goal should be to unlock business value from ALL your data which means both structured and unstructured data sets to be truly data driven.

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Deeper Insights are AI specialists that make it simple to onboard, scale, analyse and integrate your unstructured data into your business to deliver positive business outcomes, whether that is through improved automation or better insights to drive business decisions.

Contact us to find out how we can help you integrate AI into your business strategy.

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