With companies pursuing digital transformation efforts while continuing to grapple with how best to do business amid the pandemic, it should be no surprise that the market for business intelligence tools (BI) is robust. But there’s a gaping hole in enterprise BI efforts because BI tools can’t analyze unstructured data, which accounts for about 85% of all data in most companies.
That means companies are analyzing only a small fraction of the data they own, losing out on unstructured data analysis and the business intelligence it may hold.
Big market for business intelligence
Yet companies are increasingly relying on BI tools to deliver fresh insights. The global BI market is projected to grow to $34.5 billion in 2027, up from $22.4 billion in 2020, according to ResearchAndMarkets.com. That represents a compound annual growth rate (CAGR) of a healthy 6.4%.
While some BI tools claim to support unstructured data analytics, most in fact work only with structured and, perhaps, semi-structured data. It only stands to reason, given unstructured data takes many forms, including Word documents, emails, PDFs, images, videos, and more.
Finding value in BI
But BI tools are indeed valuable. Tableau, for example, helps companies visualize their data. Its brand of “self-service” analytics is meant to be used by workers on the front lines – be they analysts, bank tellers, business team leaders, or insurance claims adjusters – to make more informed decisions.
Tableau has solutions that help companies in various industries, from banking and insurance to services and life sciences. It has industry-specific dashboards that perform functions ranging from helping banks make credit worthiness decisions to helping insurance companies determine their claims liability.
Yet these solutions are only as good as the data they have access to. While Tableau can integrate with data warehouses, it expects data to be formatted correctly. You cannot expect to feed, say, contracts of 100 pages or more in PDF format to a BI tool and get meaningful results. With respect to unstructured data, an intermediary step is required to conduct that formatting.
Related Article: Gartner Report Highlights the Power of Unstructured Data Analytics
How to achieve unstructured data analytics
That’s where the Indico Unstructured Data Platform comes in. The platform is built on a database of some 500 million labeled data points along with artificial intelligence technologies including machine learning, transfer learning, natural language processing and more. Together, these technologies enable the platform to “read” and understand unstructured data just as your employees would.
In a short time, your employees can build models that extract relevant data points from unstructured documents and convert them into a format that BI tools can understand. In so doing, the Indico Data platform makes possible three key analytics capabilities:
- Search: It’s now possible to search any amount of unstructured data looking for key terms or figures. Financial institutions, for example, are using it to find contracts and loans that contain references to LIBOR, the interest rate benchmark that is soon to be retired. Natural language queries are also supported.
- Visualize: Indico Data helps you get more out of data visualization tools like Tableau, Microsoft Power BI, and Google’s Looker. No longer are they relegated to dealing only with structured data. Now you can use the Indico Data platform to transform whatever unstructured data you choose and convert it to a format these BI tools can understand, typically JSON, .csv or a proprietary format.
- Compare: The platform also enables you to easily compare reams of documents to one another. Perhaps a commercial real estate company wants to compare all of its customer contracts, to find inconsistencies, compliance issues, favorable terms and the like. Or maybe you want to understand the variability in key clauses across a body of contracts.
You’re spending good money on BI tools. Make sure they have access to all your data, so you can unlock the power of unstructured enterprise data.