The Benefits of Leveraging Unstructured Data in 2017

The Benefits of Leveraging Unstructured Data in 2017

The Benefits of Leveraging Unstructured Data in 2017

Large companies and organizations are already using big data for some specialized applications, but the majority of that big data is still structured data (transactions, clicks, etc.). It is predicted that in 2017 we will see a greater focus on leveraging unstructured data as big data usage continues to rise.

Many digital companies whose businesses rely on big data have been leading the pack in their ability to gain beneficial insights from unstructured data. But this ability is now expanding to enterprises that aren’t as data-reliant as more data becomes available, and as the tools to manage that data become attainable without huge investments or long development cycles. This will allow big data analysis in 2017 to more frequently include insights derived from an organization’s vast stores of disparate, unstructured data in addition to the current popular focus on making sense of the numbers, analytics, and business intelligence provided by structured data.

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This will be a fundamental shift. Structured data provides important numbers about revenue performance, operational metrics, etc., but unstructured text holds the critical information about how business actually gets done. A company’s institutional knowledge (or secret sauce), discoveries, internal processes, and competitive edge are often contained in a vast array of written text. It takes natural language processing, unified information access, and cognitive search capabilities to extract information from this text and share it in a useful way with those who need it. This will allow organizations to understand what the text is saying on a broad scale and use that to drive innovation, increase efficiency, and improve operational effectiveness.

The Rise of Search Technology to Tackle Persistent Challenges

Two challenges often plague organizations as they try to tackle unstructured data: infrastructure and unification. Businesses are starting to solve the infrastructure problem with data lakes or the cloud, but the unification of unstructured data remains tricky. Of the “three Vs” of big data (volume, variety, and velocity), the one that poses the greatest challenge to unstructured data usage is that of data variety. This vast amount of variety makes successful unification absolutely critical. But data lakes, while providing more flexibility than traditional data warehouses, don’t solve the variety conundrum; they just postpone the need to solve the problem to the point of data usage rather than the point of ingestion.

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In 2017, the use of search technology to create a logical data warehouse will gain significant traction as a more flexible alternative for solving the data unification problem. Search technology is key for bringing together disparate data from data stores and silos across the organization – without having to build a data lake. Adoption of unified insight engines will be on the rise in 2917, which will allow companies to access and quickly gain insights from the content buried in their vast unstructured data stores.



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