Unstructured Data Analytics

Technologie   |   Bertrand Cariou   |   31. Okt. 2022

Culling complex data for new insights from unstructured data analytics

In recent years, unstructured data analytics has soared in popularity due to the increasing availability of complex data sources, such as web logs, multimedia content and social media data. In raw format, semi-structured data sources often output in JSON or XML format, while unstructured data has its own internal structure, but doesn’t conform neatly in a database. In both cases, semi-structured and unstructured data sources are challenging for nontechnical business users and data analysts to unbox, understand, and prepare for analytic use, which is the fundamental challenge of unstructured data analytics. How can these non-technical users truly undergo unstructured data analytics without dependence?

Designer Cloud Enables Unstructured Data Analytics

With an intuitive interface, Alteryx Designer Cloud empowers non-technical users to interactively explore and prepare these complex data sources themselves in order to execute data analytics. At Designer Cloud, we call this process “data wrangling,” and it is a critical first step in order to generate the right outputs for unstructured data analytics. Not only does Designer Cloud truly empower users to work with unstructured data, but it allows users to combine that data with more traditional sources, such as social media with CRM data, for example. No matter the complexity and variance, Designer Cloud empowers users to take leverage the data they need early on in the data analytics process.

The Royal Bank of Scotland

At a leading European financial institution, unstructured data analytics was essential in better understanding customer behavior. From the XML source, they needed to extract the content from approximately 200,000 web chat conversations per month (what was actually said by the customer and operator), the metadata (time stamp, browser information, etc.), the survey data that customers completed, as well as who the operator was. Without Designer Cloud, this organization was only able to process around 3% of all web chats. Once they began using Designer Cloud they were able to process 100% of their web chats. This allowed them to optimize their processes and direct their customer service agents on how to best interact with customers online. Designer Cloud also reduced time spent on data preparation by 15 times.

Gain valuable new data insights on customer behavior by using Designer Cloud. Try out Designer Cloud and how you can transform complex data sources for unstructured data analytics.