You may have heard the phrase “Data is the new oil” but like oil, data must be refined before it can really be useful.
Numeric data is easy to refine – you can add it, sort it, average it, and look for trends.
But what about text? How do you add words?
This + That = ?
80-90% of the data in most organizations is Unstructured Data such as emails, text messages, open ended comments from customers, reports, health records, images, and audio/video files to name a few.
Unstructured data tools help refine your data into something you can process easier and faster. It can help answer questions like:
- Who is talking?
- What are they talking about?
- How do they feel about it? (sentiment – positive, neutral, negative)
This information can then help you monitor your operations more effectively, build predictive models, perform tasks faster, and deal with data that would otherwise be too big to handle manually.
Text analytics is specialized software for unstructured data. It uses linguistic tools to extract meaning and the important pieces from your data as structured pieces which you can then use like numbers.
Speech to text converts your audio to text so you can run it through text analytics.
Some examples include:
- Voice of customer – process open ended comments in real time to address customer issues right away instead of once / quarter.
- Call center – 100% monitoring of calls to allow available management resources to focus in on the most important issues instead of monitoring 1-2% of calls at random.
- Manual review tasks – things like Medical coding which can’t be totally moderated could be sped up by first processing textual records with unstructured data tools.
- Legal and compliance – detect and correct issues in email and other company communications right away instead of finding the problems during a court case.
- Chatbots – handle more simple questions and collect intake information in a natural, conversational format allowing human agents to focus on more complex issues.
- Social media, news feeds and other data sources – monitor real time and get a digestible summary of the content and sentiment across all of that data. Can be used in applications such as competitive analysis or setting up predictive models.
- Images – use image recognition software to classify, compare, and search images. Like your own “google image search” for your image data. Speed up reporting of issues by taking a picture and processing it vs writing a report, detect maintenance issues, and audit access to buildings to name a few.
Unstructured data tools can help you get value out of data that is otherwise sitting idle in storage, increase the productivity of your manual data processing, build predictive models and use data in ways that are just not possible by hand.
>How much are you paying to store data? Are you getting anything out of it?
Please contact us to discuss your business and your data. We can identify specific areas where refining the data with unstructured data tools can increase your productivity, reduce risk, and unlock insights that may otherwise stay buried forever.