Analysts Don't See Great Value in New Data Types
According to new survey, data from research firm Clutch, most users of BI data analytics tools find traditional data types more valuable than new data sources. Is this really a surprise?
- By Lindsay Stares
- September 15, 2016
We're all excited about the potential in all the new data sources. Enterprises are using external, unstructured, social media data, and analysts are ... not that enthusiastic about it.
That's according to survey data just released from business-to-business research firm Clutch. Earlier this year, Clutch surveyed 291 employees who use BI data analytics tools for their jobs for their "2016 BI Data Analytics Survey." In June, Clutch released findings about the value of BI data, but the new report is all about analytics and new types of data.
New Data Sources Aren't Valued
According to this survey, respondents still use data from traditional sources much more than from new sources.
Seventy percent report using internal data, 59 percent use data from business systems, and 58 percent use structured data. Only 38 percent report using data from social networks, 37 percent use unstructured data (the same percentage uses external data), and a mere 26 percent of respondents are using data from the Internet of Things.
This pattern continues in the respondents' perception of what data is most valuable.
Asked whether internal or external data is more valuable, 65 percent answered "internal." The same percentage believed that business systems data is more valuable than social or IoT data.
A whopping 83 percent of respondents said that structured data is more valuable than unstructured data.
If you're reading the same industry news I am, this might sound crazy at first glance. IoT data, social data, and unstructured data -- these are supposed to be the big opportunities for growth, right?
Why So Negative on New Data Types?
It must have sounded odd to the writers of the Clutch report as well. The commentary in the report points out that the traditional data sources are more reliable, accessible, and easy to use with current tools, but in each case, the report also points out that the new data sources have value.
Even after over 80 percent of their survey population said that structured data is more valuable, the report states: "However, as technology improves, it is easy to imagine the value of unstructured data surpassing that of structured data."
Other studies have found significant value in new data sources, so it follows that Clutch would try to explain their seemingly anomalous finding. For one example, a recent study from The Aberdeen Group found that "companies using unstructured data frequently experienced a higher degree of user satisfaction with several key aspects of the data environment."
New Data Types Not Providing Enough Value Yet
Do they have to explain it? It's possible that the Clutch survey result says something about messaging. Those of us reading about the data analytics space every day are overwhelmed with articles about the value of new data sources, but it's possible the practitioners surveyed either didn't read those articles or didn't believe them.
After all, it's not stated in the report whether those saying a given type of data is "less useful" have had the opportunity to use it, or whether they tried and failed. If new data types are less reliable and more difficult to access, then it makes sense that people working in the space trust the data types that are, well, currently more trustworthy.
Further, the survey question appears to be framed as an either/or choice. It's possible that most respondents would say that both have value if asked even though they may have less experience with unstructured data, external data, or IoT data.
The takeaway isn't that analysts don't understand the value of new data types. It's that until our available tools and skills reach the same level as our aspirations for new types of data, these new sources simply won't provide as much business value as traditional sources.
Read all the new data and Clutch's advice on choosing a BI analytics tool on their website.
Lindsay Stares is a production editor at TDWI. You can contact her at firstname.lastname@example.org.