How to get the most out of your BI analytics investment
Companies looking to select the right business intelligence (BI) tool need to identify the degree of data analysis they need, how much technical expertise they have in-house, and work out whether they want to integrate existing platforms.
That’s the conclusion from a study conducted by B2B research firm Clutch.co analysing how organisations are attacking their BI strategies.
70% of the almost 300 employees polled – who use BI data analytics tools in their work – said they believe their company maximises the value of its BI data, while a similar majority (65%) believe that structured data is more valuable than unstructured. This point does come with a caveat – the analysts note that it is ‘easy’ to imagine the value of unstructured data surpassing figures locked in databases as technology improves. “Once we get there, we will see huge adoption,” said Dean Abbott of SmarterHQ. “There’s incredible information in text. It’s just difficult to get to now.”
The majority (70%) of businesses polled say they use internal data most frequently, followed by business systems data (59%) and structured data (58%). Social (38%) and Internet of Things (26%) fared less well. Perhaps not surprisingly, respondents argued that business systems data was the most valuable – 65% compared with IoT (18%) and social (17%).
So with these data trends in mind, what is the best route for organisations to go down? Clutch groups BI data analytics tools in three different categories; BI solutions, which are basic analytics tools; self-service solutions, which allow more advanced users to analyse data without relying on IT support; and advanced analytics solutions, which is the realm of the data scientist. The analysts argue that creating a clear data strategy before investing in BI tools, as well as establishing appropriate metrics, will help you come to the right decision.
“What makes data valuable is what you do to it,” said Abbott. “It’s not the data that you collect that’s most important. It’s the data you create. It’s how you transform the raw data into meaningful new data elements.”
You can read the full research post here.
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