Rethinking how we think about self-service cloud BI
Every employee and every end user should have the right to find answers using data analytics. But the current reliance on IT for key information is creating an unnecessary bottleneck, says DataHero’s Chris Neumann.
“Self service” is a term that gets used a lot in the business intelligence (BI) space these days. In reality, data analytics has largely ignored the group of users that really need self service, even as that user base has grown. More than ever people realize the value of data, but non-technical users are still left out of the conversation. While everything from storage to collaboration tools have become simple enough for anyone to download and begin using, BI and data analytics tools still require end users to be experts or seek the help of experts. That needs to change.
Users should be able to get up and running on data analytics and connect to the services they use most, easily. More employees in every department are expected to make decisions based on their data, but that doesn’t mean everyone needs to be a data analyst or data scientist. Business users want to analyse data that lives in the services they use everyday, like Google Analytics, HubSpot, Marketo, and Shopify – and even Excel, and know the questions they need answered. What they need are truly self-service tools to get those answers.
Calls for change
While vendor jargon and the obsession with big data may be clouding the self-service cloud BI conversation, experts and enterprises are recognizing that things need to change. Leading analyst firms like Forrester and Gartner are recognizing that BI must evolve. When business users depend on IT teams to get answers, a bottleneck is created. End users are demanding tools they can use on their own without having to go to IT.
There are a number of vendors connecting to cloud services. But, connecting in a way that facilitates effective data analysis presents a myriad of additional challenges from navigating the sheer variety of formats to categorizing unspecified data.
At DataHero, we’ve built the requisite connectors for accessing the data within cloud services. We’ve also taken the next steps with a data classification engine that automates ETL and recognizes that what a cloud service might call “text” is actually an important field. In order to successfully integrate these connections, solutions must automatically normalize the data from disparate services, matching attributes and allowing the data to be combined and analysed. Without automatic normalization and categorization, self-service cloud BI isn’t possible.
The whole is greater than the sum of its parts
While self-service cloud BI is already possible, the users are often new to the world of data analytics. That means that the tools too must evolve as the users become more sophisticated and new possibilities emerge.
For example, without data analytics, a marketer might log into a Google Analytics dashboard, then MailChimp, then Salesforce to take the pulse of a marketing campaign. Each service provides its own value, but when combined the marketer can use a common attribute, like email address, and create a third dataset. What comes out of that is a much more pure answer to the marketers question: “how successful is my campaign?”
Google Analytics, MailChimp and Salesforce are a common combination but there are many combinations that may be just as valuable but have yet to be explored. With the proliferation of cloud applications, the possibilities are nearly endless.
The new users of BI and data analytics have also never had the opportunity to work with one another. To continue with the example, a marketer may have created the charts needed to monitor KPIs and put them into a dashboard, but these KPIs need to be shared with internal teams, clients and executives. Reporting is normally a one-way process when it should be iterative and collaborative and allow clients and executives to provide real feedback on the most up-to-date numbers.
The consumerization of BI
BI and data analytics have largely missed the consumerization of IT trend, despite industry-wide use of the term self service. That doesn’t mean that change isn’t coming. The shift to the cloud is continuing to accelerate and the emerging self-service cloud BI space is quickly heating up, driven by user demand and a need to decouple analytics from IT.