Smart businesses are seeking out new ways to leverage the benefits of their big data analytics programs, and the self-service model is coming up trumps. By placing the onus directly on business users, enterprises are empowering customers with insights-driven dashboards, reports, and more. But it’s not the only bonus.
Arguably an even greater upside for organisations is that it alleviates the talent shortage that often comes with big data. With most companies only employing a handful of data experts who can deliver analytics insights to customers, the self-service model means they are freed up to concentrate on more important tasks, while allowing the masses to derive their own insights on their own terms.
What are the real benefits of self service?
If nothing else, a self-service model creates a ‘democratisation’ of big data, giving users the freedom to access the data they need when they need it most: during the decision-making process.
Moreover, there’s a low cost to entry – coupled with reduced expenses thanks to freeing up data science and IT resources – and faster time to insight. When users know what they need and can change their research strategies according to new and changing demands, they become more empowered.
But it’s not all smooth sailing – giving customers the tools they need for self service is only one part of the equation. They must also be educated on the potential pitfalls.
Avoid the common hurdles
When several users have access to specific data, there’s a risk of multiple copies being made over time, thus compromising the ‘one version of truth’ and possibly damaging any insights that could be derived.
Business users unfamiliar with big data analytics are also prone to mistakes, as they may be unaware of data-preparation complexities – not to mention their own behavioural biases.
For all these issues, however, education is the solution, which is what Ancestry.com focused on when it began encouraging self-service analytics through its new data-visualisation platform. And with 51 quintillion cells of data you can see why.
There’s no harm in starting small with big data analytics
Ancestry.com has over 10 billion historical records and about 10 million registered DNA participants, according to Jose Balitactac who is the FP&A Application Manager.
The old application they were using was taking hours to do the calculations. They looked at seven different applications before deciding on IBM Planning Analytics.
The reason they chose IBM Planning Analytics was to accommodate the company’s super-cube of data, other solutions would have required them to “break it into smaller cubes, or reduce the number of dimensions, or join members, such as business units and cost centers.” They didn’t want to do that because their processes worked.
They set up a test with IBM to time how long it took for the model to calculate and it took less than 10-20 seconds which is what they wanted. You can read more about the Ancestry.com case study here.
If you’re keen to empower your business users through a self-service model, contact Octane today to learn how we can help you harness big data analytics.