Today, pretty much every decision – from the shows your streaming service recommends to the price you pay for lunch – is decided by algorithms crunching significant amounts of ones and zeros.
And there’s plenty of data around to fuel these decisions, too. The stuff is everywhere, with each of us leaving a trail of it behind that informs how businesses can use that data to impact their strategies and efforts. From social media activity, to form fills, to purcahse history – these day to day activities fuel data use cases such as customer experience, supply chain logistics, and fraud detection.
This data enables forward-thinking organizations to deliver the personalized products and services that keep people coming back for more. And a data-driven approach to operations can lead to significant competitive advantage.
That’s why 94% of enterprises today say that data is essential to business growth. But how many are really putting their data to work?
The truth is, around 63% of organizations claim they can’t derive insights from big data at all. And those that can, often find the process complex, costly, and time consuming.
Big data’s big problem
When it comes to turning data into insight, organizations often fall at the first hurdle – way before any analysis can even take place.
Consider for a moment, that around 2,000,000,000,000,000,000 bytes of data are produced every single day. Now consider that this data comes from various locations, is presented in different formats, and subject to various business rules. How does one begin organizing and structuring that data for analysis?
If you think that sounds like a Herculean task, then you’re not alone. We recently surveyed over 450 enterprise data professionals to try and understand their challenges in this area. What was clear is that they all understood the inherent value data presents – but most think it’s taking them too long to generate insight.
Of these professionals, 66% believe their organization is wasting time on data preparation. And 44% worry about dealing with the diversity in the types of data they work with.
Both of these things can dramatically slow time to insight. And the problem with moving slowly is that the world no longer does. Quite simply, these are problems that must be overcome.
Accelerating speed to insight
At Matillion, we see these problems all the time. We work with clients across all industries to help them gain control of their data; extracting, transforming, and loading it into cloud data platformsso it can deliver the timely insights that make a measurable difference.
For example, we recently worked with Novartis Oncology – a company dedicated to transforming the lives of people living with blood cancers – to help bring data-driven insights to its marketing, sales, digital, analytics, and data science departments.
The company previously had trouble scaling to meet the demands of its business, and would spend days preparing large data sets for analytics. (Sound familiar?)
Now, using Matillion for Snowflake, runtimes have been reduced by as much as 80 percent, and Novartis can build data pipelines and data marts for analysis in a matter of hours.
The company’s Director of Data Platform and Visual Analytics, Pushpendra Arora, described the platform as “the foundation for business transformation in US oncology.”
You can learn more about this kind of work, here.
Building your own foundation for change
Everyone’s data journey is different, but there are best practices and leading solutions that can give everyone the best chance of achieving their data-driven goals.
If the things we’ve talked about in this blog struck a chord, you’ll be interested to know that maximizing speed to insight is going to be one of the key topics at this year’s Matillion Data Unlocked, the flagship virtual event for data professionals.
To learn more about the tools and techniques that can help you unlock the potential of cloud data and improve the productivity of your data team, you can register for the event here.