What is Data Productivity
As the demand for data accelerates, enterprises must increase the productivity of their data teams. Which means doing more work, faster, with fewer resources.
The digital landscape has become a large, diverse and ever changing set of networks and assets. With that change comes the problem of organizational silos, along with the difficulty of making and implementing cross-departmental decisions.
Digital transformation has become a foundational expectation rather than speculation. As Gartner explains, "after digital transformation comes a time of value harvesting".
But the fundamental ingredient that underpins every single digital asset, and has the unique capability of unifying all those organizational silos, is data.
Frank Slootman asked, "What can you do with data in 20 seconds vs. 20 minutes?"
And the answer? You can do whatever your business processes permit you to do in that amount of time. There are a raft of opportunities, provided you have the ability to:
- Generate insights quickly from raw data
- Act on the insights before they become out of date
Value harvesting is the mature stage of digital transformation.
Changing and adapting business processes is core to digital transformation. In order to become data driven, processes must be slick and responsive, to take advantage of insights during their window of relevance.
Data as capital
In the digital economy, data takes its rightful place alongside human and financial capital as the means to grow and compete.
But just like crude oil and gold ore, raw data is not that helpful on its own. It needs refinement to become really useful. Thanks to digital transformation - and especially the rise of the public cloud - there are many different data sources, each supplying its own siloed data in many different formats. Siloed raw data doesn't link together naturally, and it's hard to read.
To unlock the capital, data needs to be consumable before business processes can take advantage of it. For data assets, refinement is known as data integration.
Data integration is much more than copying data from place to place. To begin, diverse formats need to be handled. Secondly, no business process operates in isolation.
Enterprises use an average of 212 SaaS applications, and the data from all those potential silos must be linked together to form a coherent picture. It all needs to happen in the cloud, and in a way that everyone can understand.
Digital transformation brings a constant stream of changes, so easy maintenance is a mandatory aspect of data integration. Data Productivity measures the ability of the data team to deliver quality and consumable data to the business quickly and reliably.
Thanks to the public cloud, organizations are collecting data from more applications than ever. And a simultaneous wave of innovation - especially open source - means data is arriving in many different formats. This is the contemporary data consumability challenge.
Legacy tools and methodologies are inappropriate in a cloud context. Enterprises have become limited by existing resources, practices and coding skills of their data team. Data projects don't deliver.
There is a common misperception that source data quality is poor, when in fact, it is simply hard to read and not linked together. This causes delays and gaps in the available insights. Ironically, often including a lack of insight into the performance of the original application itself.
Data productivity reverses this vicious cycle and represents a change in expectation. With a productive data team in place, the business can anticipate that answers will be available quickly enough. So it is worth putting steps in place to be able to act on those answers quickly.
Looking to the future, economists describe data as a "nonrival" asset. Meaning consumption does not reduce the quantity available. In fact, consumption of data generates more data. This is great news for those at the forefront of digital innovation: the opportunities for productive data teams are endless!
Find out more about Matillion Data Productivity Cloud and get started for free here.
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