Understand your data: 4 key characteristics to optimize your business
The DXC Digital Directions series of papers provides insights into achieving new levels of innovation, productivity and investment as companies scale their digital efforts.
Read an excerpt below from the position paper, Accelerate your transformation to a digital business.
Understanding four key characteristics of your data is essential to optimize the digital platform and your business.
1. Data inertia
As the amount of data increases, particularly data generated by consumers, that data is more difficult and more expensive to move around.
2. Data gravity
More data attracts more users and hence more processing. In the future, these “users” will include AI and will demand new sources of computing power that are ever closer to the data.
3. Data decay
Data value can decrease over time. Data that decays rapidly must be processed quickly, often as soon as it is produced. (It does no good to process the frequent flier’s dinner order after the plane has taken off.) This also requires localized compute capabilities. Data that is no longer valuable (i.e., has decayed) can be archived in less-costly infrastructure.
4. Data location
Data must be secure, in motion and at rest, no matter where it is located. In terms of the physics of networking, distance always plays a factor in degrading performance. In terms of economics, processing data as close to the source as possible is cheaper. And in terms of regulations, there are constraints to moving data across borders. So, in those cases, data must be processed locally, and derivatives of that data can be aggregated and sent to a more centralized location for analysis that leads to critical business insights.
So how do modern digital platforms create dynamic information flows and markets with data that tends to become more inert, expensive to process and less valuable over time? Digital platforms increase internal and external connectivity, and they reduce data complexity through analysis, abstraction and automation. This increases data fluidity — ensuring that data is accurate, accessible and actionable. In turn, this enables the devolution or distribution of work and decision making, as our industry examples show.
With the incredible volume of data that is being generated, companies must transition from processes built for human speed to those built for machine speed. This is a step change. The digital platform must be able to support and scale machine-speed processes that leverage the explosion of data. To do this, companies must improve their agility and pace of IT service development.