Data is the new oil…the hottest thing since sliced bread… the lifeblood of modern enterprise… it’s many things and the cliches will continue - but the thing that data most commonly is - a challenge.
This challenge is also the one worth solving as the gains are significant and there’s really no choice but to solve it if you want to remain competitive into the future. So why is it so hard?
As board rooms around the world will confirm, it isn’t for vision, will or investment - the challenge is more practical.
Organizations need a way to safely and securely use their data. Often, data is locked up in siloed systems and might not be used due security or privacy concerns, or simply because it is difficult to connect and enable access to the data. Source systems are typically record based and don’t allow you to safely combine data and get a holistic understanding across all of the enterprise. To add to the challenge, making the data operational (so you can use it) is often a major obstacle.
The next consideration is quality - how accurate, unified, consistent, reliable, timely and trusted is the data. To answer these questions, you need to be able to understand the context, source, and provenance of the data, along with any use restrictions or sensitivity indicators. Some datasets might be high quality but not ‘usable’ e.g identity and access management data is often excluded due to challenges in maintaining privacy and security. Other data sets might be usable but lack quality so trusting it becomes impossible.
A strong data governance framework can make a significant difference here, provided you have the tools that can meet your requirements for trust, while also providing the necessary controls for ensuring appropriate and safe use of all data types.
Getting value from your data
Data is often thought of just in terms of analytics and insight, and while this is a powerful application, data can also drive value in many other ways through the creation of high quality data products. These are curated sets of data, packaged in a way to be consumable throughout the organization for a number of different use cases. It could be monetization - the selling of certain data sets (e.g. machine performance or geo-tracking of purchased products) to customers, or session or behavioral data that can enable interactive products to create more personalized customer journeys.
One customer recently told us that in their global manufacturing business, there are more use cases for high quality data products than they could have imagined.
Overcoming the data challenge: capture, connect and control
To enable high quality, trusted and usable data, businesses require enterprise-wide strategies that expand far beyond traditional approaches and thinking.
Trust starts at data capture. Leveraging an identity-centric data unification platform like IndyKite’s, allows you to capture data from across the organization, connect and enrich this data into a knowledge graph full of insights and control the use of this data to build better applications and services.
The Identity Knowledge Graph unifies data into a contextualized data layer to provide a 360° view of your customers and data across the enterprise. You can then leverage this unified data view to build visibility of your data landscape, understand what data is approved for use in applications and services and drive trust with your data consumers and application builders.
Granular controls ensure the delivery of the right data to the right hands, at the right time. This provides the security that certain data types require, as well as the flexibility and controls to enable high quality data products to drive growth at your organization.
Organizations that can do this will be the winners and will drive a whole new level of personalized services and revenue generation.
To learn more, check out the webinar Building high quality data products: The PACCAR perspective
