This was my 12th meeting with as many CDOs (Chief Data Officer) in the last five days, and one particular theme kept coming back in every conversation was – Data-Centricity. In the digital age, one is used to hearing terms like ‘customer-centricity’ and ‘personalization’. Thus, when I heard data-centricity coming up a number of times, understandably I was lot more curious and also confused.
We appear to be entering the era of the Datanomics, where most of what is done in business is tied to the creation and management of data. Thus, data and especially the actionable insights derived from it, have now become the dominant component of whatever products & services businesses provide to the marketplace, as well as staying on top of compliance and regulatory requirements.
One way of thinking about it is considering what would happen if you lose the software that you currently use to run your businesses. Chances are pretty good that you’ll be able to find new applications to replace the old ones. But lose your data and you’d soon go out of business. Data has become the lifeblood of organizations, whether that’s intellectual property, critical methods, system of records, operational data, and especially the actionable insights distilled from raw data that drives an organization’s strategic activities (both explicit and tacit knowledge).
As I engaged more with the CDOs, I realized they are re-engineering their agenda to cause a tectonic shift in traditional data management approach – moving the responsibility of data management considered purely as an IT’s only responsibility to create a platform and processes, where data is managed, governed and shared beyond the applications that created it. In essence, they are talking about data-as-a-service (DaaS).
Imagine your data management functions offering elastic scalability, universal network accessibility, integration with mobile platforms, pay-per-use efficiencies, and the ability to work with widely scattered structured and unstructured data – these are foundational components of data-as-a-service.
From a layman’s point of view, DaaS consists of a combination of services – from Data Ingestion to Data Integrity to Data Storage Innovations to Agile Information Delivery and Data Governance. Traditionally, enterprises went about developing these services with an in-house and on-the-premise-centric approach and quite obviously, the focus was restricted to data within the firewalls. However, as the need for diverse sources of data became self-evident and data itself started to take more complex forms (volume, velocity, variety, veracity), these traditional approaches became increasingly difficult and expensive to maintain.
To overcome the constraints, it was quite natural for DaaS to adopt the cloud-computing model to make data readily accessible through a cloud-based platform, thus ensuring hassle-free supply of data, supply of analytical tools with which to interrogate the data (often through APIs and visual analytics techniques), carrying out the actual analysis and exchanging data with consumer communities.
Simply put, DaaS is a new way of accessing business-critical data, delivering information to a user, regardless of organizational or geographical barriers.