In Support Of Digital Transformation: Transforming Data Management Architecture And Solutions

Dan Vesset

Increased digitalization of processes, things, and human interactions; availability of higher-performance technology platforms; and cloud, data, and analytics services: These developments have ushered in opportunities to digitally transform the enterprise. Business and IT executives are increasingly looking to technology not only to improve cost control through efficiency and productivity gains, but also to drive revenue, accelerate innovation, and improve the ability to fulfill their missions.

Data as an asset

As information is at the core of the new digital ecosystem, enterprises must begin to treat data the way they would treat any other asset. They must invest in technology and people to distill insight into value and establish organizational competencies and capabilities focused on leveraging data. This trend is not about Big Data. The “bigness” of data is a topic that does not necessitate repeating. To harness all the data, enterprises will need to develop a digital transformation (DX) platform.

But isn’t this a refrain that has been heard for years — leverage your data, compete on analytics, and become data-driven? Not exactly! As DX takes hold, organizations are facing more complex ecosystems and business environments within an expansion of data characteristics, behaviors, domains, social contexts, and environments. Data complexity also grows along with volume, dimensions, timeliness, multi-channels, motion, heterogeneity, structures, distribution, or availability.

Urgency to act

A comprehensive intelligence vision is needed to start the journey of addressing this data complexity. And there is an urgency to act on this need and start (or continue) the digital journey.

According to McKinsey:

In less than a decade, new digital entrants have already seized a significant share of revenue across regions and industries — 17% on average. While digital entrants hold “only” 17% of total global revenue, they own 47% of digital revenue.

How you build your intelligent core, including its data management capabilities, will determine your ability to transform and compete (or fulfill your mission) effectively. As the foundation of the DX platform, the intelligent core is not “simply” a technology modernization exercise. Evidence already exists of key value to be generated:

  • Drastic improvement in developer productivity and ability to rapidly deploy new intelligent applications — that combine code, algorithms, and data — at the request of business users
  • Elimination of the distinction between transaction processing and analytic applications in the context of real-time operational workloads
  • Enhanced data trust and integrity leading to more pervasive use of enterprise-wide analytic assets
  • Exponential expansion in the number and types of decisions that can be automated
  • Support for new co-innovation efforts to drive business model transformation
  • Generation of new financial returns either directly or indirectly from data, a.k.a. data as a service

Critical self-assessment

The time to act is now. However, the journey to DX winds along different paths depending on the starting point; general advice to digitally transform is not actionable. Selecting the right path requires a critical self-assessment of your enterprise’s current data and information capabilities and a vision for evolving transformation. IDC’s research identifies three categories of enterprises:

  • The enterprises in the first category are seeking to transform their existing (often legacy) data management architecture and solutions. They are hampered by siloed data management technology that lacks the scalability and performance to process the volume, variety, and velocity of data created within the enterprise or by the ecosystem of external data sources.
  • The enterprises in the second category are looking to expand on the recently deployed new generation of data management technology and ensure integration with internal legacy systems as they proceed on their way toward more comprehensive transformation of their data management capabilities. These organizations have experienced project-level data management success that has led to tangible business benefits, including initiatives of data monetization.
  • The organizations in the third category have already made a substantial investment in a new generation of data management. These enterprises have experienced success in integrated legacy and new technology and, furthermore, have achieved business value from such investments in discrete areas of the enterprise. If your enterprise is in this category, it is now time to expand on early successes by enabling an ever-growing number of internal and external stakeholders with innovation accelerators, such as artificial intelligence (AI), that are made possible by the new data management solution.

Source: IDC

Regardless of where your enterprise stands, there is also a need to reframe the data management strategy. For years, IT leaders’ efforts have focused on improving the efficiency of managing the three V’s of Big Data: volume, velocity, variety. A new approach is needed where attention must turn to the three A’s — awareness, augmentation, automation — the essential elements of a comprehensive enterprise intelligence vision. A critical step in the journey to achieving this vision is to reorient the existing information management and analytics architecture toward specialized (and optimized) capabilities that leverage a broad range of data management, governance, integration, integrity, and analytics and data services.

Intelligent data orchestration

These capabilities will manifest themselves in a new architecture that intelligently orchestrates data across a network of core and edge entities (machines, things, humans, apps, bots, data stores) connected via data pipelines, where the intelligence will be derived from machine learning–based constant monitoring, diagnostics, prediction, and prescription. These capabilities will form the basis for comprehensive awareness about the state and events affecting your enterprise from within and outside They will enable augmentation of human decision-makers with machine-generated recommendations and will allow for deployment of adaptable, self-learning decision automation solutions.

Whether you’re just stepping on the starting line or approaching another turn on the journey of digital transformation, consider the impact that the foundation of an evolved data management architecture and platform will have on the chances of your enterprise to succeed.

To help you assess your organization’s current data and information capabilities and identify the opportunities and challenges posed by your particular digital transformation journey, IDC and SAP have developed three maturity models based on the categories above. To access these reports, please click here to register.

Dan Vesset

About Dan Vesset

Dan Vesset is GVPGroup Vice President, of Analytics and Information Management at IDC. Vesset’s research and consulting is currently focused on business analytics, business intelligence, and data warehousing software markets. He is also the co-lead of IDC's Big Data research. Vesset has authored numerous research publications, is a frequent speaker at business analytics conferences and seminars worldwide, contributes to IDC’s Business Analytics and Big Data blog, and tweets at @danvesset.