Adopting a hybrid data management approach

Companies such as Apple, Amazon, Google, Uber and Airbnb have shown how to build scalable data-centric foundations and disrupt traditional markets. Others will have to decide if they can lead as market disruptors or follow the leaders by perfectly executing their digital transformations to defend their market positions and extend their systems to new digital channels.

One critical step toward this capability is the establishment of a data-centric foundation using Hybrid Data Management (HDM). This approach is one that can scale with growing organization needs, enable innovation, increase agility, encompass ecosystem data, increase predictability, improve forecasting accuracy, detect new behavior patterns and deliver information insights in context to processes and applications.

Industrial-scale analytics

HDM combines the best aspects of traditional and emerging analytics — and delivers those capabilities in a flexible and cost-efficient as-a-service model. In essence, HDM is the foundation of a modern approach to Business Intelligence (BI) and involves optimizing traditional BI and data warehousing, blending in big data analytics, and embedding prescriptive analytics from both sides into operations and business processes. HDM provides a strategic direction for instituting industrial-scale analytics integrated into organization processes and systems that leverage all data and enable organizations to become data-driven and agile.

HDM fuses traditional and big data analytics, structured and unstructured data, data in the cloud and on premise, partner ecosystem data, and data from external sources; and encapsulates data services as APIs. It enables organizations to gain data-driven insights from new kinds and higher volumes of data, and to transform that information into tangible enterprise results such as optimized operations, new business models, and data-driven products and services.

That’s not to say that you should throw away your investment in traditional BI. BI, which is focused on corporate performance reporting, will continue to play a crucial role in most organizations. But with the emergence of new volumes and types of information — and the need for faster and more relevant insights — most organizations must evolve beyond those traditional capabilities to stay competitive. As most observers now recognize, traditional BI technologies and structures are simply not adequate.

IT leaders should leverage HDM to provide the infrastructure and tools needed to meet data analytics, operations improvement and customer engagement requirements, as well as to find the right balance between enabling the organization with industrial-scale analytic solutions and implementing those solutions quickly.

Read more in the position paper, Thriving on Enterprise Data and Analytics.

Dragan Rakovich, DXC Technology’s chief technology officer for Analytics, leads the company’s analytics technology and innovation strategy. Dragan brings strategic advice and thought leadership to customers in actionable analytics, business intelligence, machine learning, internet of things (IoT) and analytics platform domains to create advanced analytic solutions. Prior to this role, he served as Hewlett Packard Enterprise Services CTO for Analytics and Data Management. Dragan has more than 20 years of experience in analytics, business intelligence, management consulting, solution delivery, enterprise architectures and software engineering. @AnalyticsCTO


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