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Redefining business intelligence to unleash value from big data

Bruce Dahlgren, Senior Vice President and General Manager, Enterprise Services Asia Pacific and Japan, HP | Oct. 29, 2014
Hewlett-Packard’s Bruce Dahlgren explores how enterprises can unleash and harness the immense value of big data quickly, on a sustainable basis, and without a huge upfront investment.

But by taking an 'as-a-service' approach, changes can be implemented without costly upfront investments, regardless of where an organization is in the transformation journey.

There are three core elements to a successful business intelligence modernization strategy:

  1. Discovery environments that address how to bring data to a broader workforce or employee base so that they can make data-driven and agile decisions. Environments include data lakes - storage repositories that hold raw data in its native format until required - data visualization tools, and services that enable rapid, enterprise-wide data sharing and analytics collaboration.
  2. Analytics solutions to support specific needs to run the business more efficiently, whether it be helping customers build something or making targeted improvements.
  3. Hybrid data management services to enable enterprises to pursue business innovation through industrial scale analytics. This is integrated into business processes and systems to leverage all relevant information, whether it is from within the organizations' transaction systems, social, sensor or streaming data.

Key to achieving early milestones

By pursuing an 'as-a-service' approach enterprises are protecting themselves against infrastructure obsolescence.

If the approach is flexible and open, it can combine the best of an organization's existing business intelligence investment with the latest innovations in analytics to deliver real business value.

Such a flexible consumption model enables organizations to quickly capitalize on business opportunities made possible by both traditional and new forms of data.

Modernization can begin immediately and important milestones reached early in the journey.

Setting up a discovery environment in the data lake, for example, can take as little as two weeks, especially if using the cloud, followed quickly by new analytic solutions in an incremental manner.

This 3-step approach minimizes the risk of a big-bang transformation and associated costs. By 12 to 18 months a rock-solid, data-driven BI environment can be operating with greatly improved total cost of ownership and service level agreements.

Counting the benefits

A BI modernization program that combines software, hardware and consulting services can deliver lower, predictable costs and an increased ability to build enterprise-wide capabilities and differentiation. The transformed environment will support\

  • Data sharing across the enterprise to empower the workforce and spur innovation.
  • New insights through embedded analytics to improve operational and decision-making processes and to provide integrated guidance real-time.
  • Risk mitigation through quick start options involving discovery environments and as-a-service deployment models.
  • Business agility to improve competitive advantage and customer interactions.

Mastering big data on an industrial scale

As the amount of data continues to grow, it's imperative that organizations improve their data processing abilities.

By pursuing BI modernization with a strong emphasis on 'as-a-service', enterprises can protect themselves from infrastructure obsolescence and avoid major upfront investment.

Unleashing the power of data through industrial scale analytics and data-driven insights will allow them to optimize nearly all areas of operations.

This is the key to the next wave of business innovation.

 

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