Key Benefits of Heterogeneous Analytics Compared to Traditional BI
This blog examines why traditional BI is becoming increasingly ineffective and how heterogeneous analytics can solve business problems with analytics.
By Simon Moss, CEO of Pneuron.
In today’s competitive environment, enterprises require fast, effective and agile business solutions. In other words, not traditional business intelligence. While the process of building analytics is certainly more affordable today than it was 30 years ago, buyers still aren’t satisfied with the quality of what gets delivered. No matter what tools are used -- Oracle 1.0 nearly 30 years ago or Hadoop Cassandra now -- the way we design, build and deploy has not changed. Meanwhile, projects continue to pile up and we now have a trillion-dollar backlog in application projects.
However, there is hope on the horizon: Data scientists and IT leaders are at last able to offer a new type of solution based on heterogeneous analytics. By definition, this technology is the ability to mix and match diverse analytical capabilities in the same workflow - at will - to accelerate rich solution build-outs and leverage accessible analytical assets.
The key benefit of heterogeneous analytics is that it helps businesses avoid wasting resources on technology that has little to no return on investment. Instead, by focusing on the desired business outcome first and working back to solve the problem with well targeted analytics, users eliminate the lag time and high costs associated with traditional approaches. In essence, solution architectures align to the solution requirements and available assets in the environment rather than the arbitrary boundaries created by various best-of-breed technology investments and centralized data models. Because heterogeneous analytics offer the ability to mix and match diverse types of analytics in a continuous, linked and highly productive manner, this technology approach can be deployed without traditional overhead costs. What’s more, heterogeneous analytics create a continuous flow of higher added value results with substantially lower degrees of “friction” between.
A key differentiator between heterogeneous analytics and traditional BI is the ability to rapidly deploy ideas into solutions, adapt to changes in the environment and maintain flexibility of one’s various assets. For example, native capabilities plus imported capabilities (like PMML Predictive Models and Java code) or “called” capabilities like Hadoop or Python can all be easily mixed and matched in a given workflow:
Savvy IT leaders and data scientists should consider deploying heterogeneous analytics to help enterprises innovate, compete, react to the market, and ultimately succeed. As technology platforms proliferate, and as data becomes even more distributed, technology like heterogeneous analytics will become increasingly important for enterprises looking to truly innovate in an already competitive market.
Bio: Simon Moss is the CEO of Pneuron Corporation. Under his leadership, the company was founded, capitalized and the strategic platform developed, transforming Pneuron into a global technology provider. Simon brings over 20 years of successful strategic leadership at CEO, Partner and Board of Directors executive levels in the financial services industry, and has a proven track record as a successful entrepreneur.
Top Stories Past 30 Days