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Perspectives

Cloud and data analytics clearly joined at the hip

Deloitte on Cloud Blog

The reality is that if analytics are in your near or long-term future of dealing with enterprise data than cloud is probably the analytics solution you’re seeking, or at least the core platform.

October 11, 2018

A blog post by David Linthicum, managing director, chief cloud strategy officer, Deloitte Consulting LLP

In an April 2018 survey of 500 analytics and business intelligence professionals worldwide conducted by MicroStrategy, it was found that 24 percent of respondents said that cloud computing is the technology that is most likely to impact their analytics initiatives over the next five years. Moreover, one-fifth of respondents who cited big data and artificial intelligence (AI) technologies as a core driver.1

The writing is on the wall for enterprises. For marketers, for example, outdated technology often stands in the way of getting insights on customers in meaningful ways. In fact, in a July 2018 survey of 560 marketing professionals worldwide conducted by Harvard Business Review Analytic Services, 36 percent of respondents said that legacy systems were one of the biggest roadblocks.2

They view these systems as preventing them from implementing real-time analytics to get the customer insights they needed. Moreover, a third of respondents also reported that data silos hinder their progress, with the data needed to do the proper analysis often inaccessible.

Cloud computing becomes a force multiplier in this space to address many of the problems found in the survey, including:

  • The core consolidation and integration of data. Cloud computing provides an inexpensive way to both consolidate, improve, and integrate data into analytics. Moreover, the number of databases that are available on premises that can be found in the cloud is numerous, as well as cloud native public cloud databases such as AWS’s RedShift.
  • The use of machine learning and other AI technology. When machine learning is bound with data the potential of those driving analytics to gain better insights into that data is greatly improved. Indeed, AI provides the ability to learn from patterns and now static streams of data, so making your analytics systems think are a part of cloud-based data analytics.
  • The use of big data in the cloud makes the use of larger distributed databases that are able to leverage both structured and unstructured data affordable. Hadoop systems that would cost millions in hardware and software if done on-premises could be a fourth of that cost in the cloud, depending on the cloud provider and service you’re leveraging.

The reality is that if analytics are in your near or long-term future of dealing with enterprise data then cloud is probably the analytics solution you’re seeking, or at least the core platform. With the core analytical capabilities that cloud platforms provide, it’s not only a game changer, but enables deep analytics for enterprises that could not normally afford the use of this technology.

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