Centralized Data Will Push Cloud Adoption into “Hyper-Drive”

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daniel freemanIn this special guest feature, Daniel Freeman of Sumo Logic explores the premise that a centralized data model will become the “new” normal, and companies who are slow to transition will find themselves buried beneath their own data. Daniel Freeman is VP of Marketing at Sumo Logic, a company specializing in transforming Big Data logs into new sources of operations, security and compliance intelligence. Daniel brings over 15 years of enterprise software experience from various industry segments including, Internet security, enterprise collaboration and software developer tools.

Cloud services have seen immense adoption over the past few years and will be a $76 billion market by 2017, according to IDC. But the next level of growth will be determined by two factors: modernization of the technological backbone underlying cloud services and a shift away from fragmented data sets to a centralized utility model that houses all of an enterprise’s data. This is because the next level of growth will be dependent on analytics, and the speed and variety of analytic services that will be offered in the cloud. Only when all of a company’s data can be accessed at one time will adoption of cloud-based analytics be kicked into hyper-drive. Having all of a company’s data in one centralized model will allow for analytics capabilities that were previously unheard of— comparable to how the modern power grid enabled the rapid growth of the industrial age.

What Companies Are Missing in Today’s Data Analytics

With many of today’s analytics services, visibility is limited to one environment per solution and IT rarely gets a vision of how they interact with each other. Given the proliferation of these data sources and increasingly complex interactions between them, understanding these event relationships is fundamental to optimizing customer interactions, business processes and security procedures. This means that enterprises are currently missing out on valuable information by not understanding the causal relationships between events. It’s predicted that there will be a ten-fold increase in the number of cloud-based solutions targeted to IT in the next five years; the resulting competition will create a perfect storm of innovation in a moment where change is sorely needed.

Why Companies Need to Change their Approach to Cloud and Data Consumption

While enterprises manage their data sets separately in their current data models, soon that won’t be possible. As the underlying IT infrastructure grows increasingly complex and streams of machine-generated data increase 15 times by 2020, Big Data and DevOps technologies are reaching critical mass. If companies attempt to use their old legacy models for storing data in the coming years, the real benefits of cloud-based analytics cannot be realized. Traditional mechanisms for deriving insights from data are not built to sustain real-time visibility at scale, and intermediate solutions have so far failed to provide a unified view or to be cost-effective. With more than 2.5 exabytes of data already being generated daily, companies must deviate from the status quo in 2015 or risk losing the insights their data has to offer as they make strategic decisions.

There’s No Turning Back

The rising tidal wave of data pushed forward by the cloud economy can’t be held back, nor will it recede. As enterprise demand for intelligence grows, leading-edge providers will emerge to deliver scalable and reliable applications and services across the private and public cloud. For those that don’t sign on, data bloat will slow their rate of progress and access to data-driven insights. It will become impossible for decision makers to glean insights from the mountains of machine, transactional and customer data, or to take actions that improve outcomes. In 2015, a centralized data model will become the “new” normal, and companies who are slow to transition will find themselves buried beneath their own data.


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  1. Nice article Daniel,

    Products such as iPaaS will become more important in this space, especially those providing Master Data Management and Modeling capabilities.