04 / 14 / 14
Cloud Adds a New Dimension to Data Analytics                                                                                                                                                                                                                                                                                   
A major global shipping company is saving millions of dollars per year with insights into fuel usage patterns on its ships. A new startup pours through 30 years’ worth of weather data at sub-zip-code levels to provide agricultural customers with accurate forecasting. A new service provides analytics to entertainment companies on what types of music their customers are listening to.
For these organizations, building a scalable data analytics platform is essential to their business growth, and it is delivering tangible benefits, from opening new business lines to significant cost savings. Cloud computing is making these large-scale analytics possible.
In an intensely competitive global economy, analytics offers ways to run a business smarter than ever – predicting customer demand, competitors’ moves, and even trends in internal operations. Analytics can also be employed to prescribe possible solutions to situations that are uncovered.
But this capability brings on enormous amounts of data from a variety of sources. It’s often called “Big Data,” but the term doesn’t adequately describe the value and opportunity such information and insights offer to decision makers.
Data streaming in from a range of sources – from transactions, production systems, sales systems and financial systems – has long been the lifeblood of organizations. Now, new types of data are also entering the corporate mainstream. The data may be non-traditional, “unstructured” data, such as that generated by machines, or by humans. 
There’s a lot of innovation taking place with this information. But to really capitalize on data to achieve innovation, enterprises need to run powerful analytics, as well as to be able to manage, process, store and back up all this data. Traditional data systems are no longer up to the task. As data volume keeps growing, the typical – and perhaps, until recently – the only way to keep up was to simply keep buying new servers and disks to store these growing volumes.
Cloud operations and log management software offers a smarter, cleaner and more cost-effective way to handle the data analytics opportunity. Perhaps even more importantly, it is a powerful source of insights on many levels for decision-makers.  The ability to collect and analyze this data (such as application logs, network traces, configuration files, messages, performance data and system state dumps) provides visibility across the enterprise.  Enterprises also can integrate unstructured data (such as log files) with structured data (such as metrics and key performance indicators) to move their businesses forward.
Cloud-based storage frees up enterprise end-users to take advantage of pooled storage space to support any and all new data sources. If storage resources are also made available from public cloud services, this capacity is almost limitless in terms of supporting any and all data sent to it, and is available on a global basis. A private cloud, while ensuring greater security and control, takes advantage of data center consolidation and virtualization to provide any and all resources needed.
Cloud provides all the power needed, on demand, to analyze massive amounts of information in real time.  It alleviates the storage crunch that organizations often encountered within their siloed enterprise architectures. Importantly, the availability of cloud-based storage and analytical processing resources also allows for more frequent, and rapid experimentation. Many of the business game-changing data analytics that are now seen today – such as those described at the beginning of this post – started out as pilot projects or experiments by someone within the business, who was able to quickly provision the resources needed from the cloud, without the fuss and muss of attempting to reserve compute resources for their projects. Such experimentation is constrained, however, if IT systems are constrained by insufficient storage, processing power, or memory. With that, a major roadblock to innovation is removed.
Joe McKendrick is an author, independent researcher and speaker exploring innovation, information technology trends and markets.
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For more thought provoking cloud management insights visit vmware-erdos.com.
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Cloud Adds a New Dimension to Data Analytics                                                                                                                                                                                                                                                                                   

A major global shipping company is saving millions of dollars per year with insights into fuel usage patterns on its ships. A new startup pours through 30 years’ worth of weather data at sub-zip-code levels to provide agricultural customers with accurate forecasting. A new service provides analytics to entertainment companies on what types of music their customers are listening to.

For these organizations, building a scalable data analytics platform is essential to their business growth, and it is delivering tangible benefits, from opening new business lines to significant cost savings. Cloud computing is making these large-scale analytics possible.

In an intensely competitive global economy, analytics offers ways to run a business smarter than ever – predicting customer demand, competitors’ moves, and even trends in internal operations. Analytics can also be employed to prescribe possible solutions to situations that are uncovered.

But this capability brings on enormous amounts of data from a variety of sources. It’s often called “Big Data,” but the term doesn’t adequately describe the value and opportunity such information and insights offer to decision makers.

Data streaming in from a range of sources – from transactions, production systems, sales systems and financial systems – has long been the lifeblood of organizations. Now, new types of data are also entering the corporate mainstream. The data may be non-traditional, “unstructured” data, such as that generated by machines, or by humans. 

There’s a lot of innovation taking place with this information. But to really capitalize on data to achieve innovation, enterprises need to run powerful analytics, as well as to be able to manage, process, store and back up all this data. Traditional data systems are no longer up to the task. As data volume keeps growing, the typical – and perhaps, until recently – the only way to keep up was to simply keep buying new servers and disks to store these growing volumes.

Cloud operations and log management software offers a smarter, cleaner and more cost-effective way to handle the data analytics opportunity. Perhaps even more importantly, it is a powerful source of insights on many levels for decision-makers.  The ability to collect and analyze this data (such as application logs, network traces, configuration files, messages, performance data and system state dumps) provides visibility across the enterprise.  Enterprises also can integrate unstructured data (such as log files) with structured data (such as metrics and key performance indicators) to move their businesses forward.

Cloud-based storage frees up enterprise end-users to take advantage of pooled storage space to support any and all new data sources. If storage resources are also made available from public cloud services, this capacity is almost limitless in terms of supporting any and all data sent to it, and is available on a global basis. A private cloud, while ensuring greater security and control, takes advantage of data center consolidation and virtualization to provide any and all resources needed.

Cloud provides all the power needed, on demand, to analyze massive amounts of information in real time.  It alleviates the storage crunch that organizations often encountered within their siloed enterprise architectures. Importantly, the availability of cloud-based storage and analytical processing resources also allows for more frequent, and rapid experimentation. Many of the business game-changing data analytics that are now seen today – such as those described at the beginning of this post – started out as pilot projects or experiments by someone within the business, who was able to quickly provision the resources needed from the cloud, without the fuss and muss of attempting to reserve compute resources for their projects. Such experimentation is constrained, however, if IT systems are constrained by insufficient storage, processing power, or memory. With that, a major roadblock to innovation is removed.

Joe McKendrick is an author, independent researcher and speaker exploring innovation, information technology trends and markets.

________________________

For more thought provoking cloud management insights visit vmware-erdos.com.

#cloud management #Joe McKendrick #business #analytics cloud Posted 6 months ago
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