Taming Big Data Complexity With Automation

A new QuoCirca report reveals why data automation is imperative to successfully manage the explosion in data volume, velocity and variety.

Yann Guernion
Yann Guernion, April 21, 2016 1:45 pm
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To understand the explosive impact of Big Data on organizations, you need look no further than the automotive industry. Autonomous, self-driving vehicles are just around the corner; the typical in-car entertainment system now creates more than a gigabyte of data every day and the in-car behavioural data collected by the vehicles themselves is expected to be a goldmine for organizations everywhere. We’ll soon be driving data not a Dodge or a Daihatsu.

This is the age of Big Data and the Internet of Things (IoT)—and organizations need to get ready to manage the scale and complexity of this explosive data growth.

This is the core theme of a new study by QuoCirca, a primary research and analysis company. In Taming Big Data Complexity Through Automation, QuoCirca argues that organizations need the appropriate technologies in place to cope with the volume, variety and velocity of data. Without the right tools, organizations will be unable to extract the right analytical data for decision-making.

The QuoCirca report initially highlights the difference between Big Data and ‘a lot of data’. Organizations with large, formalized databases do not necessarily have a Big Data problem. True Big Data issues arise where there are multiple different sources of data that need to be brought together for analytics purposes.

QuoCirca also emphasise where that explosion of Big Data is coming from: The IoT and the Internet of Everything (IoE), both of which may result in millions of devices connecting to an organization’s networks, each generating data of its own variety, at its own volume and velocity. Security systems, cameras, biometric devices and sensors, for example, running via Ethernet to central monitoring systems. Or production lines with sensors, actuators and other devices attached to the network.

Ensuring this data is dealt with effectively demands accurate and effective data discovery along with extraction, transform and load actions, as well as automated data movement. Attempting to deal with the IoT/IoE without automation, QuoCirca argues, will be doomed to failure.

The role of Data Automation

The answer lies in data automation. Processing large estates of disparate, dispersed data manually is not only slow and expensive—it’s prone to error and delay. Automation minimizes errors and enables organizations to achieve the scalability needed to fulfil the demands of Big Data processing. The bottom line is that more actions can be carried out and data accessibility improved for all users.

According to QuoCirca, this data accessibility should be the prime objective. Users require access to the data they need to make better decisions—from the shop floor to the boardroom. Decisions will be more accurate and outcomes more valuable. Individuals can concentrate on being ‘data savvy’ rather than ‘data intelligent’—the complexities of the underlying data sources and structures can be hidden from the users.

The report also recommends the use of templates and function libraries to empower users. Together, they make it easier for users to deal with complex data actions. Enabling power users to create and share additional templates and functions, for example, allows the organization’s domain expertize to be improved through data automation. Moreover, drag and drop user interfaces can make life easier for non-power users wanting to leverage existing templates and functions as well as create their own.

The QuoCirca report also highlights how automation can help transform internal and external processes. By ensuring that data is accessible, securely available and easily movable, organizations can optimize their business processes—everything from internal processes to the value chain of suppliers, customers, contractors and partners. The bottom line is increased agility, flexibility and improved analytics for ‘over the horizon’ thinking.

Democratization of Big Data

Make no mistake, data automation is a business imperative. Organizations face growing data volumes in multiple varieties, with the IoT/IoE driving the stream velocity of data. Meanwhile, users require instant availability of data for analysis and decision-making. Against this backdrop, the true value of data can only be extracted and managed using intelligent and advanced data automation.

Instead of a search for the mythical ‘data scientist’, QuoCirca argue, organizations should focus on data accessibility for all. Democratization of data accessibility will drive an organization’s decision-making capabilities, and streamline internal and external processes. It will enable intellectual property to be more accurately discovered, stored and distributed. It will build an organization’s wisdom, enabling it to be far more competitive within its markets.

Neglecting data automation will have strong adverse impacts on an organization’s capabilities to compete in today’s disruptive markets.

To find out more about how your organization can drive competitive advantage by automating their IT and business systems—from on premise to the Cloud, Big Data and the IoT, click here.

Taming Big Data Complexity Through Automation

Workload Automation
Big Data
Data Automation
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Yann Guernion

Yann Guernion

Yann Guernion is Product Marketing Director at Automic Software. With over 25 years of experience in the world of IT, Yann has a wealth of expertize in managing the entire product line lifecycle.