Operational Big Data

ORIGINAL ARTICLE

According to a recent report from Accenture, “Big Success From Big Data,” researchers found that 89 percent of respondents who have implemented at least one big data project see it as a way to revolutionise business operations. Furthermore, 85 percent believe big data will dramatically change the way business is done. Yet there are still operational challenges preventing businesses from fully embracing this new way to trade.

Unlocking Digital Business Data
In a world where everything is connected, IT pros are overwhelmed, searching through inundations of data for meaningful insights that can give the business any advantage over competitors and protect its infrastructure, data, and employees. It is often an arduous, time-consuming, and manual process that frequently results in analysing old and therefore irrelevant data.

An enhanced approach to scrutinising and discovering terabytes of data isn’t just favourable, it is imperative in the 4th Industrial Revolution.

Volumes are exploding, objects are getting bigger, and even planned downtime is unacceptable and costly if you can’t meet business demands for availability and performance. Eventually every organisation will want to benefit as the lines of business push for better access to big data. But how can businesses formulate new methods of collection, storage and analysis to extract the most value from their data?

The challenge that businesses face is that the more volume, velocity, and variety of data that is introduced into the organisation the more the need for a sophisticated and scalable approach to managing the big data environment. Mastering this data is fundamental to every organisation’s successful digital transformation – and failure to leverage the data and analytics will cripple an organisation’s ability to meet customer expectations and competitive pressures.

When data is siloed, such as residing in self-contained departmental databases, you’re going to get lackluster insights. It is important to take a holistic approach to a big data strategy. The big data technology ecosystem must interface with enterprise applications and data sources, such as ERP solutions and connected devices, to integrate data in one central location.

Right from the pilot phase of a big data initiative, automation processes must be put in place to ensure that data from across multiple sources can be seamlessly ingested, processed and available to the business, for on demand analytics

My IT is Better Than Yours
In the modern digital business revolution technology is integrated into every step of an organisation’s value chain. This unprecedented use of technology creates a complex challenge for IT Infrastructure and Operations organisations, as it becomes difficult to collect and organise the sheer volume of data generated by new digital business systems and sources.

With technology that enables the collection, storage, and analysis of this data, business demand for big data deployments has moved from experimentation to production. At the same time, IT needs to keep integration with existing business systems in mind. For instance, structured data remains the main focus, so IT needs to keep traditional storage and analytics solutions in place while exploring big data.

To leverage the benefits of the data explosion, organisations need to prepare their IT teams properly. An IT operations management tool with enterprise-grade capacity optimisation and visualisation can help IT plan and right size the data ecosystems—including compute, storage, and network resources, ensuring control over infrastructure costs. Not to mention, having the right actionable data helps you to be proactive when you’re troubleshooting any IT operations issue.

But the most valuable use of big data analytics is not reporting what’s already happened; it is accurately predicting future outcomes and behavior affecting the important areas of the business. Through predictive big data analytics, organisations can change operations in real time and build strategic, forward-looking plans to drive faster business outcomes, which give companies a competitive edge. One of the most powerful types of data for actionable insight is the ability see how measurements change over time, intelligence indicating trends upward or downward to enable action before a condition impacts end users.

With IDC predicting that the digital universe will double every two years to about 1.7 MB of new information created every second for every human by 2020 it is clear that data in the modern age is the currency that guides all decisions and actions. Complete and accurate analysis will empower IT operations to make fast, data-driven decisions that support continuous digital service improvement and innovation.

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