Today’s businesses are drowning in data from IT systems, applications and digital platforms. It’s a situation that’s been accelerated by the post-pandemic pivot towards home working and the popularity of AI, which has seen the volume of global data rise from 2 zettabytes in 2010 to a forecasted 394 zettabytes by 2028.
Managing this flood is overwhelming for IT teams, whose current approaches to data management simply can’t keep up with the exponential growth in scale and complexity. Without a digital life raft, they’re at risk of an information overload that could obscure data analysis, delay decision-making and impede commercial growth.
Enter AIOps, which can help businesses manage vast amounts of data by surfacing the most critical issues in real-time – allowing IT teams to address problems faster and allocate resources where they’re needed most. Ultimately, this technology converts having an excess of data into a significant competitive edge.
Director of Solutions Engineering, UK & Ireland, at Riverbed Technology.
Why traditional methods fall short
It’s likely that the businesses struggling to cope with the complex demands of modern IT environments are those still relying on legacy software, siloed data sources and rigid monitoring tools. The problem is, these traditional approaches typically require manual input, which is time-consuming and prone to error.
By design, they also fail to provide a holistic view of the IT ecosystem – a lack of transparency that makes it difficult to identify patterns or predict potential issues in a world where data is everywhere. What’s left is an overreliance on under-resourced IT teams that are tasked with locating, protecting and utilizing a completely unmanageable amount of information.
Updating or replacing these existing solutions involves considerable time and money. However, persisting with inefficient and outdated systems will likely incur ‘tech debt’ – the financial burden of constantly needing to update aspects of a digital estate to meet the demands of new projects. Essentially, neglecting digital transformation will result in repetitive and costly business expenses moving forward. Therefore, businesses need a more proactive solution.
Achieving clarity with AIOps
AIOps has the power to transform organizational IT management thanks to the way it harnesses machine learning and advanced analytics.
By allowing these platforms to oversee their data, organizations can effortlessly deal with the technical disruptions that would otherwise be buried within increasingly complex digital estates.
AIOps doesn’t just react to issues; it predicts them too. By analyzing real-time and historical data, it detects patterns that signal future interruptions, allowing teams to act before problems impact users. Automating repetitive tasks frees IT professionals for strategic initiatives while streamlining processes and optimizing budgets, and platforms offering AIOps for observability provide a single window into IT ecosystems – reducing blind spots and generating insights that protect performance across applications.
AIOps enables organizations to cut through the chaos, offering a comprehensive view of digital operations and helping them focus on the information that truly matters to them.
The increasingly vital role of data stores
For businesses to integrate technology that helps them comprehensively monitor the behavior of IT systems, their information needs to be easily accessible – which is exactly why data stores are another key part of the AIOps equation.
Imagine that an organization’s IT infrastructure is like an office block. Just like every office space would store its own paperwork, each department in this virtual building contains different stacks of unique data. If an IT team was told to examine every bit of this information, they’d have to carefully search every siloed location to find it.
Having a data store is like putting all those siloed datasets into a virtual warehouse, within which an organization’s information is immediately more accessible, analyzable and trackable. A digital asset of this nature can be the difference between a failed and a successful AI strategy.
However, an inability to build a repository large enough is often a major stumbling block for many businesses, particularly as datasets become more immense than ever before. With the help of pre-built infrastructures, IT teams needn’t worry about finding more capacity. Instead, they can reap the scalable, secure and accessible rewards of having a unified data ecosystem.
Why a successful AIOps strategy matters
In today’s digital economy, data isn’t just an operational byproduct. Rather, it’s a strategic asset that can support businesses to outpace their competitors by identifying trends faster, providing superior customer experiences and innovating at a higher level than the rest.
By automating the handling of data streams and consolidating disparate systems, AIOps can turn organizations into agile, data-driven enterprises. Indeed, decision-makers across all industries believe in its potential, with a recent survey revealing that 91% of businesses agree that AI provides a competitive advantage.
Take customer service as an example. A public-facing business that integrates AIOps – like a retailer, bank or airline – can swiftly resolve any data bottlenecks that would usually cause website downtime or slower transactions. Customer retention levels rise as the brand establishes itself as a reliable digital presence in the industry – as does the financial bottom line.
Surviving and thriving in the age of information
As data continues to flood the IT landscape at an overwhelming rate, it’s a challenge for businesses still deciding what action to take. AIOps can be a life saver, by prioritizing proactive problem-solving, optimizing resources and adopting solutions like unified observability and data stores.
In fact, in an era where information is power, organizations that embrace the transformative power of AIOps can not only survive but thrive. These digital platforms unlock heightened levels of security, efficiency and innovation, shifting the strategic focus from merely coping to growing; turning the stress of being inundated by data into a competitive advantage.
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