Conscious organizations know that analytics is integral to their application stack because it facilitates informed decision-making via data visualisation. Data analytics has evolved beyond displaying facts and figures into collaborative business intelligence that predicts outcomes and aids in decision-making. IDC’s Worldwide Big Data and Analytics Spending Guide projected the region’s spending on big data analytics solutions to rise to USD 53.3 billion within the next three years. However, these investments will be in vain if IT departments are not part of the conversation. 

The fact that the IT division tends to be left out of discussions about analytics initiatives is ironic in itself because of the sheer volume of data produced by IT systems. One of the main reasons IT gets the short end of the stick is because IT data is unique. Compared to other business data, IT data is vast, complex, and generated at a high velocity. These characteristics perpetuate the notion that IT data analytics requires little attention. To understand trends and make better decisions that delight customers, empowering IT analytics is imperative for businesses.

Domain expertise for complex data 

Though often looked at as a single entity, an IT team is actually made up of several different departments that have different areas of focus but need to work together to ensure business continuity. 

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These departments generate and analyse large volumes of complex and contextual data. Bringing this data together requires a deeper understanding of how these different functional areas of IT impact and influence each other. As opposed to a standard IT analytics offering, advanced IT analytics software can scan IT data for important metrics, identify correlations in it, and highlight important metrics that enable stakeholders to make the right decision.

Out-of-the-box connectors for popular IT tools

A typical IT department uses anywhere between 10-15 applications that help it run and manage operations. These IT applications hold valuable information that can be used to develop an overarching view of operational health, analyse the efficiency of operations, look for security gaps, and find potential cost-saving avenues.

However, the true challenge lies in tapping data from these applications, identifying sections that can serve analytics, and building the right visualisations to allow for a larger audience to consume the data and take necessary corrective action. Analytics can consolidate IT data from multiple applications and monitoring tools and gain automated insights to help make better strategic decisions and achieve operational excellence.  

An IT analytics application that has out-of-the-box connectors for popular IT applications can extract data, model it, and generate prebuilt reports and dashboards that can cut down the time for analysis by almost 80%. IT teams don’t have to do the heavy lifting themselves. Additionally, IT data demands customisable visualisations, and IT analytics applications empower users to tailor visualisations to represent the overall health of operations based on business needs. 

AI-enabled auto-interpretation

IT analytics applications that take advantage of AI and NLP are capable of understanding direct questions and answering them in the form of visualisations. For example, questions such as, “How many alarms are expected in the next 12 hours?” or “What is the average cost per outage?” can be easily understood by the NLP engine and answered in the form of reports. Such simplicity safeguards sensitive and confidential corporate data while opening up channels for data democratisation across the organisation. 

AI can go a step further and remove another aspect of analytics that predominantly requires human effort: interpretation. Effective analysis of data requires two components: a robust analytics application and an end user with a good eye for detail. AI-enabled IT analytics overrides the perennial issue of bias and the subjective nature of human interpretation by auto-interpreting data and offering direct insights swiftly.  

Large volumes of data need high scalability

Depending on the size of the organisation, hundreds of network devices are monitored, thousands of security events are logged, and millions of lines of logs are being created by IT management applications at any given point in time. Data on this scale requires a robust analytics application that is capable of processing, storing, and analysing millions of rows of data every few minutes.

Though generic analytics applications are capable of analysing large volumes of data, they are unable to keep pace with the speed at which modern IT applications generate data. 

Specialised IT analytics applications use intelligent algorithms, batch processing, and auto-prioritisation of data based on criticality. This ensures high-risk activities such as security threats are detected immediately and reported to security analysts. Users can also configure event-based thresholds and choose to be notified when set limits are breached.

Real-time analytics, real-time alerts and visibility

There are two types of IT metrics: those derived from historical data and those derived from real-time data.

While traditional analytics applications are good at historical analysis, they fall short when it comes to analysing data in real time. On the other hand, IT analytics applications are fine-tuned for this specific purpose. Services such as Live Connect allow direct, real-time, on-demand connections to the data source, helping bypass the traditional mode of periodic synchronisation and storage of data for analysis. As a result, IT admins can rectify issues as soon as they occur, leaving no room for security loopholes to be exploited. 

Moreover, when real-time analytics is coupled with real-time alerts, organisations can react to opportunities and threats faster, particularly when anomalies are detected in privileged accounts. Choosing an analytics tool tailor-made for IT requirements not only removes the albatross from the proverbial neck but protects against operational disruptions and empowers organisations to get out of firefighting mode. 

IT can simply be more proactive by utilizing advanced analytics and the right data. Proactive IT departments offer IT teams many opportunities to think strategically and achieve larger, company-wide goals, cementing IT as a key department that helps to direct the company’s strategic direction.

This article titled “Off-the-shelf just doesn’t cut it: Why IT needs specialised analytics” was contributed by Rakesh Jayprakash, Head of product Management, ManageEngine

About the author

This article titled Off-the-shelf just doesn't cut it Why IT needs specialised analytics was contributed by Rakesh Jayprakash, Head of product Management, ManageEngine

Rakesh Jayaprakash is Head of Project Management at ManageEngine, the IT management division of Zoho Corp, where he is involved in product design and management of ManageEngine’s IT analytics software, Analytics Plus. Rakesh specializes in building analytics integration with popular ITSM and ITOM applications to help companies leverage IT data to make business-critical decisions.