Today’s business world is taking a major seismic shift in the market at a speed faster than ever. The data coming into enterprises is coming from a substantial number of multiple areas and in various formats. Organizations are receiving these database at high volume and at lightning-speeds, whether from a mobile device, scientific sensor or the Cloud. Each of the data sources e.g. social media, sensors or spatial coordinates are new data vectors for the industry and established companies are having difficulty keeping pace with the changing trends. The digital revolution is disrupting the existing business models. Thus, enterprises need to learn how to address the pool of huge database in this digital world using IT Analytics.
IT analytics use cognitive computing capabilities to understand the IT systems’ behaviour over the time and provide early detection of abnormal system behaviour. Advanced data and text analytics are also used to extract insights from structured and unstructured data sources. It helps to predict problems before they impact the service and cause costly outages. But organizations are facing issues and certain challenges to integrate the analytics in the cloud.
- Data Model Diversity: The entire analytical workflow can get complicated because of complexity and elaborate steps and processes. These steps are data acquisition (accessible data, selection of parameters, data cleansing & data quality), data modelling(Defining the logical model and linkage of various database), data mining (Algorithm writing, variable identification and process validation) and visualization (Advanced and customized graphical representation and reports).
- Data Volume: Its not that easy to process the large amount of generated/available data as there are multiple channels and means to obtain the data pool. It is a big task to move the whole data to cloud. Furthermore, analyzing this database for definite insights is yet another challenge.
- Real Time Analytics: As the value of IT analytics is increasing, the demand for rapid insights is also increasing. Thus, the world is moving towards the real time analytics and thus it is impacting and changing the business models and existing IT infrastructure.
- Security and Privacy: Security and privacy is the most difficult part of data analytics to handle. It is difficult to keep the data anonymous after the analysis to retrieve potential insights. With Private cloud this issue has been addressed but still companies with data criticality or regularity constraints stay reluctant.
Emergence of End-User IT Analytics
From banks and insurance companies to healthcare, and from retail stores to telecommunications companies, and many more are leveraging IT Operations analytics to transform their business processes, their organizations and even their industry.
According to the Harvard Business Review, companies in the top third of their industry who use data-driven decision-making processes are, on an average, 5% more productive and 6% more profitable than their competitors.
Today’s world seeks smarter and faster technologies and therefore it becomes important to bridge the gap of end- user satisfaction level. IT departments need to raise the bar and add end- user IT analytics for value addition services. Nexthink is the innovator in the field of end user IT analytics. Nexthink is unique because of its real time analytics for all execution and network connections. The corresponding real-time visualization of Nexthink provides new visibility and insight into what it means, in real terms, at that particular moment in time.
Benefits of IT analytics:
• Detect security threats and risks beforehand, avoid costly assumptions and mistakes, resolving issues early.
• Create a fact-based decision making culture.
• Using data analytics enterprises are able to gain better and complete understanding of captured data and use it efficiently to process and analyze these database.
• IT analytics lead to efficiency improvements, increased sales, lower costs, better customer service, and improved products and services.
