Big data management tools analytics

It comes as no surprise that IT systems are utilizing data analysis tools to adapt to digital transformation. This refers to the integration of digital technology into all areas of business. In order to stay competitive in the industry, IT systems need high-tech data analysis tools that are capable of offering valuable business insights. 

For a business to stay competitive and relevant as they shift towards digital transformation, they must collect and analyze massive amounts of information, dubbed big data, concerning every aspect of their processes. The more advanced data analysis tools are, the more insights a business will have about its processes and overall efficiency. The right tools can save an operation substantial time, costs, and labor. 

Digital Transformation and the Need for Time Series Data Analysis

Digital transformation has influenced the demand for big data in a major way. The information available from collecting large volumes of data is largely useless without advanced analysis capabilities and big data management tools that can quickly, reliably, and efficiently comb through it for valuable insights. These insights are then used for guiding business decision-making and responding to issues throughout entire operations. 

What is Time Series Data Analysis? 

IT systems will require something called time-series data analysis in order to be successful and innovative in their industry. Without this capacity, systems operate too slowly and inefficiently with identifying areas in need of improvement and potential setbacks.

Paired with time series analysis, historical data visualization additionally allows IT systems to see a snapshot of operational activities and any important patterns that have occurred over time. When analytics platforms are used over an extended time period, users can access predictive insights using past data and comparing it historically. 

Time series data analysis refers to the real-time availability of useful insights. When the technology monitors any abnormalities throughout an entire operation that may lead to downtime, users can immediately be alerted. Having this kind of on-the-spot access is a colossal factor in an organization’s overall data intelligence capabilities.

The Current Landscape of Data Intelligence

Data intelligence refers to the utilization of artificial intelligence, or AI, and machine learning tools for the purpose of identifying and understanding patterns and/or abnormalities in massive sets of collected data. 

Data intelligence technology improves IT systems, empowering them with the ability to use and understand data right away. With the huge shift toward digital transformation, data intelligence is revered now more than ever.

If your business wants to limit downtime, having real-time access to operational analytics is essential. Overall business intelligence is reliant on the insights made available from modern data analysis tools. Gone are the days of waiting for data analysts to manually sort through and extract useful insights about issues or inefficiencies in business processes. 

For example, it used to take days, sometimes weeks, for root cause analysis—an application we’ll dive into further down this post. With data intelligence, the time it takes to respond to problems and concerns is reduced to minutes.

This makes it easier for teams to evaluate and understand the ins and outs of their business practices, where they can cut down on costs, and how to handle irregularities because their decisions are truly data-driven. 

Applications and Uses of Sightline EDM for IT Systems 

Sightline Systems offers IT systems a unified platform for all data intelligence. Using AI, our analytics solution monitors all of your collected data and applies the following processes.

Análisis predictivo en tiempo real

Predictive analytics is defined as a category of data analytics used to make predictions and forecast future events all based on collected data and historical patterns. Companies are utilizing predictive analytics to gather insight into potential events that may decrease efficiency or cause breakdowns somewhere throughout their operations. 

With this technology, businesses are able to see into the future and make accurate predictions as far as years ahead of time. Thanks to digital transformation and the rise of automating as much of business operations as possible, the practice of using predictive analytics has grown exponentially over the last few years. In fact, by 2022, it is projected to reach over $10 billion in global market value.  

Real-time predictive analytics gathers intel from big data, machine learning, and a number of other embedded technologies to detect trends good and bad within business processes. With this type of tool on your business’ side, your team will be able to recognize potential risks before they have a detrimental impact on your operations. More so than previous tools, predictive analytics is a reliable way of tracking things like inventory requirements or shipping schedules, so IT companies are ahead of the curve in terms of future planning. 

One of the most valuable applications of real-time predictive analytics is the detection of potential security threats. With this tool on its side, your IT system can pick up on anomalies and abnormalities right away and deal with them before they grow to detrimental risks that could halt operations or access sensitive information. 

Sightline EDM collects metrics from an entire system and unifies them in a single dashboard. It gathers this data from the servers, applications, and network devices across all IT system operations. The information gathered is readily available for the user. Taking inventory of all collected metrics, EDM quickly visualizes the information. This capability allows for big-picture analysis of all past, present, and future system infrastructure, enabling it to predict and foreshadow possible inefficient or problematic processes. 

With Sightline, monitoring the performance of your system is simple. With metrics across thousands of systems, having a tool that uses past data to proactively project future occurrences can save your operation ample time and money

Detección avanzada de anomalías 

Anomaly detection, sometimes referred to as outlier analysis, involves the gathering and combing-through of data to identify irregularities and variations from historically normal baselines. With this tool, companies are able to detect processes and evaluate performance.

Anomalies in data sets may indicate a technical glitch, an inefficiency, or even a serious cyber threat. Using patterns from previously collected data, the detection tool will alert when they see deviations in business practices that are misaligned with the standard set from a business’ history. Anomalies are not necessarily bad things for businesses. They are just instances of unusual processes or circumstances that may indicate a more major snag, but this isn’t always the case.

Anomalies can be classified into three groups:

  • Point anomalies: This refers to major outliers in a set of data that are entirely beyond normal points. They are sometimes referred to as global outliers. 
  • Conditional outliers: Also called contextual outliers, this is a term for irregularities that are not totally uncommon, but are not expected in a specific set of data.
  • Collective outliers: These represent an entire set of data that deviates from the normal operation and data behavior.  
Predictive analytics big data optics

Detecting strange activity across all your facilities and operations offers businesses an inside look at what business decisions and incidents are working for and against them. Using anomaly detection tools will further root cause analysis efforts and can ultimately save your processes from unnecessary time and money spent on correcting problems or inefficiencies.  

With advanced anomaly detection, identifying outliers and potential threats in real-time can keep a system from experiencing detrimental interruptions or downtime. With Sightline EDM, collected data is stored and used to establish baselines that the system will then use for forecasting and IoT pipeline monitoring. In addition to comparing data with historical metrics, EDM can configure alerts tailored to the needs of the user. 

The visualization of data will show spikes when behavioral anomalies are detected. The system catches irregularities in the collected metrics and uses the data visualization to notify the team of early warning detection. With the evaluation of historical information and real-time anomaly detection across all systems, your team is able to quickly address issues informed by data. With EDM, identifying and addressing critical problems is more straightforward than ever.

Análisis de raíz de la causa 

Root cause analysis refers to the method of discovering the underlying causes of a problem or disturbance using data: in this case, massive amounts of data. 

Root cause analysis technology is applied to answer the following questions when an issue or an alert to a potential issue takes place:

  • What problem is occurring?
  • Why did this problem occur? 
  • What is this problem also affecting?
  • How can this problem be solved?
  • What can be done to prevent this from recurring in the future?

Adversely, when operations are running smoothly or more efficiently than usual, root cause analysis tools can help an organization narrow down why this is happening and where along operations this is occurring. Before the availability of this kind of analytical tool, data analysts had to manually scour data for indications of irregularities. This could take days or weeks on end to come to any viable conclusion. 

Sightline EDM offers streamlined root cause analysis capabilities that exponentially cuts down on the time it takes to pinpoint a problem. Before data analysis tools were able to resolve issues, it could take days and, in some cases, weeks to get to the root cause of an operational issue.  

With automated root cause analysis capabilities, Sightline examines behaviors and events across the entire ecosystem. Every server, application, and database is combed and reviewed by the advanced analytics engine to address root causes and any related symptoms so your team can take recommended corrective action.

Because EDM documents and stores past solutions, your team is able to resolve issues sooner and reduce both possible downtime and the unnecessary costs of recurring problems. Users can access research notes and recommended solutions by leveraging artificial intelligence.

With issues and resolutions stored in the EDM system, it’s able to alert your team before an event is repeated, giving them time to correct problems and avoid recurring issues that can be very costly for your IT systems.

Predicción y planificación de la capacidad 

Capacity planning, also referred to as capacity management, is a company’s ability to organize and plan for processing requirements. Before diving into future needs, capacity planning examines current workloads and can relay information about performance and efficiency. Using data, this tool can give your team important indications about best practices and approaching capacity limits. Capacity forecasting is like seeing your future in a crystal ball. With the information gathered from this tool, businesses can reduce problems and optimize their services. 

With Sightline EDM, IT systems can boost efficiency with custom forecasting reports and alerts. These automated reports utilize data from resource metrics including CPU, disk, memory, and networks. Through capacity planning and predictive analytics, EDM sends alerts about the threshold limits so your team can always see which critical resources are running out along with the out-of-capacity date. 

With EDM, your team can utilize a baseline of system performance and apply important information to planning processes such as available capacity and resource requirement data. With forecasting capabilities, the EDM system can help maintain service delivery levels and minimize spikes while also accurately predicting capacity shortages in advance. 

Seguridad de datos de un extremo a otro SIAS

It’s no secret: Today’s business operations need to protect themselves against cyberattacks in an ever-increasing way. Powered by Sightline Systems and in partnership with Unisys, SIAS is an all-encompassing data intelligence solution that encrypts all data and keeps sensitive data hidden in transit. This cybersecurity solution isolates anomalies and micro-segmentation to secure networks. Micro-segmentation is a network security approach that divides the data center and individually protects closed user groups. 

Learn More About Sightline EDM for IT Systems

Sightline EDM is a revolutionary data analysis tool catered to IT systems and their operations. Having access to real-time data allows your team to operate at the highest level of efficiency, cutting out tremendous wasted time and costs. 

With EDM, data intelligence is located in one unified dashboard that offers AI-powered data monitoring and analytics designed to improve your operations. Paired with our end-to-end data security solution, SIAS, your team can rest assured knowing that your sensitive data is always protected during the process of analysis. Plus, our pre-built integrations support a wide range of platforms for the easiest implementation.

capacity planning data analytics

Programe una conversación with an EDM expert to learn more about improving your IT system performance with Sightline Systems today. 

Preguntas frecuentes:

What applications are used to analyze data?

Sightline EDM and Sightline Systems SIAS

What are the tools and techniques that you used to analyze your data?

Root Cause Analysis, Advanced Anomaly Detection, Real-Time Predictive Analytics, Capacity Planning & Forecasting, SIAS End-to-End Data Security 

¿Qué le permitirá obtener la determinación de parámetros óptimos (centerlining)?

Data analysis refers to the integration of digital technology into all areas of business. In order to stay competitive in the industry.