Enterprise Real Time Analytics Use Cases

Popular Enterprise Real Time Analytics Use Cases

Enterprise Real Time Analytics Use Cases

“The more real-time and granular we can get, the more responsive, and more competitive, we can be.” – Peter Levine.

Real-time data! Real-time data analytics! These technical terminologies are much in demand and have turned out to be the latest jargon today. Without data, everything becomes worthless. Communication with accurate data and fetching of data as and when required at the required time is a must. Desired types of dashboards and reports can be generated through real-time data analytics.

Real-time data analytics can be leveraged for multiple reasons, some of which will be listed below. Also, the different industry segments that it touches upon are varied and each one of them gets influenced in their way. Organizations depend upon data analytics to stay abreast of the rest in terms of peer competition and successful business results.

Real-time Analytics – An Overview

According to Gartner, Real-time analytics is the discipline that applies logic and mathematics to data to provide insights for making better decisions quickly. It is a robust approach that focuses on enabling effective processing of data as soon as possible. It empowers stakeholders to make the right decisions at the right time.

It applies different logical and mathematical tactics for faster and more effective data perception. Because of detailed real-time data analytics, the face of business is changing. There are newer ways and means by which business task forces can access data instantly and in the desired format.

Importance of Real-time Analytics

Real-time analytics is majorly used in making operational decisions and applying them to routine business activities. It also offers predictive and prescriptive analytics on existing and historical data.

Client behavior can be predicted, technical issues can be fixed, speed can be increased, and wiser business decisions can be taken. Process improvement can also be made, and innovative services can be worked out.

Top Real-time Analytics Use Cases Popular Today

  • Supply Chain, Fleet Management and Logistics

Fleet managers in the supply chain and logistics arena leverage real-time analytics for effective tracking of shipping fleets, optimizing routes, and ensuring faster delivery of goods. Since real-time data is fed into the business algorithms, it comes up with the best possible route for drivers to stay away from hassles and save on time and energy.

Real-time analytics can also help in overcoming any operational hazard that may come along the way, for drivers. Advanced techniques can also help in determining the age of equipment, likely time of service and repair. This can help in knowing if the equipment can cause an issue in the near future or not. 

There could be a detailed utilization of newer technologies like infrared, thermal imaging, remote sensors, etc. Necessary real-time information can be gathered with the set technologies, and data can be collected and analyzed for further use. Real-time data also manages the inventory turnover that plays a crucial role in businesses. 

  • Assistance in Financial Services

Real-time analytics can help financial service providers manage mortgage functionalities with ease. It can help abide by the actual regulatory standards and hence stay on track. There would be no issues that need to be addressed. Risks would be minimized, and the business output would be much more profitable.

It also helps in implementing a thorough credit score to create output that can be fit to customer needs. It can enhance analytics output with other on-demand tools. High risk factors can be identified well ahead of time, to take necessary action, as and when needed. Especially since it works well in quickly changing market conditions.

Real-time analytics tracks malicious activities with ease, and that helps financial organizations keep a strong foothold over secure and robust transactions. It enhances the safety and credibility of transactions and lessens the negative impact of fraudulent activities. 

  • Real-time Analytics in Manufacturing

Real-time analytics can increase the operational efficacy levels in a manufacturing unit. It can help in controlling, tracking, and streamlining the procedures that can lead to effective manufacturing operations. Inventory management can be controlled on an actual stock basis, because of which demand and supply of stock can be managed well.

It helps in finding out the sales potential, inventory cost and aging of products. The dashboards can show the expired / to be expiring stock for necessary action to be taken. Predictive, prescriptive, descriptive, and diagnostic analyses can be performed to get the best of figures in manufacturing operations.  

  • Finetuning Application Features

Analyzing data in real-time can help in perceiving the implementation and, hence, finetune applications. Certain features may not be performing well. Real-time analytics can take necessary action so that those features can come up to the mark and offer results.

Newer implementations can be smoother and help in making proper business decisions instead of wasting time and effort. Any error that is occurring or about to occur can be caught beforehand and dealt with. Predictive analytics can assist in enhancing customer experience. 

  • Cybersecurity and Safety Against Malicious Attacks

Organizations find it difficult to safeguard their data and business processes against cyberattacks. Real-time data insight can help them gain knowledge about possible attacks in the future. Security experts can be prepared for the same well in advance, leading to a smooth flow of data. It can protect the entire organization from any malware or malicious attack.

There are companies involved in a lot of IoT-related information, passing data from device to device or between cloud and on-premises. Real-time data can be analyzed to understand the consequences of IoT within devices and locations. This can help stakeholders in judging the possibilities of any mishap coming up.

Good Read: How to Create an Effective Data Analytics Team?

Summing It Up

Real-time analytics is a window to the business world for the top management and end users to look at. It offers a real-time view of all the needed business information in one go in the much-needed format. This helps them make the optimal decisions and, thereby, enhance the productivity and profitability of the company.

Ridgeant, as a skilled data analytics partner, is experienced in unlocking actionable insights, helping you evolve into a data-driven organization. Be it machine learning predictive analytics or data visualization, there are customizable solutions that can catalyze your data journey and extract real-time analytics.

Our enterprise level real-time data analytics services encompass a multitude of industry segments, fuelling innovation and growth, making a strong difference. Our latest and well-chosen tech stack helps in synchronizing business requirements to convert raw data into actionable insights. 

Connect with Ridgeant for top notch data analytics services and industry ready solutions.


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