Real Time Big Data Analytics – definition, examples and benefits

Businesses nowadays are generating huge amounts of data, and it is expected that in the future we’ll be dealing with even larger volumes of information. More and more companies depend on big data analytics to improve their efficiency. Some of them can’t operate without real time analytics. What is it and what can it be used for?

Real Time Big Data Analytics gives entrepreneurs useful business insights almost immediately after collecting data. This means better control over the various internal and external processes, which allows them to optimize them really fast. What exactly can your company gain by adopting Real Time Big Data Analytics solutions?

Real Time Big Data Analytics – what it is? 

Thanks to real time Big Data analytics you can perform analysis of large amounts of data at the very moment when this data is collected or used in some process. Valuable information is extracted from the gathered data just after it is stored using your company’s big data infrastructure.

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Real time Big Data Analytics is usually performed in industries and companies that constantly produce a lot of data and those which require output from analysis a short time after collecting data. This type of analytics can be run on data from multiple sources.

So, how does it work?  Stream of data is loaded directly to the analytics platform which reduces the time needed to ingest and transform data versus classical batch approach. Data can be assessed and analyzed just milliseconds after being created at the source system.

What are the advantages of performing real time analytics on big data? You receive insights almost immediately after collecting data, so you can act without delay in many situations – having such knowledge accessible soon after storing the data may help you outrun your competitors.

Good real time analytics tools are very useful for those who have to be up to date all the time – for financial industry workers for example. Real time big data analytics can help e-commerce companies learn trends by tracking orders in the real time, and you can analyse customer activity on your shopping platform to better understand user behaviour or offer customized discounts, when customers hesitate to complete a transaction.  

Examples of Real Time Big Data Analytics application in business

Using real time big data analytics in e-commerce to support sales is one of the most popular reasons for applying this technology in business, but certainly not the only one. In all industries, these solutions may be implemented in order to reduce costs of day-to-day operations by saving money in areas such as hiring and employee engagement.

With effective analytics, you can also gain useful business insights faster and spot big opportunities for your business before your competitors see them. Real time analytics also allows you to get ahead of situations that could cost you an extra money – it can help you find and fix problems before any damage is done. 

Performing analytics on big data in real time is very important for cybersecurity and fraud detection. By constantly monitoring incoming data and analysing the behaviour of the systems’ users, analytics tools can find the weak spots of your business infrastructure, detect the breaches of suspicious activity and help you react and prevent fraud or data leaks. 

Big data analytics enables businesses to apply predictive and prescriptive models in order to run advanced analytics and forecast the future of the industry. This technology is used by many companies along with quite new technologies, such as real time speech analytics, real time streaming analytics or real time manufacturing analytics – each of which can be adopted by the company in order to improve customer service, improve sales or reduce costs, which leads to general efficiency improvement.  

What industries are using Real Time Analytics?

All industries can apply real time analytics technology in order to increase their profits. How is real time big data analytics used in particular industries? 

Retail – pattern detection

Sales companies are using business intelligence solutions all the time to identify trends and adjust offers and advertising to consumer expectations. Businesses are using technologies such as machine learning to become “smarter” and more modern. You can learn many things from big data analytics – customer spending habits, preferences and expenses. It allows you to provide an accurate product recommendation to a given customer and to raise the total value of the cart.

More and more brands use real time analytics to adjust prices according to demand and market conditions – Uber is the most famous example of that. Advanced real time big data analytics tools can tell not only what kind of goods your clients are most likely to buy, but also when they’ll be ready to make an order. 

Amazon is one of the most tech-savvy e-commerce companies in the world. It uses real time big data analytics to find transactions which are most likely fraudulent in order to prevent them from happening. Of course, Amazon also customizes the browsing experience using big data gathered during customers’ previous purchases.

Marketing and advertising

Experts in traditional and online advertising use real time big data analytics. The most obvious benefit of applying this technology is learning how effective a particular campaign is. Of course, after realizing that a campaign is rather ineffective, specialists can adjust it to make it more efficient. But that is just the beginning. Sophisticated methods of advertising using big data are being invented all the time and – with technology all around us – we’ve stopped noticing it anymore. It affects us almost all the time without our knowledge. 

Automotive and Aircraft 

Whenever there is IoT (Internet of Things) involved real-time analytics can bring an immense value. Based on millions of readouts from different sensors, engineers and analysts can create automated Machine Learning models to predict if a given device will fail within the next hours or days.   If a high risk pattern is identified using the trained ML model  in the real-time data stream from the device can be flagged for inspection or event predictive replacement of crucial parts. It all happens before a malfunction occurs  reducing cost of unplanned downtime.

Many car manufacturers today rely on real-time analytics based on the output of hundreds of sensors embedded in each item they produce. For instance the manufacturer can have a real time view of all cars and assess how many of them are operating in an optimal way.

If the car sensors indicate that there may be some malfunction or defect the car manufacturer can either issue a recall action or simply instruct the owners to upgrade the software or recommend changing driving habits that impair the car performance. 

In the Aircraft industry real time data analytics allows engineers to identify and correlate patterns of events that lead to potential downtime or imminent malfunction even mid-flight. If such a pattern  is identified during a long distance flight the crew in the target airport already has the necessary parts at hand and has a clear repair plan even before the plane touches down.

Powerful technology for all industries

Real time big data analytics is used by financial institutions, healthcare organizations, e-commerce, advertising agencies, manufacturers – in short, by everybody. There is no industry that couldn’t benefit from real time analytics. If you’re interested in how your company can use it, contact our consultants – we’ll be happy to advise you. 

What are the potential benefits of adopting Real Time Big Data Analytics?

The main benefit of real time data analytics is speed – you can use data to gain insights, improve efficiency of selected processes or even correct your own mistakes shortly after realizing that something could be improved. Advanced analytics in real time can produce business insights that will allow you to make critical decisions faster. By using modern real time analytics tools you gain the possibility to: 

• monitor customer behaviours easily,
• apply machine learning and other technologies,
• analyse and share information using clear dashboards,
• modify and improve the efficiency of advertising,
• make changes in campaigns or other processes based on produced insights, 
• customize analytics tools,
• detect anomalies and suspicious activity in your systems and organization in order to prevent data leaks and fraud,
• prevent technological failures.

A high quality real time big data analytics tool should have a low response time, be able to handle huge amounts of data and be easy to use. There are many business analytical solutions available on the market, but not all of them will fit your organization’s requirements. Allow us to study your company’s needs and offer the best possible approach.