

Data is important. Nobody has a second opinion about that. However, in this dynamically changing world, using that data as soon as it is generated will make all the difference. For example, a shipping company can be hugely benefited if it has the system to analyze weather data every hour. It can optimize the fuel consumption of its ship and ensure the choice of optimal routes. The efficiency of data analytics today depends largely on how fast it is analyzed. This is the gist of Real-Time Analytics. With Real-Time Interactive Insights, an organization remains always prepared for any issue and can detect and solve it faster than its peers.
Realtime Analytics is the real-time analysis of the data generated by the concerned company. This means- companies with Real-Time Interactive Insights capabilities can analyze data as soon as it enters the database. As a result, they can gain insights from the data as and when it enters.
Real-Time Analytics also means that the analytics system can handle dynamically changing data. It doesn’t just work with static data. In this setup, data analysis can take place even when the data gets updated every two minutes.
There are two ways in which Real-Time data analytics works.
👉 In one case, the ever-changing data keeps on getting ‘pushed’ upstream to the database. The system doesn’t need to ‘request’ data.
👉 In the other case, the system looks for updates to the existing data and ‘pulls’ the update to its database. The first case is also known as data streaming (just like YouTube streaming), where data flow is continuous. In the latter case, the flow or update of data can happen at certain intervals. Ofcourse, the length of the intervals can’t be too long.
There is another important aspect of Real-Time Interactive Insight, and that is – Response Time. No matter how quickly the data arrives, the time it takes for the system to parse and analyze the data will make all the difference. Let’s give you a fun example. We often play a Linux game named Cube 2. In that game, there are some servers that kick the person out who kills his own teammate thrice. That’s an example of basic real-time analytics. The server receives the game data continuously and performs automated action based on the data on a real-time basis. A more practical example is the stop-loss feature of the stock market. In this case, too, the system keeps track of the changing market data continuously and sells your stock once it reaches a particular price.
An example of pulling the data is your third-party email app on your phone (not the official Gmail app). The third-party email app periodically polls the mail server connected to it. During such polling, if the system finds new emails, it downloads them to the database. In this case, the app does not receive data from the mail server. Rather, it ‘requests’ for new mails, and only then does the server send the new emails.
Pretty much every company will benefit from Real-Time Analytics. From financial institutions to retail industries, from maritime companies to healthcare, from ecommerce to streaming sites- Real-Time Interactive Insight has its role in every domain.
This awesome technological paradigm is already in action. For example, people make investment decisions based on real-time stock market insights. Again, during the pandemic, the doctors and the government constantly updated their advice based on the ever-updating insight on the infection.
Since we are more into the maritime industry, let’s show you how the shipping industry can benefit from Real-Time Analytics.
The maritime industry can gain a huge technological upgrade once Real-Time Analytics gains traction. There are multiple ways in which this technology helps the shipping industry gain efficiency.
The remote sensors in the ships can help the shipping company keep track of the quality of the equipment. The sensors can alert the stakeholders on a real-time basis if any equipment malfunctions. For example, maintaining the correct water level in the boiler is extremely crucial. Sensors can alert the maintainers in case of a low water situation.
Real-time GPS and RFID data can mitigate a lot of pain points of the maritime industry. For example, with real-time port congestion data, ships can plan their route and speed so that they don’t get stuck in long queues. Real-time Analytics can also help companies that ship their products with the help of freight forwarders. Real-time data can help these companies track their shipments and containers without the need to be dependent on the freight forwarder or the shipping line.
Making the maritime industry environment friendly is on the top of the agenda of all the stakeholders in the industry. However, for that to happen, the ships need to lower the consumption of fuel.
While lowering fuel consumption needs technological innovation, there are many ways of making the ships fuel-efficient. Ships have started using real-time data to monitor maritime weather conditions and decide on the optimal route. Re-routing ships based on real-time weather data can significantly reduce time spent on the oceans and seas, thereby reducing wastage of fuel. This will indirectly reduce the emission of greenhouse gas.
Real-Time Interactive Insight is going to be the primary way of data analytics in the future. With breakneck competition, companies need to analyze their data as quickly as possible to make faster decisions and improve customer experience. Real-time analytics makes your data usage in the truest sense.