We know the importance of making data-driven decisions in today’s business life*. However, using time in the most effective way while making these decisions is also crucial for the agility of institutions. This is where real-time data analytics comes into play.
What is Real-Time Data Analytics?
Since the increase in the use of smart devices and wearable technologies and the decrease in data storage costs, the amount of data is increasing significantly. At our current rate, it is predicted that 1.7 MB of data will be generated per second for each person in the world*. Those who interpret all these data in the fastest and most accurate way always stay ahead of the competition. Real-time data analytics, which comes into play at this point, defines the technology and processes that enable seeing, analyzing, and evaluating data as soon as it is captured.
A More Agile Corporate Culture
Disruptions and delays in decision-making and action processes cause a waste of money, time, and workforce. When we look at the old methods, data had to be collected, transformed, and manually reported by IT experts and data analysts to gain insights. Under current conditions, such a process is a serious obstacle to the agility of institutions. The faster organizations can turn their raw data into useful insights, the better their ability to act agile. Real-time data analytics meets these needs due to capturing instant and informative insights from data for decision-making.
Competitive Advantage
In today’s conditions, systems that support real-time data analytics need to be used in order to fully gather insights and discover opportunities. Therefore, sectoral information and opportunities can be obtained for competitive advantage. By not only discovering opportunities but also quickly discovering problems, simultaneous measures can be performed and losses can be minimized. In addition, comparisons can be made and trends can be discovered in order to choose the best option in business development processes. Risks can be calculated by real-time testing of how fluctuations or changes in the market will affect the processes. Decision results can be measured by instant viewing, and if any problem arises, different options can be tried with minimum damage.
Many organizations are now investing in real-time data analytics to keep up with the pace. Thus, the data is ready to be analyzed, interpreted, and visualized as soon as it is created.
Which Sectors Can Benefit?
It would be a mistake to limit real-time data analytics to sectors. Every sector has a process that requires following the events instantly. Let’s take a look at the manufacturing sector. Real-time data analytics help significantly reduce operational risks. Any equipment failure can be detected quickly by monitoring real-time data, and loss or damage due to failure can be prevented with instant intervention.
If we look at the financial markets, we should consider the instant changing tables. Therefore, financial industries or finance teams in institutions use real-time data analytics to evaluate how their day-to-day operations are performing and monitor the impact of fluctuations on these operations. Sudden market fluctuations can also bring great opportunities for businesses. In order to take advantage of the opportunities that these fluctuations will bring or realize the risks, real-time data analytics come into play.
Let’s look at the trade and retail sector; In some cases, purchasing or selling decisions may need to be made very quickly. By observing the instant situations in the market with real-time data analytics, decisions can be made considering instant data.
Many industries such as logistics, airlines, and the tourism sector can also be affected by instantaneous events and there may be situations where urgent measures are required. With the real-time data analytics system designed for needs, very fast responses can be given to any situation.
How to Build a Correct System?
Although most of the real-time data is now processed and stored in the cloud, taking advantage of this technology requires data storage and proper planning. System outages, late data, or problems in processing real-time data may hinder decision-making processes.
Datactive is a real-time data analytics system, which means queries data at their sources and visualizes them instantly without the need for data transfer. Thus, it provides the fastest interpretation of the instantaneous data and the capture of instant data changes with scheduled tasks without losing time.
The ability of these technologies to process bulk data is also very important. However, the system also needs to process this data in a way that users can easily interpret. User-friendly dashboards, interactive infographics, and the ability to quickly share this data make the system suitable for use by every unit within the organization and highly support decision-making processes. Since such technologies are also responsive, data can be monitored simultaneously from anywhere and decisions can be made without wasting time.