The next big thing in terms of data analysis is real-time data, also known as ‘data streaming’. Let me explain why.
The importance of using data to support any decision or strategy in today’s economy is, without question, something that any organization would compromise with. The growing generation and storage of data exceed anything that human beings have ever measured before.
An Increase in Global Data Creation
According to Statista, the total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, having reached 64.2 zettabytes in 2020. Over the following five years, up to 2025, global data creation is projected to grow to more than 180 zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the Covid-19 pandemic, as more people worked and learned from home as well as used home entertainment options more often:
It would be irrelevant to simply talk about how much data we generate or store in the cloud or locally within systems
Now, something that is inherent to humans is the need to anticipate what is coming; what’s going to happen next? That’s usually a very difficult question to answer. However, we can figure out the trend about what’s coming by just observing how both data generation is evolving and the technology supporting data storage and analysis.
Fundamentals of Data Analysis
Why do we need data more than ever? For the first time, we have the opportunity to measure many variables and observe their behavior historically. The ultimate need to measure more variables — in other words, include more data — is to make better decisions. Making better decisions means producing a final choice among several. That ultimate choice should minimize the risk associated with the choice and maximize the reward; also considering the other choices not taken.
In the last decade, we have been able to analyze more data every time. Therefore, we are capable to make more decisions, even in less time, as we rely more on data — how it’s stored, treated, and analyzed. As we can make more decisions in a shorter period, we also generate more data faster. This is a closed circle of analysis, decision-making, and data generation. This wheel is going bigger and faster each time.
The tendency of analysis is now needing more real-time or close-to-real-time data, so we can anticipate what the next decision is that we must make as an organization or what the next thing is to offer our customers. In general terms, anticipation is becoming more critical than just analysis of historical data to understand ‘what happened’ and ‘why it happened’.
Final Thoughts
Within the last decade especially, there are many solutions and technology facilitating the storage, processing, and analysis of streaming data; many of them are open-source technology. There’s also a good number of investments made from large corporations and private equity towards real-time data processing and analysis.
If your organization has been investing or adopting technology and infrastructure to store and analyze historical data, start planning on adopting data streaming technology and infrastructure, so you can be ahead of the wave.
Last but not least, being able to process and analyze real-time data requires improved skills. So, along with new technology adoption, it is important to reskill or upskill your workforce with these new technologies.
