With more and more people going online, large volumes of data are being generated, processed, and collected every second. This means more raw and potentially helpful insights can be gained if this big data is utilized by businesses and organizations properly.
Also, since the emergence of the Internet of Things or IoT, we were introduced to the concept of “data across different devices and systems being interconnected through the internet”. With big data vs. fast data making noise in the tech and business world, how do we adapt and see the difference between the two?
What is big data used for?
Big data refers to massive volumes of information collected and stored from a variety of sources which grow at increasing rates. Before, search engines collect big data gathered by web crawlers and then process them overnight to be able to provide updates and insights the following day. With this, big data was then focused on data capture and offline batch mode operation.
However, this process may not be as helpful today. The future of big data states that modern fast data reduces the time between capturing and analysis, mainly because real-time fast data are processed as they arrive by the second.
What is fast data?
This pertains to data that provide real-time insights. Before, gaining insights from big data took much time and effort. Now, making fast analyses of information is crucial to a business’ bottom line. Fast data helps in preventing fraud and breach that would reveal confidential customer information.
Even if the concept of big data has been here for years now, not all systems are set up to handle fast data. Hence, this can be a challenge for businesses. Without the right tools to manage and assess streams of data quickly coming in, valuable insights may be lost or gained too late. As a result, these can’t help resolve business processes right away.
Let’s look at websites for example. Websites offer products or services to a target customer at a specific moment. Through data and analysis, we can assess what type of customer behavior and actions were done on a specific webpage. But this data can be massive and need to be processed immediately to become more effective. That’s where the challenge lies—data collecting, storing, and processing are all happening at the moment, necessary to make changes to the webpage to cater to the customer’s needs more efficiently. Hence, the term “fast data”, where processes are happening in real-time, and fast-moving.
With these new insights on how data is being collected, stored, and processed, it’s imperative for businesses to keep up and improve the way they handle big data vs. fast data.
Lastly, these are just some of the top technology trends to watch out for in the years to come. For businesses to thrive, they must consider the evolution of data processing and analysis to come up with better business decisions and offer more quality products and services to customers.
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