One of the biggest problems with present-day data analytics lies in the fact that the volumes of data gathered are bigger than they have ever been before. In fact, they’re getting bigger by the hour. In theory, the volume shouldn’t have that much of an impact on the analysis. Think about it, if the algorithm is solid enough, what difference does it make whether there are 10 pieces of information or 10,000 of them?
Well, the difference is a gigantic one. First of all, with a limited amount of raw data, you can’t draw meaningful conclusions, which means that you can afford to use an inferior tool. As the volume of the data grows, things rapidly change. With that in mind, here are five big data trends that you can expect to grow in significance in 2019.
The rapid expansion of the IoT
So many times before, we talked about the issue of the IoT, and one of its biggest drawbacks lies in the fact that it’s still available on a limited number of items. In 2019, the trend of growth is bound to continue. You see, the difference comes from the fact that the volume of information that comes through the IoT is so large, in quantity, and so sophisticated, qualitatively, that it opens up so many new options for analysts to consider.
As for the numbers, it’s expected that by the year 2019, the number of IoT connected devices might grow to 26.66 billion, compared to 23.14 billion in 2018. With this growth rate, one can expect the number of these items to reach 75.44 billion by the year 2025. To some, this may sound like a distant future, yet, this is only 7 years away.
One of the biggest issues with analytics is the fact that it needs to have data in order to work. This is data that comes only from events and occurrences that have already taken place, which means that it’s is the most efficient when it’s reactive. In other words, you have the result and then you look backward in order to figure out the consequences. The problem with this form of analytics lies in the fact that, by the time you have the results of the analysis, the damage is already done and the opportunity is already long gone.
With the help of the latest tools and algorithms, predictive analytics may be much more efficient. This, of course, doesn’t mean that predictive analytics didn’t exist or were impossible before big data and BI tools. It only means that with their help, they can become drastically more efficient.
In the past, a lot of people had second thoughts when it came to open source software, unjustly assuming that these tools and platforms were amateurish or inadequate. It turns out that a huge community of users with access to the tools come up with some of the most outstanding community patches and fixes, which, sometimes, makes these tools even more user-friendly. This is the main reason why open source analytical languages like GNU or R are getting a lot of love from big data analysts all over the world. This trend is expected to continue growing in the future.
5G is still not likely
The next thing worth mentioning is the fact that 5G, that was expected to arrive and make a huge splash in 2019, is probably not going to arrive in the following year. The biggest halt here lies in the fact that infrastructural changes cost quite a bit and the latest change in the FCCs stance on net neutrality regulations makes investors wary to approach this market. Either way, we may have to wait a tad longer for this trend to finally arrive, alongside all the big data changes that it may introduce.
At the end of the day, it’s important to mention that with more sophisticated tools, we also need some highly sophisticated hardware to help us keep up. This is where the notion of quantum computing may make a huge entry. The fields that will get the most affected by this are the communication and relationships between customers and organizations. Other than this, such trends are expected to introduce a proper revolution in the field of financial modeling (one of the greatest benefits of big data).
The thing about big data is the fact that it’s getting used by more and more small organizations, startups and individual users, which was hard to imagine just a couple of years back. This phenomenon improves the quality of service across various industries and is bound to continue doing so in the future.