Artificial intelligence and machine learning depend on big data solutions in order to become useful. On the other end of the spectrum, big data becomes more manageable when humans are no longer tasked with identifying every bit of data that comes into the system. In short, artificial intelligence and machine learning are a logical part of big data services.
Big data solutions continue to grow and machine learning grows along with it. For 2017, what are the trends that you should look out for?
1. Self-service big data services will soon be available online.
The Internet has always played a role in leveling the playing field. Small businesses can now compete on a global stage in the same way that global multinational corporations can. Amazon has brought the same compute, networking and storage capabilities to both small and big customers.
We have seen a lot of cloud applications and data processing advancements of late and these have given rise to different data platforms that are free to use and available to everyone online. Big data solutions such as Sisense, TIBCO Spotfire, Grow, BeyondCore, SAS Visual Analytics, IBM Watson Analytics, SAP Lumira and other free data platforms can help beginner data enthusiasts and expert data scientists to organize and analyze their data easily.
Most of the earlier big data platforms are now available on the cloud and you can use these without having to worry about wiring, server racks, networks or servers. You can just say how much compute and storage resources and databases you need to run both your data warehouses, and your applications will be available to you in just a few minutes. And there are several giant vendors to choose from, including Amazon, Baidu, IBM, Google, Microsoft, and several others.
These self-service big data services will help drive down costs and clear the barriers for companies that want to try getting into big data.
2. Analytics will still lag behind.
The tools that we currently have for analytics are still very complicated. Hadoop and Spark can help you manage giant data warehouses but it will still be difficult to move data from operational to analytical systems. The situation may be helped by the emergence of more data and improved algorithms that can pave the way for more automation.
3. Yet, artificial intelligence and machine learning will need more analytics.
It has been years since machine learning has been used and it has seen a lot of developments and improvements along the way. In 2017, expect more improvements in the area. Artificial intelligence applications that are driven by machine learning will need more analytics and more data to create predictive models and consequently makes the applications better.
For example, an artificial intelligence application that detects sepsis events would need a lot of medical records then analyze the data recorded in these records in order to predict a sepsis event even before it happens.
4. Machine learning and artificial intelligence will also give rise to data cleansing industry.
To ensure the quality and accuracy of data being used for machine learning and artificial intelligence, it would have to be checked for accuracy. Data cleansing also guarantees that there are no formatting errors, duplicated data and other mistakes. It is important because bad data will only lead to bad predictions.
5. Free your data.
Most of an organization’s data is stored in silos, which makes it very easy to stay on focus and make accountability possible. However, big data can now go serverless, which can help businesses manage their data without going through virtual machines or without racking any server. So instead of doing administrative work, data owners can just focus on making their data applications better and pay for their needed resources by the minute.
It is no surprise that artificial intelligence and machine learning are among the areas that Amazon AWS focused on during the recent Amazon re:Invent event. AWS has announced three new services that would make machine learning available to end users while also getting their investments in these technologies amped up.
Big data solutions will pave the way for more artificial intelligence and machine learning applications. The good news is that companies now have a way to easily try out big data services online without needing to spend too much or even have the technical know-how to use these. Self-service big data solutions will be available to beginners.
Machine learning will also need better analytics and data cleansing. And while analytics will continue to falter in 2017, data cleansing just might become a whole new industry.
As big data becomes bigger and bigger, enterprises and organizations can no longer ignore the technology. And machine learning and artificial intelligence are helping this explosion. And most of these improvements are going to happen on the cloud, not on onsite systems.
If you are looking to get into big data solutions or is curious about artificial intelligence and machine learning, then now is the time to act. You can leave the complexities behind, decide on what you want to do and call Four Cornerstone!
You can also seize the opportunities that machine learning, artificial intelligence and big data offer. For instance, if you are looking for another line of business, data cleansing might be a good avenue for additional income. As indicated here, data cleansing is going to be a much sought after service and getting in early might mean a boon for your company.
Four Cornerstone can act as your big data consulting partner as it can help you take advantage of the many technologies and services that are available on the cloud. There is simply no excuse, as you can get the database, storage, networking and compute resources you need without having to come up with a lot of money upfront.
Contact Four Cornerstone now at (817) 377-1144 or complete our short contact form and talk to us about the big data solutions you have in mind. That is all it takes!
Photo courtesy of Alex B.