Whether you’re part of a small business or a large one, big data is important. Even small businesses are finding they now have access to many of the same tools as very large corporations, and they’re using it to their advantage. Being able to afford big data resources and analytics tools is no longer out of reach for small organizations.
With that being said, just because the tools and resources are there, it doesn’t necessarily mean all organizations are using them correctly or that they’re staying current with how to use data.
The following are some data trends and other things to think about in 2019, whether you’re an analyst or someone who’s in a different role in a small, large or medium-sized business but who wants to harness the power of big data effectively.
The Growth of Cloud Computing
Data may have outgrown the name “big data” in many ways because it’s not just big. It’s pervasive and it’s everywhere in the background of every organization, whether people realize it or not. There was a fear that this ever-growing nature of data in the business world (and everywhere else) would be difficult to keep up with in terms of cloud computing, and potential infrastructure shortcomings.
The process to bring data from the perimeter of the IT infrastructure and to the cloud can take a long time, but there has been a focus on creating new infrastructures that reduce this lag time in a cost-efficient way and make the move from the perimeter to the cloud more efficient overall.
With all that being so pertinent right now, it’s important that companies have the storage and processing tools to make it happen.
What all this boils down to is an increasing need for edge computing. Edge computing in simplest terms is computing done near the source of data or perhaps even at it. This is a shift away from the cloud in reality, but the cloud isn’t likely to lose its important role in how businesses and the world do things.
Edge computing is just incredibly fast, and it can offer some advantages regarding privacy and security as well.
Machine Learning Isn’t Necessarily That Important…Yet
For the past few years, you’ve probably heard a lot about machine learning. However, just because the algorithms provided by machine learning are advancing quickly, it doesn’t mean that old-fashioned analytics are dead.
Machine learning is driven toward achieving very specific goals, but we’re not at the point where it can necessarily take those specific tasks and goals and apply them to real-world situations in the way that humans can.
The Risks of Dark Data
The potential risks that come with dark data are very relevant right now. Dark data is any digital information an organization is storing that’s not being used. It’s the data your organization collects and stores as part of doing business, but isn’t using it for any purpose currently.
There are plenty of reasons an organization might leave dark data hanging around. The business may outgrow the need for that data before it’s used, or it may no longer be relevant for some reason. The data might be incomplete, or it may be stored in places that are no longer in use.
There are risks, however. If dark data is being stored there are security concerns that need to be addressed. Along with the security risks, dark data may also represent opportunities that aren’t being utilized.
The Rise of the CDO
There is likely to be so much focus on data in 2019 and beyond that many companies will begin hiring someone to be in charge of it all. This position is often referred to as the Chief Data Officer or CDO. Some organizations may already have a CDO, but that position is likely to grow and expand in the future.
Finally, while the fact that the cloud is less relevant in the face of edge computing, it’s certainly not obsolete. One trend in the world of the cloud is something called the hybrid cloud. The hybrid cloud combines elements of a private cloud with a public cloud. The benefits of a hybrid cloud can include increased flexibility, options, and tools. With a public cloud, the applications for use can include projects that don’t require a high level of security.
For on-premises private cloud, the applications can include the more sensitive information that needs a high level of privacy and security.
Image Credits: Data Trends from Tonktiti/Shutterstock