How to Handle Rapidly Growing Data

Data is an omnipresent element within every organization. Data comes in from customers, employees, third-parties, or other external sources. It is up to each company to find ways on how to handle rapidly growing data and put it to good use. Smart businesses are already looking into ways how this data can address numerous issues within the organization and outside it, as well as how to differentiate themselves from the competition.

Some challenges arise when it comes to leveraging this information. With the many technological advancements over the past two decades, the amount of information coming in is growing at an almost exponential rate. What's more, most of this data is unstructured.

Structured data is much easier to handle. Businesses use it every day by making use of relational databases or by creating spreadsheets in Excel, to give a couple of examples. When this happens, various patterns emerge and can be easily identified.

The biggest issue in this context, however, is with unstructured data. It can come from numerous sources such as social media, emails, documents, blogs, videos, images, etc., and represent ample opportunities for businesses to grow and optimize their operations.

Unfortunately, however, unstructured data makes it much more difficult to gain any easy or straightforward insight by using conventional systems. What's more, much of the data that's generated nowadays is unstructured, making it vital for businesses to find ways on how to properly leverage it.

Cloud Migration

First things, first. With the overwhelming amount of data coming in on a daily basis, storing it on-site can become quite costly. On the one hand, having this data on-site can result in an over-provision, leading to further unnecessary costs. On the other hand, it can take a lot on onsite real-estate.

But by migrating your application and database to the cloud, none of the problems mentioned above will be an issue. With public cloud vendors such as AWS and Microsoft, you can pay as you go, meaning that you will have access to a much higher degree of flexibility and scalability than otherwise. In addition, keep in mind that a cloud provider will become an extension of your IT team once you've made the transition. And let's not forget that storing your data in the cloud also implies less real-estate expense.

Cognitive Computing

Cognitive computing (CC) refers to various technology platforms that make use of artificial intelligence (AI) and signal processing. These platforms also make use of machine learning, natural language processing (NLP), reasoning, speech recognition, human-computer interaction, dialog generation, among other such technologies.

CC can analyze unstructured data, interpret it, and generate insights based on all possible decisions using evidential support. These systems can be adaptive, meaning that they can learn as the information changes. They can also be interactive, seamlessly communicating with users as well as other devices and cloud services. And they can be contextual, in that they can understand, identify, and extract various contextual elements, from multiple sources and different sensory inputs such as visual, auditory, gestural, etc.

In short, cognitive computing will help businesses understand and structure disorderly data to put it to good use and get ahead of the competition.

Conclusion

Big data can offer plenty of opportunities for growth and profitability, but it can also pose a severe challenge if not leveraged correctly. For more information on the topic of data management and other related issues, visit our website or contact us directly.

 

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