Companies and organizations already have their own definition of Big Data, and their expectations are all different. But unlike their idea, Big Data has a misleading element. Big Data is a complex market that consists of small technologies that grow as you ride the unique maturity curves of each field, but there are a lot of exaggerations now.
So what are the misunderstandings of a company or an organization?
- Big data is only a description of unstructured data.
Often, Big Data is a technology that analyzes unstructured data from social media. But that alone can not explain big data. For example, we may not be able to collect unstructured data due to privacy laws or security issues. In this case, the information is processed through the formal data.
- The key to Big Data is better customer service.
Most of Big Data’s best practices came from companies that used to improve customer service. But it’s hard to say that it’s the heart of Big Data, and in fact, the biggest benefit companies get from Big Data is process efficiency. Next is identifying security risk areas and finding new areas for customer satisfaction.
- Big Data is just an IT project.
Big Data does not provide information that businesses need to move right into action to create successful business results. Big Data can not be regarded as a short-term IT project, and if it is treated as an IT project, it will fail. Also, if a company is negative about big data projects, then all big data in the enterprise will decline.
- Big data should start big size unconditionally.
Many companies have an obsession that they must start big size unconditionally when using Big Data. Because it is a prejudice, It’s okay to start small if you do not know how to introduce Big Data or if you are skeptical about investment. In addition, small start-up companies should use specialized vendors who can analyze big data.
5. Big Data all is about analysis.
Big data analysis is part of Big Data technology, but ultimately it is the ultimate goal. So companies must first understand how to store, manage, compress, and retrieve data. Big data can be so complex and fast, so it’s important to understand how to manage it before you analyze it.
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