Common False Beliefs About Big Data in Business

Big data's ambiguous information makes it impossible for corporations to obtain conclusive solutions

Big data may be used by businesses to understand their customers better, spot patterns, and solve issues that will help them expand, target their advertising, and create new products. Retailers, for instance, can use big data to better understand the buying habits of their clients and offer each one of them an improved shopping experience. The following are some common misconceptions concerning big data held by businesses:

Large companies only use big data

No, not exclusively. The benefits of Big Data technology are available since most firms, including smaller ones, produce enormous amounts of data. Major companies, which will generate more than $154 billion in revenue in 2020, will be the main proponents of big data and business analytics in the future. According to International Data Corporation (IDC), small and medium-sized businesses will also continue to contribute significantly.

Big data is often perceived by businesses as being expensive to manage. Even some big data firms today offer affordable services to help businesses with data analytics. Big data's ubiquitous application has also made technology more readily available to organisations than ever before.

Therefore, you should start by identifying a few high-value challenges that prove the business case for utilising this new resource before investing significantly in big data technologies or infrastructure. Once the proof of concept confirms the benefit of big data, the process may be scaled.

Big Data integration is the solution to all business problems

Big data is unstructured, making it difficult to "quantify" or convert into numerical values and being too huge and complex to be studied using conventional methods. Because of this, using big data to address business issues is challenging. Big data's ambiguous information makes it impossible for corporations to obtain conclusive solutions. Therefore, to use big data analytics, useful questions must be raised. As a result, an increasing number of companies are looking for analysts to deal with these issues.

Non-tech enterprises are not affected by big data

Being able to analyze information to make decisions will provide you an advantage over rivals, even if your company doesn't deal in technology. When innovations like automation, artificial intelligence (AI) in customer support, and big data-driven marketing become the norm, the early adopters will be at the leading edge of a brand-new digital era. Non-tech organisations can also benefit greatly from data by understanding how it enables an organisation to make better decisions and take more interactive adaptive based on facts rather than gut feelings. A corporation will need to use data-based technologies to stay ahead if it wants to seize this market right now.

Big Data is challenging

Despite the complexity of Big Data, the biggest error that data scientists make does not understand the context and corporate objectives of their work. They instead put a lot of effort into developing their AI/ML skills. We need to confirm that the company isn't focusing solely on machine learning or AI-related projects; we want to know that they are also conversant with some of the other methodologies. Get a sense of the magnitude and extent of their efforts in this area as well. In order to understand how their company objectives have changed and how their strategy should evolve correspondingly, data scientists must work closely with consultants. Context is crucial when working with huge data.