Big Data: The Risks behind the Glamorous Opportunities

Even though data has been a part of our surroundings for an extended period, the concept of Big Data has only gained widespread recognition in the past decade, profoundly impacting the global landscape. Every software development company, regardless of its size, interacts with big data in various capacities, making it an undeniable cornerstone of the tech industry.

However, similar to the proverbial two sides of a coin, Big Data presents significant risks alongside its myriad benefits. Unfortunately, these inherent dangers are frequently ignored by software development companies, largely driven by the profit-centric nature of the business world.

Big Data Risks

As such, to provide more insight on this, following are the four most concerning risks nowadays:

Breach of Data Privacy

Big Data also means big threats to data privacy. Enterprises all around the world store an enormous amount of sensitive data at their disposal, such as personal customer and employee information, company’s strategic documents, and so on. These kinds of data are an obviously juicy target for hackers because of how valuable they are to the other competitions in the business. Therefore, the last thing you want is an organizational data breach, which could inevitably lead to heavy consequences, potentially bringing down the business. Developing countermeasures for security scenario is a compliance necessity.

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A Troublesome matter named: “Data Organization”

To put it mildly, an enterprise may possibly generate an enormous heap of data points on a daily basis, as most tasks involving business nowadays are completely data-driven. The bigger the business, the larger the data accumulation. Furthermore, data is ever-changing and therefore highly versatile, which comes in from numerous sources and forms. With all this data keeps flooding in and piling up each minute, enterprises are prone to be overwhelmed when trying to make use of the stored data. As such, a significant amount of time is wasted on cleaning and integrating it into the enterprise network. These tasks negatively affect the performance of the business. It is imperative that the firms understand data collection and deploy a solution for it as soon as possible.

Inefficient Analytics

How important Big data analysis is

Without analysis, data is just an unnecessary burden for the business. Data analysis is an absolute obligation to put big data into good use, giving valuable insights into enterprises’ usage in business decision-making as well as developing business strategies. Had the firm not handled their data well, analyzing data is surely an arduous task, as much as it is money-consuming. Likewise, with information overload due to unorganized data, businesses run a huge risk of wasting, misinterpreting, and even relying on outdated data, which ultimately leads to major data error while making poor decisions and plans for the firm. Sequentially, the business lags further behind on the market competition.

Big hit on the budget

As the business grows, more and more information flows into the database, it becomes apparent that the concerns for storage are absolutely critical. With such data coming in huge volumes, the costs for upgrading storage also multiplies. Traditional data warehousing calls for a huge initial setup cost, not to mention the fact that performing hardware upgrade is also time-consuming and costly, due to the fact that the actual hardware needs to be purchased and properly installed. Another approach for data storage is to make use of cloud technology. While this method can minimize the costs for on-premise data warehouse, there are certain hidden security risks associated, which is why many firms prefer the former system. Regardless, both traditional and cloud-based storage methods involve a huge expenditure. Additionally, the procedure of processing, analyzing and securing data requires top dollar investments, which may take a heavy toll on the enterprise budget. Only with a carefully developed Big Data Solution can the cost be mitigated well.

Read more: 6 Questions You Should Ask before Using Big Data

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