Considering Top Pros and Cons While Managing Big Data BIG Data

Today, every enterprise leverages the power of Big Data as data has become a more valuable asset than a currency. Thus, capitalizing on big data, organizations are pouring huge capital on it. In an IDC report, the global spending on big data and analytics is growing at a CAGR of 11.9 percent and revenues will likely to worth over US$210 billion by 2020.

Along with, most privacy advocates concern that gleaning enormous amounts of information about individuals, groups and people’s behavior could lead to new technologies that can have overwhelming and nefarious impacts on people worldwide. However, as it is easy to comprehend those worries, the large number of big data applications available in today’s marketplace have the ability to improve analysis, assisting users to make better decisions.

Data is often amassed through the platforms that generate it in the first place, such as social media sites, search engines, mobile applications, utility infrastructure and public records, connected devices like smart TVs and any other source. Data generally gets collected and assessed at specific intervals, but using real-time data analytics makes it acquire and analyze on a continuous basis.

So, before embarking on any analytics project, businesses need to consider some top pros and cons around big data.

Pros

Automating Routine Tasks: Making use of big data applications, companies can improve their operations across areas like customer service, among others. As an organization gleans more information about a user’s behavior and preferences, big data technologies convert that information into meaningful insights to create experiences that are more personal, responsive and precise than ever before.

Keeping Data Safe: Collecting, processing and evaluating data in real-time provides users farfetched benefits. But safeguarding it against security threats should be a concern as each 1 in 4 businesses at risk of experiencing a data breach. Thus, before commencing to accumulate more data, it is significant to detect the heightened risk of a breach from both internal and external sources. In this way, deploying specific analytics techniques allows for immediate real-time verification and secure storage of data.

Making Competitive Strategies: As competition jolts businesses in the modern competitive marketplace, big data analytics offers them a complete competitors’ picture, including the launching of a new product, price fluctuations for a particular duration, targeting users’ specific locations, among others. Thus, taking benefits of real-time data analysis can assist businesses to create effective strategies to compete with their competitors. Also, sales data, industry trends and market indicators can support organizations to stand tall by better understanding customers’ behavior and the products and services they need.

With this veritable gold mine of potential benefits, big data also poses significant challenges that could counterpoise any potential gains.

Cons

Running Without Roadmap: Deploying big data applications can certainly add efficiency to a business in the short term, but it is crucial that the company understands the full value of their data in the long run. For that, they must rethink their entire approach to data collection as the real-time analysis requires constant data collection instead of a periodic collection. It also requires major changes to business strategies and a significant investment.

Handling Data Management: Some organizations may see real-time big data analytics as a glittery new asset and seek to deploy it immediately. However, without the tools or staff in place to accurately handle data management, a company can miss the opportunity to make valuable insights. Also, it could place them in legal jeopardy. So, mishandling or misrepresenting data collection and processing can result in serious fines that can impact the company’s bottom line.

Lack of Expertise: In order to carry out real-time analysis, businesses can’t just rely on software alone. They must look for people with big data expertise, who also has knowledge about big data visualization and other related skills that make sense of the information which further enhances the company efficiency. This talent deficiency can also lead to slow adoption of big data analytics in specific domains and may face an uphill battle against data breaches.

In a crux, big data analytics can be of huge importance to a business, but they need to scale out the benefits and pitfalls in their particular circumstances before implementing it.

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