The Advantages & Unseen Disadvantages of Big Data in Business

Home » The Advantages & Unseen Disadvantages of Big Data in Business

BigDataScalability.com – Big data isn’t about a big volume of data. This term has been popular nowadays because of the growth of new systems for businesses such as e-commerce and healthcare. Big data in business will generate information, transactions, and also activities efficiently.

The important aspect of big data that is useful for the system itself is the multiple data types. All data combined is structured, various, easy, and quick to access and process. However, it doesn’t mean that big data doesn’t have disadvantages. Check out the pros and cons below.

The Advantages of Big Data in Business

1. Unobstructed Supply Chain Management

Unobstructed-Supply-Chain-Management

Supply chain management is bothered easily when there are obstacles, and the pandemic is one example. Disruption and obstacles are inevitable during that time if the system is still traditional. Big data can save it from fragility and generate it into an agile system.

Integrated supply chain management needs a system that will work well in real-time. The analytics must be predictive, so the supply chain management will continuously work without disruption. Big data is the answer to creating an integrated system.

2. Providing unseen information

Providing-unseen-information

Before the big data system does exist, the information provided is standard. The pricing, for example, it’s not real-time and the level to access the information is low. The big benefit of big data in business is providing unseen information regarding the business, especially in retail.

New insight because of unseen information will optimize the profit. The problems that might occur will be solved quickly because the solution is available even before the problems themselves start. The risk reduction level is higher because of unseen information from big data systems.

3. The source of insight

The-source-of-insight

It’s unavoidable that insight from customers is important in business. High understanding is the key to gaining profit and trust for sustainable business. The insight will give the businesses a new understanding of the key to improving the business. Big data becomes the platform to get insight easily, such as:

  • Social media activity: customers nowadays have social media as the source of information. They tend to follow what makes them interested. Big data in business provides information about their trace of interests.
  • Financial transaction: for financial businesses such as banking and fintech, big data becomes the source of information regarding the customers’ transactions. It gives insight into how their money goes to particular merchants.
  • Computer cookies: it has been a public secret that big data in business use computer cookies as the source of information. It’s the trace of what visits because it gives the information about their interests and curiosity about products or services.

4. Targeting the audience

Targeting-the-audience

Big data in business is the biggest system to give newer recommendations to the customers and the business itself. The system is smarter than before because it gives access to customers’ insights easily and quickly without surveying. It has become a common activity in the market.

The engine will create an environment where the users are unaware that they are not involved in the survey, yet it’s not part of breaching privacy. The system only leads particular consumers based on their behavior. The information can be limited, yet the result is sensitive and more accurate.

5. Deep analytics of customers

Deep-analytics-of-customers

Analyzing the behavior using big data helps you to get detailed information. The understanding is deeper because the dynamics of customers’ behavior are seen, even in real-time. It’s the reason why big data in business can increase market intelligence.

How does big data analyze it? The system generates to look for customer preferences. Customers share their information about their interests, then big data collect information ranging from the product, value, priority, etc. From that information, big data infers understanding.

6. Data sets for diverse roles

Data-sets-for-diverse-roles

Conventional data can’t be used for a lot of business purposes. This is why big data in business starts to be a role model since it’s suitable for many cases. A data set can be the source of several cases and it helps the user to have more efficiency to work on it.

Data sets have some advantages for applications or digital businesses. However, it may take longer to create since it involves legality and needs fraud prevention if the case is financial planning. The data provided usually are raw to create another particular model.

Those data sets which are in the system might only be taken partially. The design for analytics is always different for each case. The techniques used are different, depending on the type and number of applications. The team should understand the datasets and databases.

7. Historical data storage

Historical-data-storage

Data is always important material for future reference. To get some high-quality predictions or outcomes in the future, it needs good historical data. The pattern in the past is crucial to collect and save. They will give you a proper and better insight into the business, in the short or long term.

The volume of big data in business may be challenging since it needs gigantic space to store. On the other hand, the growth of data is getting more complex. The dynamic is changing from time to time. Many factors are demanding as well to create accurate results for a better conclusion.

Another point to note is that big data in business is a kind of investment that you might think it’s expensive now. Management sounds complicated, but for future reference, big data is a place to catch the pace of challenging and complex change, especially in business.

8. Improving business

Improving-business

The main purpose of using big data in business is to improve and optimize all the contributing factors. With less staffing work for the business and being replaced by big data, the cost saving is greatly changing. The productivity is better with higher levels of satisfaction from the customers.

Big data detects a lot of risks. It forms better management. Fraud detection and cybersecurity planning are two things to start once using big data. The business might only need an experienced data team to infer every analytics from the data shown by the big data system.

For the time pace, big data will help the maintenance better than human work. As long as the system is well-integrated, big data in business can pull out the necessary information. The production is more optimal and it gives more power to improve the business on any scale.

The Disadvantages of Big Data in Business

The-Disadvantages-of-Big-Data-in-Business

1. Hardware

Hardware availability to support big data becomes the main problem of the system. To store massive data, it needs durable high-quality hardware. Some devices damage easily because of non-stop usage. Since big data in business is real-time, the devices get heat often.

Hardware is quite costly because of the quality issue. If you are getting the inexpensive one, the durability might be questionable. The installation of the hardware also needs the best technician and programmers. They are the ones who understand how the hardware works without device issues.

2. Storage

The more data to store, the bigger the storage. For a big-scale sector, the size of storage will affect the usage of big data systems. All kinds of information must be stored in the cloud and it’s limited. Getting big-size storage is also expensive. You have to spend a lot of money.

Storage also gives influences access to the data. If the storage is limited, the process to get information is slow. Information changes continuously and inevitably. It requires faster storage, so you can access and analyze the data faster too.

3. Cost

Another problem of big data in business is the high cost to build the whole system. The data isn’t stored in the system, but it also needs to integrate with other elements. Without gathering data together, then the information isn’t detailed. The result of the information is incomplete.

Individual companies might get their system since they are carrying out their research. However, it’s different from small-scale businesses. It’s very expensive to get a supercomputer to support the system. This is why big data is not affordable for some businesses.

4. Maintenance

Maintenance is another issue that you need to consider before establishing good data in business. Two things require maintenance. The first one is hardware. It’s not cheap to give proper maintenance to the device. The people must have the experience to do so.

The second maintenance is about the software, The analysis has to be deeper to get a better conclusion and it needs updated software. Without updating, the factors contributing might be unseen. The data pattern might have less information to infer.

5. The data is unstructured

The big data system is still messy for now since it’s a newly established system. The data collected to store is usually random. When you are accessing the information, the arrangement might be confusing and the form is difficult to process.

This is the weakness of big data in business unless you are ready to create a structured system. To achieve this, you need an experienced team. They have to generate the data into several categories. The information will not be broken and unstructured anymore, so the conclusion is accurate.

6. Security factors

We can’t deny that the security factor of big data in business is concerning. The information stored in the cloud is confidential. Without high security, it’s dangerous if the information is leaked to the public. Irresponsible parties will make money from it.

This is a big challenge for big data. The network must be secured, yet the standard of security is still unknown. The staff who are responsible for the information should be trusted too. Leaked data can be a big source of information for those people who will take advantage of it.

7. Skillful staff and analysts

Analysts who work for big data systems must have a lot of experience to handle massive information. They should be professionals who not only understand the business, but also statistical matters. Since it’s complicated, analysts usually are highly paid.

Updated software for big-scale businesses also needs professional staff to handle it. They have to update everything quickly, so the skills to analyze the information are better. However, training for analysts costs a lot of money. Big data training for analysts is still rare too.

Big data in business still has pros and cons, since the system is new. Some businesses try to blend and engage with the system because it is such a great help. However, the challenges of using big data are great too. Analytics and techniques are required to get the best conclusion.

Bulk information in big data improves the business to higher scales. Its usefulness helps a lot, but the technology must be better too. Not only from the updated hardware and software, but the skillful staff is also the key to getting the best result from gathering and analyzing information from big data.

Read More: