Advantages & Disadvantages of Big Data
Last Updated on August 5, 2021 by Editorial Team
Big data is a collection of both structured and unstructured data that is huge in volume and rapidly generated. The amount of big data produced grows exponentially with time, and that amount is expected to double every two years.
Two of the most popular open-source big data frameworks are Scala and Hadoop. Programming languages play a significant role in big data analytics as well. For instance, the big data framework Hadoop is implemented in Java, while MapReduce applications can be written in Python, C++, or R.
Big data is mainly collected through search engines, social media platforms, mobile phones, service networks, public records, and connected devices like smart televisions. There are also other sources of information businesses can access to retrieve big data.
After collection, huge datasets may be placed in a structured, unstructured, or semi-structured database for further processing and analysis. NoSQL Databases are often used to store big data as they provide high performance in processing large data sets at a massive scale.
Like any other technology, Big data also comes with its own benefits and drawbacks. When it comes to real-world applications of big data, there are instances where drawbacks mitigate some of the benefits of big data. Therefore, it is essential for companies to pay attention to both pros and cons of big data before using it.
After understanding what Big data is, let’s discuss its advantages and disadvantages.
Advantages of Big Data
1. Better Decision Making
Companies use big data in different ways to improve their B2B operations, advertising, and communication. Many businesses including travel, real estate, finance, and insurance are mainly using big data to improve their decision-making capabilities. Since big data reveals more information in a usable format, businesses can utilize that data to make accurate decisions on what consumers want or not and their behavioral tendencies.
Big data facilitates the decision-making process by providing business intelligence and advanced analytical insights. The more customer data a business has, the more detailed overview it can gain about its target audience.
Data-driven insights reveal business trends and behaviors and allow companies to expand and compete by optimizing their decision-making. Furthermore, these insights enable businesses to create more tailored products and services, strategies, and well-informed campaigns to compete within their industry.
2. Reduce costs of business processes
The surveys conducted by New Vantage and Syncsort (now Precisely) reveals that big data analytics has helped businesses to reduce their expenses significantly. 66.7% of survey respondents from New Vantage claimed that they have started using big data to reduce expenses. Furthermore, 59.4% of survey respondents from Syncsort claimed that big data tools helped them reduce costs and increase operational efficiency.
Do you know that Big data analytics tools like Cloud-Based Analytics and Hadoop can help reduce costs for storing big data?
3. Fraud Detection
Financial companies, in particular, use big data to detect fraud. Data analysts use machine learning algorithms and artificial intelligence to detect anomalies and transaction patterns. These anomalies of transaction patterns indicate something is out of order or a mismatch giving us clues about possible frauds.
Fraud detection is significantly important for credit unions, banks, credit card companies to identify account information, materials, or product access. Any industry, including finance, can better serve its customers by early identification of frauds before something goes wrong.
For instance, credit card companies and banks can spot fraudulent purchases or stolen credit cards using big data analytics even before the cardholder notices that something is wrong.
4. Increased productivity
According to a survey from Syncsort, 59.9% of survey respondents have claimed that they were using big data analytics tools like Spark and Hadoop to increase productivity. This increase in productivity has, in turn, helped them to improve customer retention and boost sales.
Modern big data tools help data scientists and analysts to analyze a large amount of data efficiently, enabling them to have a quick overview of more information. This also increases their productivity levels.
Besides, big data analytics helps data scientists and data analysts gain more information about themselves so that they can identify how to be more productive in their activities and job responsibilities.
Therefore, investing in big data analytics offers a competitive advantage for all industries to stand out with increased productivity in their operations.
5. Improved customer service
Improving customer interactions is crucial for any business as a part of their marketing efforts.
Since big data analytics provide businesses with more information, they can utilize that data to create more targeted marketing campaigns and special, highly personalized offers to each individual client.
The major sources of big data are social media, email transactions, customers’ CRM (customer relationship management) systems, etc. So, it exposes a wealth of information to businesses about their customers’ pain points, touchpoints, values, and trends to serve their customers better.
Moreover, big data helps companies understand how their customers think and feel and thereby offer them more personalized products and services. Offering a personalized experience can improve customer satisfaction, enhance relationships, and, most of all, build loyalty.
6. Increased agility
Another competitive advantage of big data is increasing business agility. Big data analytics can help companies to become more disruptive and agile in markets. Analyzing huge data sets related to customers enables companies to gain insights ahead of their competitors and address the pain points of customers more efficiently and effectively.
On top of that, having huge data sets at disposal allows companies to improve communications, products, and services and reevaluate risks. Besides, big data helps companies improve their business tactics and strategies, which are very helpful in aligning their business efforts to support frequent and faster changes in the industry.
1. Lack of talent
According to a survey by AtScale, the lack of big data experts and data scientists has been the biggest challenge in this field for the past three years. Currently, many IT professionals don’t know how to carry out big data analytics as it requires a different skill set. Thus, finding data scientists who are also experts in big data can be challenging.
Big data experts and data scientists are two highly paid careers in the data science field. Therefore, hiring big data analysts can be very expensive for companies, especially for startups. Some companies have to wait for a long time to hire the required staff to continue their big data analytics tasks.
2. Security risks
Most of the time, companies collect sensitive information for big data analytics. Those data need protection, and security risks can be demerits due to the lack of proper maintenance.
Besides, having access to huge data sets can gain unwanted attention from hackers, and your business may be a target of a potential cyber-attack. As you know, data breaches have become the biggest threat to many companies today.
Another risk with big data is that unless you take all necessary precautions, important information can be leaked to competitors.
The need to have compliance with government legislation is also a drawback of big data. If big data contains personal or confidential information, the company should make sure that they follow government requirements and industry standards to store, handle, maintain, and process that data.
So, data governance tasks, transmission, and storage will become more difficult to manage as the big data volumes increase.
Nowadays, big data analytics can be crucial for any company. However, every business should figure out whether the pros of big data analytics outweigh the cons, particularly in their own case and situation. If they decide that advantages are greater, they also need to find out ways to overcome the disadvantages.
Furthermore, if your company needs to employ big data analysts to grow the business and improve marketing efforts, make sure you or your staff know how to use Big Data appropriately. Big data analytics has become challenging for many companies as it is still a new technology. Yet, most of these issues will be resolved as the big data technology field grows and evolves in the future.
Advantages & Disadvantages of Big Data was originally published in Towards AI on Medium, where people are continuing the conversation by highlighting and responding to this story.
Published via Towards AI