Big Data Pros and Cons

Big Data Pros and Cons


 May 17 2020
Website :https://www.datamation.com/big-data/big-data-pros-and-cons.html

Student Name : Joyce Chang 張可薔
Student ID : D0740800

According to the NewVantage Partners’ Big Data Executive Survey, 97.2 percent of the firms surveyed were investing in big data and AI initiatives. This also leads to a booming market with almost 12% annual growth rate in the big data analytics spendings worldwide. Experts have expected the a total revenue of more than $210 billion by the end of 2020. However there is always risks and it is not guaranteed that you get the results you want. Around 80% of the companies believed that they are at the medium or high level of big data maturity. Yet, the fact is that only around 10% of them meet the criteria of high level maturity. Moreover, the companies in the lower maturity level are struggling with multiple challenges.
Therefore, experts suggest that companies carefully weigh the pros and cons of the big data before they embark their new analytic projects to see if it's worth the risk.

Advantages

  • Better decision-making
  • Increased productivity-Modern big data tools allows analysts to analyze more data faster, which increases their personal productivity. At the same time, the results from the analytics allow organizations to increase productivity more broadly throughout the company.
  • Reduce costs
  • Improved customer service-Social media, customer relationship management (CRM) systems and other points of customer contact give enterprises information about their customers, and it is only natural that they would use this data to better serve those customers.
  • Fraud detection-Big data analytics are good at detecting patterns and anomalies, which give banks and credit card companies the ability to spot stolen credit cards or fraudulent purchases
  • Increased revenue-Organizations use big data to improve their decision-making and improve their customer service, increased revenue is often the natural result.
  • Increased agility-Companies are using their analytics to support faster and more frequent changes to their business strategies and tactics.
  • Greater innovation-Companies can have a look inside what their competitors don't equip and easily get out ahead of the rest of the market with new products and features.
  • Faster speed to market

Disadvantages

  • Need for talent-Hiring or training staff can increase costs considerably, and the process of acquiring big data skills can take considerable time.
  • Data quality-Data scientists and analysts need to ensure that the information they are using is accurate, relevant and in the proper format for analysis, which slows the reporting process. But if enterprises don't address data quality issues, they may find that the insights generated are worthless or even harmful.
  • Need for cultural change
  • Compliance-Much of the information included in companies' big data stores is sensitive or personal, and that means the firm may need to ensure that they are meeting industry standards or government requirements when handling the data.
  • Cybersecurity risks-Storing big data, particularly sensitive data, can make companies a more attractive target for cyberattackers.
  • Rapid change-Organizations face the possibility that they invest in a particular technology only to have something much better come along a few months later.
  • Hardware needs
  • Costs-Many big data tools rely on open source technology, which dramatically reduces software costs, but enterprises still face significant expenses related to staffing, hardware, maintenance and related services.
  • Difficulty integrating legacy systems

In the end, most organizations decide that the advantages outweigh the disadvantages. However it is still worth considering the risks before the decisions.

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