What is big data analytics? Fast answers from diverse data sets

What is big data analytics? Fast answers from diverse data sets

Link: https://www.infoworld.com/article/3220044/what-is-big-data-analytics-fast-answers-from-diverse-data-sets.html


 In recent years, whether it is the IT industry, marketing, or academia, there has been quite a lot of discussion about big data (or big data), but because big data covers a wide range, everyone defines big data There are also ambiguities, so there is always a feeling of incomprehension about its abstract concepts and actual operation.

 To put it simply, big data is very large and very large amount of digital information. The amount of these data is too large to be stored, transmitted and analysed by manual and existing technology, which in turn encourages people to develop higher-level data storage equipment and technology. Most interpretations of big data have the following four characteristics:

 Volume: The huge amount of data accumulated.
Variety: The diversity of data forms, including text, images, community messages, search behaviours, etc.
Velocity: Fast transmission speed.
Veracity: To ensure the authenticity and correctness of the data, the analysis process is very important.

What is data analytics?
  • Data analytics involves examining data sets to gain insights or draw conclusions about what they contain.
  • By analysing information using big data analysis tools, organisations can make better-informed business decisions
  • Analytics can refer to basic business intelligence applications or more advanced, predictive analytics such as those used by scientific organisations.
  • Data analytics can include exploratory data analysis and confirmatory data analysis

Big data analytics use cases

Big data and analytics can be applied to many business problems and use cases. Here are a few examples:
  • Customer analytics. Companies can examine customer data to enhance customer experience, improve conversion rates, and increase retention.
  • Operational analytics. Improving operational performance and making better use of corporate assets are the goals of many companies. Big data analytics tools can help businesses find ways to operate more efficiently and improve performance.
  • Fraud prevention. Big data tools and analysis can help organizations identify suspicious activity and patterns that might indicate fraudulent behavior and help mitigate risks.
  • Price optimization. Companies can use big data analytics to optimize the prices they charge for products and services, helping to boost revenue.

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