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Big Data Write for UsBig Data Write for Us – Big Data is a collection of enormous volumes of data that grows exponentially over time. Big Data is data of such size and difficulty that none of the traditional data management tools can store or process it efficiently. Data is also data but with enormous scope.

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Data may remain collected from publicly shared comments on social media and websites, voluntarily collected from electronic devices and personal applications, through questionnaires, product purchases and electronic records. The attendance of sensors and other inputs in smart devices allows data to remain collected in a wide range of situations and circumstances.

The History of Big Data

Around 2005, people began to realize the amount of data users generated through Facebook, YouTube, and other online services. The same year, Hadoop (an open-source framework built specifically for storing and analyzing large data sets) remained developed. NoSQL also started to gain fame during this time.

The growth of open-source frameworks such as Hadoop (and, more recently, Spark) was essential to the progress of big data because they make big data easier to use and cheaper to store. In the years that followed, the volume of big data skyrocketed. Users continue to generate vast amounts of data, but it’s not just humans doing it.

With the arrival of the (IoT) Internet of Things, more objects and devices are connected to the Internet, collecting data on customer usage patterns and product performance. The advent of machine learning has produced even more data.

Advantages and Disadvantages of Big Data

Companies that collect large amounts of data can perform deeper and richer analyses for the benefit of all stakeholders. They are increasing the amount of data available presents both opportunities and challenges. Overall, having more customer (and potential customer) data should allow companies to tailor product and marketing efforts better to create the highest level of customer satisfaction and retention.

While better analytics is good, big data can also create overhead and noise, reducing its usefulness. Businesses must manage large volumes of data and determine which data represents signals versus noise. Deciding what makes the information relevant becomes a key factor.

Structured data, consisting of some values, can be stored and sorted. Formless data, such as emails, videos, and text documents, may require the application of more sophisticated techniques before it becomes useful. In addition, the nature and format of the data may require special treatment before processing.

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