Data is growing worldwide at an exponential rate. Current estimates put the amount of global data at around 40 zettabytes and the expectation is that by 2025 this will have increased to 175 zettabytes. Data is being created on a daily basis from a multitude of different sources. Whether it is the individual with their smartphone, the business with a spreadsheet or one of the millions of connected IoT devices currently online – the sheer amount of data being generated is massive.
Big data is a phrase that encompasses this massive amount of data. Big data covers both structured and unstructured data. Concerning big data, the amount of data itself is not the issue at stake. What is more important is what is done with this data. The term was popularized in the early 2000s and specifically talks about Volumes of data being received at Velocity by organizations in a Variety of different formats. These three V’s are at the heart of any Big Data definition.
The phrase Big Data was popularized in the early 2000s and specifically talks about Volumes of data being received at Velocity by organizations in a Variety of different formats. These three V’s are at the heart of any Big Data definition.
More recently the definition of Big Data has expanded to include Value and Veracity. The two new V’s speak to the fact that while data by itself has intrinsic value, it is not really useful to the world until that value is realized. Similarly, with veracity, if data is incorrect, then it is unreliable and cannot be used.
Data is not just being generated by humans anymore. With more and more devices being connected to the Internet daily, data is being generated at an ever-increasing rate. Big data helps to take this information and transform it into something actionable. For businesses looking to leverage this data effectively, partnering with a reliable AI data collection company can be invaluable.
Big Data can help companies to make smart decisions faster and more efficiently. Data coming from a multitude of different sources can be analyzed with a host of different tools to provide meaningful insights for company leaders.
When Big Data is paired up with AI, efficiencies can be dramatically improved. AI with its ability to learn can search for specific patterns and extrapolate out, based on the information obtained. With the help of AI, data analytics is less labor intensive as AI continues to create new systems and processes. While AI has not completely removed the need or requirement for people in the analysis phase, it has made it a less time intensive need.
One significant way that AI can help is through its ability to weed out outliers. This allows AI systems the intelligence to eradicate bad and duplicate data ensuring only useful information gets processed and used. By using information that is validated and correct, AI systems and tools are better able to predict future outcomes helping companies improve their overall strategy.
