Descriptive analytics is a type of analytics that uses historical data and summarizing it into meaningful patterns, such as the analysis of customers’ purchasing histories. Descriptive analytics provide the “what has happened” information.
Predictive analytics is a type of analytics that looks at historical data, identifies patterns and trends, and then uses them to predict future events and outcomes. Predictive analytics can help organizations make better decisions and anticipate needs and future demands.
Data is typically defined as information that is stored and organized in a structured manner that can be easily analyzed. Big data, on the other hand, is large, complex collections of data that typically contain many different types of data sources and formats. Big data can include a wide variety of data types such as images, audio, video, and text. Big data can also come from sources such as social media, mobile devices, financial transactions, and sensors. Big data can often contain more than Terabytes of data and must often be analyzed using different techniques such as machine learning.
Companies use big data to gain insights on customer behavior, market trends, and operational efficiency. By analyzing large sets of data, businesses can better understand their current market and customer needs, as well as anticipate future customer behavior. This can help companies make more informed decisions, predict future customer needs, and ultimately improve operational efficiency. This can be especially useful in industries such as e-commerce, where data-driven decisions can help a company reduce costs and boost profits.
Radio Frequency Identification (RFID) is a type of automated data capture technology that utilizes radio waves for communication between a tag consisting of an antenna, a transceiver and a processor, and a reader. The transponder embedded in the tag contains a unique identification code that is read by the reader, which in turn allows the reader to identify, locate and track objects in a supply chain. RFID tags can be affixed to goods, assets and personnel to ensure tracking, authentication, control and visibility throughout the supply chain.
Hi Leonid,
I think you did a good job highlighting the differences between data and Big Data. In general, what kind of problems do you see arising from Big Data? I think it’s astonishing how 90% of all data was created in the last 2-3 years, and although Big Data can be useful for companies in providing insights, I think the sheer amount of Big Data that exists is coming in at a much faster rate than humans can process, even with the help of computer software. I really like how you mentioned how Big Data contains many different types of data sources and formats–I think a big difference between regular data and Big Data is that regular data is sorted and has the same format. Big Data is mixed and contains many different formats, making sorting it more difficult. Hopefully, as we accumulate more data, we will also figure out how to process the large amounts that it is being created.