Post by account_disabled on Mar 7, 2024 0:45:40 GMT -4
Speed with which new data is generated and reaches the system that performs analysis on it; Variety , i.e. various types of data that are generated, accumulated and used. In relation to the last characteristic (variety) the data used can be of various types: Structured , these are the data used before the advent of Big Data, i.e. collected for the same purposes for which they are processed, according to predefined fields and with ad hoc formatting; Unstructured , data stored in its native format and not processed until used. The advantage lies precisely in the accumulation rates (higher than structured ones) and the freedom of the original format. Examples of this include emails, social media posts, chats, images, etc.
Semi-structured , that is, they have metadata that identifies Greece Telegram Number Data some characteristics and therefore have sufficient information to catalogue, search and analyze them, a middle ground between the first two. Data science deals with discovering the links between different phenomena, very often correlations, and predicting the phenomena on the basis of statistical calculations, also in the business context. Big data is therefore the basis of data storytelling : to build a narrative that has solid foundations and whose purpose is to highlight the performance of an activity or business process, highlight a problem or produce insights useful for decisions future, it is necessary to start from concrete and significant bases from a statistical point of view, therefore generalizable.
Searching for patterns in the data It is the second important element of data storytelling: it is not enough to collect data, but obviously the next step is to interpret it to draw conclusions or rather insights. In this sense it is necessary to look for significant relationships between the data and explore them in search of patterns that are significant. Big data allows different types of analysis: Descriptive analysis , where the tools used serve to describe the current and past situation of company processes and/or functional areas. Predictive analysis , in which the tools develop hypotheses and forecasts based on statistical forecasts Prescriptive analytics , in addition to data analysis and statistical forecasting, are capable of proposing solutions.
Semi-structured , that is, they have metadata that identifies Greece Telegram Number Data some characteristics and therefore have sufficient information to catalogue, search and analyze them, a middle ground between the first two. Data science deals with discovering the links between different phenomena, very often correlations, and predicting the phenomena on the basis of statistical calculations, also in the business context. Big data is therefore the basis of data storytelling : to build a narrative that has solid foundations and whose purpose is to highlight the performance of an activity or business process, highlight a problem or produce insights useful for decisions future, it is necessary to start from concrete and significant bases from a statistical point of view, therefore generalizable.
Searching for patterns in the data It is the second important element of data storytelling: it is not enough to collect data, but obviously the next step is to interpret it to draw conclusions or rather insights. In this sense it is necessary to look for significant relationships between the data and explore them in search of patterns that are significant. Big data allows different types of analysis: Descriptive analysis , where the tools used serve to describe the current and past situation of company processes and/or functional areas. Predictive analysis , in which the tools develop hypotheses and forecasts based on statistical forecasts Prescriptive analytics , in addition to data analysis and statistical forecasting, are capable of proposing solutions.