What is BIG DATA? and the data types.

What is Big Data | Introduction and Application Of Big data

Big data refers to large and complicated data sets that are too big to handle or analyse efficiently with conventional data processing tools. It includes a broad range of data kinds, such as unstructured, semi-structured, and structured information. Semi-structured data, like XML or JSON files, lacks a formal structure but has tags or markers to divide parts. Structured data, on the other hand, is organised in a preset format, like databases and spreadsheets. Contrarily, unstructured data, which consists of text documents, photos, videos, and social media posts, is not organised according to a predetermined framework. Structured, semi-structured, and unstructured data are the three primary categories into which big data can be further subdivided according to its source and characteristics. Every kind offers unique analytical opportunities and challenges. but when used effectively, big data can provide valuable insights and drive informed decision-making across various industries and domains.

Comments

Post a Comment

Popular posts from this blog

Reasons for the growth of data

Image
The growth of big data is happening because of the way we interact with technology in our daily lives. One big reason is social media. Every time we post a photo, comment on a friend's status, or like a post, we're adding to the massive amount of data that social media platforms collect. This data helps these platforms understand what we like and what we're interested in, so they can show us ads and content that we're more likely to engage with. Another reason is the way businesses operate now. Companies are using big data to understand their customers better, like what products they buy and when they buy them. For example, online retailers can analyze our shopping habits to offer personalized recommendations or discounts. And let's not forget about new technology. With the rise of smart devices like fitness trackers and smart home assistants, we're generating even more data about ourselves and our environments. All of this data is valuable because it can help b...
Read more

Traditional statistics (descriptive and inferential)

Image
Traditional statistics function as a toolkit to assist us in interpreting data in many ways. In a sense, descriptive statistics represent a moment in time in the data's appearance. They aid in our understanding of properties of the data by summarising and describing its key elements, such as averages, percentages, and graphs. Conversely, inferential statistics enable us to extrapolate conclusions or forecasts about a broader population from a smaller sample. To test theories, arrive at judgements, and comprehend correlations between various variables, we employ inferential statistics. When combined, descriptive and inferential statistics provide us with a strong framework for comprehending and interpreting the world around us through  numbers and data.
Read more