We recently had a write-up on Big Data stating how powerful Big Data is to transform business for industries. However, we indolently missed to bring to the attention of readers about a single, mighty technology – Machine Learning, the technology that makes Big Data a handy tool for business entrepreneurships. And this story covers many important aspects everyone wants to know in transforming business models. In fact, we are all living in an unprecedented world of technologies where transformations happen and cause the denouement of many and germination of others keeping up the equilibrium of entrepreneurial culture.
Machine learning is bestrewed across engineering, sciences, and commercial applications. In brief, Machine Learning acts as an effective tool for using unstructured and semi-structured data in the most prominent way which are available in different forms from different sources. In this blog, we will be discussing how and from where Big Data came from and how the term ‘Machine Learning’ originated?
It is all about data
Data are distinct pieces of information that are generated from structured or cleaned sources. Data are spread in different forms and types. They are predominantly categorised into unstructured, semi structured, and structured data, that are in forms of numbers or text on pieces of papers, as bits and bytes stored in electronic machines, and facts stored in a person’s mind.
In the perspective of predictive analysis, data is the source for extracting information. By analyzing data, we can forecast the future. When we can derive patterns or functions from data, we can also predict the future using the pattern or function. Informations are generated from the structured or cleaned data. Informations are lately formed to become the stepping stones to the future.
How data became big data?
Data gears up from many sources. During the gradual soaring changes in the sources of data, it’s quite habitual to witness an elevation in the volume of data. Social media channels, sensors that communicate, employees, e-commerce, online banking, and electronic machines generate a huge amount of data. It turns data from gigabytes to exabyte storage spaces. This enlargement in the source of data or the collection of data irrespective of its relevance reasons the formation of big data.
How Machine Learning works with Big Data?
Now there is a huge amount of data. Analysing this collection of data we can study the past and can also generate a function to forecast the future. Forecasting the business logic is the leading technique to improve business with better strategies. Now a days, it is required to look back to the past and study what happened in the past. By analysing the past studying the characteristics of the data will help you to create a pattern to predict the future, which is Machine Learning. Pattern analysis and creation of mathematical models are the core functions in this process. Analysing the huge amount of data from past sources, recognising patterns and create a mathematical model from such patterns we can forecast the future of the business product.
By analysing the big data we can find the features of data, and classify data into different classes using different types of classification algorithms. Using the same pattern, we can predict what the world was like. On the other hand, we can derive a pattern or a mathematical model to forecast the future using regression and correlation algorithms.
Briefing Machine Learning
Machine learning is artificial intelligence that provides self learning ability to systems from the huge amount of data so that systems can analyse the past and predict the future trends using data. Machine learning advanced from the study of pattern recognition and computational learning theory. This makes computer programs to learn themselves to act accordingly when mated with new data without being explicitly programmed. Machine Learning is also known as predictive analytics.