The current age is popularly known as the digital age. There is data everywhere. Smart machines like our phones, fitness bands, laptops and other devices are continuously generating heaps of data every second in every nook and corner of the world. This data can range from a person’s health to market trends to financial transactions. There is no point of all this precious data if it cannot be read and understood. Data analysis is the science of reading and understanding all the data that surrounds us. The copious amounts of data generated from various sources in found in different formats. While some of this data can be structured, there is a lot of unstructured data as well. This complex and large amount of data is known as big data. There are various types of analytics certification courses available online and offline for students who are interested in this field. One of the best big data analytics courses that helps you to learn the science of organizing, collating, analysing and interpreting data. The professionals working in this field are known as big data analysts.
The online course that provide analytics certification provide a variety of courses such as basic data analytics, big data analytics, statistics, probability, randomization, quantitative methods, machine learning, deep learning etc. All these courses delve into various techniques of data analytics and prepare students for a career in this field. The techniques taught through these courses also provide the much-needed value to the businesses and processes in which they are applied.
According to IDC Canada, a Canada based IT research firm, Big Data Analytics is one of the top three things that mattered in the year 2013. The relevance of big data has only increased since then. Below are the 6 most important techniques to learn in data analytics and especially big data analytics –
- Machine Learning
Machine learning is the science of learning from data. It provides the smart devices the ability to learn using the data of the past in a continuous manner. It does not require any explicit programming and it also gains from the insights and data properties studied through the training data sets. Machine learning allows to target the customers with appropriate content as per their viewing history. It also helps distinguish between spam and non-spam mails. It can learn user preferences over time. It also determines the probability of winning legal cases basis the results of the older cases.
- Social Network Analysis
Social network analysis is a technique that involves the study of interpersonal relationships. It is applied for analysis of relationships between people from many commercial fields. It also has uses in finding out how people form relationships from other people outside of their fields. To find out the important of a person in a group or understand the social structure of a customer base.
- Classification Tree Analysis
This technique employs statistical classification to find out the category that a new observation belongs to. It is used to automatically assign documents to categories. It can categorize organisms and newly discovered species into groups. It also helps in developing student profiles who take different courses online.
- Sentiment Analysis
Sentiment analysis is a technique that is used to find out the sentiments or reactions of speakers or writers on any topic. This is used to analyse the feedback on any new service or product. It is also used to read the comments by buyers or guests. It is utilised to customise a company’s offerings according to customers’ needs and preferences. Additionally, it is also used in analysing the opinions generated on social media portals.
- Regression Analysis
Regression Analysis is a technique used for understanding the affect that an independent variable has on another dependent variable. By manipulating the independent variable, the affect on the dependent variable can be analysed. The change is value of the dependent variable due to the change in independent variable can provide a dependable result as long as continuous quantitative data is provided. For example, the impact of the music played in a store on the average time spent by customers in that store can be ascertained using regression analysis.
- Genetic Algorithms
Genetic algorithms are used to find useful evolved solutions to a problem that requires optimization. It is inspired by the concept of evolution and is based on mechanisms like inheritance, mutation and natural selection. For example, a television channel decides to alter its time of broadcasting a show in order to get highest ratings.
Data analytics has many more techniques up its sleeves. These techniques can be learnt through online through a data analytics certification course. For those, interested in statistical work, data analysis can be a highly rewarding career choice.