In continuation of the previous blog – www.techtreeindia.com/blogger/2018/11/29/different-types-of-data-analytics-you-need-to-know-rn/, which was the first installment of the series, we now dig deeper into the different terminologies used in data analytics. If you want to achieve big in data analytics, you must get a grip around these terminologies. Below, we’ve rounded up some of the most popular data analytics terminologies along with their meanings:
Business Intelligence – It refers to a collection of intelligence applications that has the ability to extract data from internal and external sources and help professionals devise crucial decisions for a healthy growth of an organization.
Avro – Reckoned as a data serialization structure, it encourages encoding of a database schema in Hadoop.
Big Data Scientists – Also known as data ninjas, big data scientists are a horde of professionals who tames data and make them efficient tools of drawing insights and boost company growth. They develop complex algorithms and infuse meaning into data.
Cassandra – It is an open source and well-segregated database system. Facebook is the mastermind behind developing Cassandra so as to manage huge volumes of data and ease off data analysis.
Database – It is referred to a hefty digital collection of data, all logically-related and shared.
Database Management System (DBMS) – It is advanced software that develops and manages database structures in their structured format.
Data Collection – It is the process in which data is collected for a decent presentation.
Data Science – It is the very discipline that employs the use of statistical tools, machine learning, data visualization, computer coding and data mining database for solving challenging issues within an organization.
Machine Learning – It is an application of artificial intelligence using algorithms to help computers analyze data with an objective of extracting out meaningful information. It aids in taking specific actions based on any particular event of pattern.
Automatic Identification and Capture (AIDC) – It is the method that automatically identifies and gathers data on products, and stores them within a computer system.
Behavioral Analytics – This is a fairly new branch of data science and big data analytics that comprehends people’s behavior, their intentions and thereby predicts their future action, all using data.
Classification Analysis – It is defined as a systematic process of hoarding critical and relevant information about raw data and its subsequent metadata.
Data Cleansing – The process of reexamining and revising data with a sole aim to strike off duplicate entries, check for spelling mistakes and add missed out data.
Data Migration – It refers to the process of transporting data from one storage setup or server to another without changing its format.
Now that you know the most common terms used in data analytics, you are a bit closer to ace the skills of data analytics. However, if you want to master the skills in a more profound way, avail comprehensive data analytics courses in Kolkata. They help you understand the intricacies of this fairly new field of IT.