Data Science and Analytics Course
Data is everywhere. In fact, the amount of digital data that exists is growing at a rapid rate—in fact, more than 2.7 zettabytes of data exist in today’s digital universe, and that is projected to grow to 180 zettabytes in 2025. Data Science and Analytics Course is all about analyzing and extracting right info.
All this data—from your photos to the Fortune 500’s financials—has only recently begun to be analyzed to tease out insights that can help organizations improve their business. That’s why more organizations are seeking professionals who can make sense of all the data.
It is easy enough to become a data scientist. Once you get the art of data analysis right, it is just a matter of practicing your newly-found skills well enough to become proficient.
What is a data scientist? What do data scientists do? Data scientists combine statistics, mathematics, programming, problem-solving, capturing data in ingenious ways, the ability to look at things differently to find patterns, along with the activities of cleansing, preparing, and aligning the data.
Dealing with unstructured and structured data, Data Science is a field that encompasses anything related to data cleansing, preparation, and analysis. Put simply, Data Science is an umbrella term for techniques used when trying to extract insights and information from data.
What is a big data analyst? According to Gartner, the definition of Big Data reads, “Big data is high-volume and high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision-making, and process automation.” Big Data analytics find insights that help organizations make better business decisions.
A buzzword that is used to describe immense volumes of data, both unstructured and structured, Big Data inundates organizations of all sizes on a day-to-day basis. In other words, Big Data refers to humongous volumes of data that cannot be effectively processed with traditional applications. The processing of Big Data begins with the raw data that isn’t aggregated or organized—and is most often impossible to store in the memory of a single computer.
What is the role of a data analyst? Data Analytics is the science of examining raw data with the purpose of finding patterns and drawing conclusions about that information by applying an algorithmic or mechanical process to derive insights. According to Forbes, the big data analytics market will surpass $200 billion soon.
The work of a data analyst lies in inference, which is the process of deriving conclusions that are solely based on what the researcher already knows; for example, running through a number of data sets to look for meaningful correlations between each other. Data Analytics is used in a number of industries to enable organizations to make better decisions as well as verify and disprove existing theories or models.
Data Science and Analytics Course is customized to cater everyone’s need.