Data analytics course
WHAT IS DATA ANALYTICS
Data analytics is the branch of technology that deals with a qualitative and quantitative approach towards data and deriving valuable insights by analyzing the given data or information. It involves many major procedures like extraction of useful data or information, categorization of data to analyze relations, patterns and connections to arrive at an output.
Most companies and organizations today have adopted data analytics for analyzing data related to business, market, stocks etc. to measure the amount of success or profit the company or business achieves in a particular domain.
NEED FOR DATA ANALYTICS
Data analytics has become an essential technology to be employed in businesses and industries to analyze market trends of a product, consumer feedback and to derive possible relations that could help in the future success of the product or service.
Today, everything revolves around data and technology. With the vast amounts of data present for everything, there is a need to analyze the data to make decisions about the future of certain products and services or to analyze the success of a product or service in the retail market.
TYPES OF DATA ANALYTICS
There are four major branches of data analytics- prescriptive analytics, predictive analytics, diagnostic analytics and descriptive analytics.
Prescriptive analysis refers to the data analytics method that analyses based on recommendations and rules in order to determine a certain path of analytics in the organization or business.
Predictive analytics refers to the type of analytics that uses data to predict the future action course or path. It describes the future of data by analyzing the past of the given data or information. A good example would be ascertaining how successful a product or service would be in the retail market.
Diagnostic analytics refers to the method of data analytics that uses the past of the data to determine how and why a certain thing or outcome happened and revolves mainly working on a dashboard. It is used to mainly determine why a specific course of action happened or occurred. An example would be a survey to determine why a certain social media page is popular.
Descriptive analytics refers to the type of data analytics that works based on incoming data and data mining on which the analytical model is applied and the data is thus analyzed and described. A good example of descriptive analytics would be a credit based assessment.
QUALIFICATIONS NEEDED TO BE A DATA ANALYST
A good data analyst must have thorough knowledge of various programming languages, especially Python and R and should also be knowledgeable in various subjects like mathematics, statistics, data visualization, data modelling, machine learning and deep learning, algorithms etc.
A data analyst must also be good at machine learning algorithms to incorporate it into computer systems for faster and more accurate analysis of data and information. Computers can perform data analysis on huge volumes of raw information much easier and faster than a professional data analyst or data scientist.
RESOURCE BOX
There are many online and offline portals offering data analytics training which is very beneficial for those looking to have a successful career in the field of data analytics and engineering and such courses can help boost the career.
Contact:-
360DigiTMG
2-56/2/19, 6th floor, Vijaya towers near Meridian school, Ayyappa Society Rd, Madhapur, Hyderabad, Telangana 500081
9989994319
For more info Click here
For more Details Click here
Source link : Click here
