Data analytics can also be phrased as an agile methodology where useful/relevant/appropriate information is gathered as a pool and can be inspected and analyzed for future references. This form of data can also be used or compared to future referrals. We have made tremendous progress in the field of technology and science. Analytics refers to the systematic computational analysis of data. It interprets meaningful patterns. Collected facts and statistics put together to give you data. Data are collected and analyzed to answer questions. Data analytics is a process of obtaining raw data and converting it into useful information. Once the data are cleaned it can be analyzed, analysts will be applying a variety of techniques which is referred to as exploratory data analysis.
TYPES OF DATA ANALYTICS
1)DESCRIPTIVE ANALYTICS: – Descriptive analytics answer the question of what happened; it collects raw data from multiple sources to give valuable insights.

2)DIAGNOSTIC ANALYTICS: – There is a possibility to find out dependencies and to identify patterns. Usually, companies go for diagnostic analytics as it gives useful/essential insights.

3)PREDICTIVE ANALYTICS: – It tells what is likely to happen. It brings the findings of descriptive and diagnostic analytics to predict future trends. Even though it gives numerous advantages, one must understand that forecasting is just an estimate and therefore requires careful treatment and continuous optimization.

4)PRESCRIPTIVE ANALYTICS: – The purpose of prescriptive analytics is to tell as to what the actions are to be taken. This is used to eliminate future problems.
COURSES IN DATA ANALYTICS: –
INTRODUCTION TO DATA ANALYTICS: – In this course, one will get to opportunity to learn about data analytics, its types and its advantages in the industry.
PYTHON PROGRAMMING: – In this course, you will be able to learn/understand the programming language, the data types and its various functions.
INTRODUCTION TO PANDAS: – Pandas is one of the most important libraries which provides high performance and is easy to use for data analysis.
DATA VISUALISATION: – This course will cover Matplotlib and Seaborn which are essential in visualization, and these are the main libraries which will help in creating different types of plots and various figures.
ADVANCED DATA ANALYSIS USING PANDAS: – In this course, you will be learning about data wrangling, text mining and time series analysis.
APPLIED STATISTICS AND MACHINE LEARNING: – Here, you will be learning about various concepts of the machine and also about the sci-kit library.

We get five benefits by using data analytics: –
1)PROACTIVITY AND ANTICIPATING NEEDS: – Proactive means doing a job meticulously and quickly. By sharing data with business customers expect companies to know about the data and to anticipate their needs.
2)DELIVERING RELEVANT PRODUCTS: – Effective data and analytics help the companies to stay competitive even when the demand changes. It makes them know about the market demand and provides the relevant product effectively.
3)PERSONALISATION AND SERVICE: – The data offers the opportunity to interact with customers based on their personality; it does this by understanding customers attitudes and helps to deliver in a service environment.
4)OPTIMISING AND IMPROVING THE EFFICIENCY OF OPERATION: – Using analytics for business operations ensures efficiency and effectiveness which will be used to fulfil customers expectations.
5)REDUCING THE RISK AND FRAUD PRACTICES: – Everything in the analytics are secured from internal and external threats. Even though at present the fraud factors are getting improvised day-by-day the analysts are making their best to overcome this.

A business can be benefitted from data analytics to get positive outcomes for the business and also to the customers. With various types of analytics companies are free to choose their own data analytics which they feel would compromise/satisfy their business at its best.

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