Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can help inform decision-making. This practice uses various techniques, including statistical analysis, machine learning, and data mining, to extract valuable information from datasets. Data analytics is crucial for businesses, as it enables organizations to optimize operations, improve customer experiences, and enhance strategic planning.
The key types of data analytics include descriptive analytics (which summarizes past data), diagnostic analytics (which explores the reasons behind certain outcomes), predictive analytics (which forecasts future trends), and prescriptive analytics (which recommends actions based on data).
With the growing availability of big data and advanced technology, data analytics has become an indispensable tool across industries such as finance, healthcare, marketing, and retail. By leveraging data analytics, companies can make data-driven decisions that improve efficiency and drive growth.
Course Content
Data Analytices
Class1:Complete data analysis work flow
00:00Class2:Loading dataset in your jupyter notebook
00:00Class3:Loading dataset in your jupyter notebook
00:00Class4:Dealing with missing values
00:00Class5:Dealing with inconsistent values
00:00Class6: Dealing with miss identified data types
00:00Class7:Dealing with duplicated data
00:00Class8:Learn data sorting and arrangement
00:00Class9:Learn to merge extra variables
00:00Class10:Learn to concatenate extra data
00:00Data Analysis
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