List the best data cleaning methods?

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Strong skills and ability to accurately analyze, organize, collect and disseminate big data.
Technical knowledge in database design, data models, data mining and segmentation methods.
Confident knowledge of statistical packages for analyzing large data sets ( SAV , Excel , SPSS, etc.)

3) Mention what are the different stages of an analytical project?
The various stages of an analytical project include:

Problem Definition
Data Research
Data preparation
Modeling
Data verification
Implementation and tracking
4) Mention what is data cleaning?
Data cleaning, also called data cleansing, is the process brazil consumer mobile number list of identifying and removing errors and inconsistencies in data to improve its quality.


Some of the best data cleansing practices include:

Sorting data by different attributes
For large datasets, clean the data in stages and improve the data at each stage until you achieve good data quality.
For large data sets, break them into smaller data sets. Working with smaller amounts of data will increase the speed of iteration.
To solve a common cleaning task, create a set of utility functions/tools/scripts. This could include remapping values ​​based on a CSV file or SQL database, or searching and replacing regular expressions, excluding all values ​​that do not match the regular expression.
If you have data cleanliness issues, sort them by expected frequency and address the most common issues.
Analyze the summary statistics for each column (standard deviation, mean, number of missing values).
Keep track of each date clear operation so that you can reverse the changes or remove the operations if necessary.
Data Analyst Interview Questions
Data Analyst Interview Questions
6) Explain what is logistic regression?
Logistic regression is a statistical method for examining a set of data in which there are one or more independent variables that determine the outcome.