Start learning 50% faster. Sign in now
Data cleaning is widely regarded as the most challenging and time-consuming step in data analysis. Analysts often encounter issues such as missing data, inconsistent formats, outliers, and duplicate entries. Addressing these problems requires a meticulous approach to ensure data quality without losing valuable information. For example, cleaning customer survey data may involve filling missing age values using statistical imputation or correcting typos in categorical fields. Data cleaning underpins the reliability of subsequent steps like modeling and interpretation, making it a critical yet complex task. Why Other Options Are Incorrect: • A: While important, data collection is generally less time-consuming with well-defined sources. • C: Modeling complexity depends on the problem; simple models may suffice in many cases. • D: Visualization requires creativity but is less technically challenging than cleaning. • E: Interpretation is crucial but depends on having clean, reliable data.
Who is a good endorser for life insurance?
A motor insurance cover note is valid for how many days?
Which of the following is a policy document which is an evident of insurance contract issued by an insurer digitally signed in accordance with the appli...
Which of the following is insurable?
An agreement between an insurance company and an agent, granting the agent authority to write insurance from that company is called?
What is the purpose of a deductible in an insurance policy?
Which of the following is an example of a variable charge in a business?
The Indian insurance industry is governed by which of the following act ?
Which Insurance is a compulsory insurance plan administered by a government agency with the primary emphasis on social adequacy?
What is the purpose of a declaration policy?