In time series analysis, the process of transforming a non-stationary series into a stationary series is known as _______.
- Aggregation
- Decomposition
- Differencing
- Smoothing
The blank is filled with "Differencing." Differencing is the process of transforming a non-stationary time series into a stationary one by computing the differences between consecutive observations. This helps remove trends and seasonality, making the series more amenable to modeling and analysis.
How does the principle of 'small multiples' aid in comparative data analysis?
- It emphasizes the use of small-sized charts to fit more data on a single page, improving visualization density.
- It focuses on reducing the overall size of the dataset to simplify analysis, making it more manageable.
- It involves breaking down a dataset into small, similar subsets and presenting them side by side for easy comparison, revealing patterns and trends.
- It suggests using minimalistic design elements to create a clean and uncluttered visual presentation of data.
The principle of 'small multiples' involves creating multiple, small charts or graphs, each representing a subset of the data. This aids in comparative analysis by allowing users to quickly identify patterns, trends, and variations across different subsets.
________ in ETL helps in reducing the load on the operational systems during data extraction.
- Cleansing
- Loading
- Staging
- Transformation
Staging in ETL involves temporarily storing extracted data before it is transformed and loaded into the target system. This helps reduce the load on operational systems during the data extraction phase.
When preparing a report, a data analyst should always consider the _______ of the intended audience.
- Background
- Expertise
- Interests
- Preferences
Considering the expertise of the intended audience is crucial when preparing a report. Tailoring the content to match the audience's level of expertise ensures that the information is both relevant and comprehensible to the readers.
In Big Data, what does NoSQL stand for?
- New Object-oriented SQL
- No Serialized Query Language
- Non-sequential Query Language
- Not Only SQL
NoSQL stands for "Not Only SQL." It is a category of databases that provides a mechanism for storage and retrieval of data that is modeled in ways other than the tabular relations used in relational databases.
For a case study focusing on predictive analytics in sales, what advanced technique should be used for forecasting future trends?
- Clustering
- Decision Trees
- Linear Regression
- Time Series Analysis
Time Series Analysis is the most appropriate technique for forecasting future trends in sales. It considers the temporal aspect of data, making it suitable for predicting patterns and trends over time, which is crucial in sales predictions.
The process of adjusting a machine learning model's parameters based on training data is known as _______.
- Evaluation
- Optimization
- Training
- Tuning
The process of adjusting a machine learning model's parameters based on training data is known as Tuning. It involves fine-tuning the model to achieve better performance and generalization on unseen data.
What role does a data steward play in ensuring data quality?
- A data steward ensures data quality by overseeing data management processes, defining data quality standards, and resolving data issues.
- A data steward focuses solely on data analysis.
- A data steward is not involved in data quality initiatives.
- A data steward is responsible for creating data silos.
Data stewards play a crucial role in ensuring data quality. They define and enforce data quality standards, monitor data quality metrics, and collaborate with data users to address any issues, contributing to overall data quality improvement.
What is the significance of 'stakeholder analysis' in the context of data project management?
- It determines the hardware requirements for the project
- It ensures compliance with data privacy regulations
- It helps identify potential risks in the project
- It involves assessing the impact of the project on various stakeholders
Stakeholder analysis is crucial in understanding the impact of a data project on different stakeholders. It helps in effective communication, managing expectations, and ensuring that the project aligns with organizational goals. It is not primarily focused on risk identification or hardware requirements.
Which dplyr function is used to summarize data, like calculating the mean of a column?
- stat()
- summarise()
- summarize()
- summary()
In dplyr, the correct function for summarizing data, such as calculating the mean of a column, is summarize(). The alternative spelling summarise() is also accepted. summary() is a base R function used for statistical summaries, and stat() is not a valid function in this context.