To combine rows from two or more tables based on a related column, you use a SQL ________.
- COMBINE
- JOIN
- MERGE
- UNION
In SQL, the JOIN keyword is used to combine rows from two or more tables based on a related column. It allows you to retrieve data from multiple tables based on a related column between them.
How does 'commit' function in Git?
- To copy changes from the local repository to the remote repository
- To delete files from the repository
- To merge branches in Git
- To save changes in the local repository
In Git, 'commit' is used to save changes made to the local repository. It creates a snapshot of the changes, making it possible to track the project's history and revert to previous states if needed. Committing is a crucial step in the version control process.
What does the acronym KPI stand for in business analytics?
- Key Performance Indicator
- Key Performance Insight
- Key Progress Indicator
- Key Project Insight
KPI stands for Key Performance Indicator. These are measurable values that demonstrate how effectively a company is achieving key business objectives. KPIs help in evaluating performance and making informed decisions.
The process of continuously checking and ensuring the quality of data throughout the project life cycle is known as _________.
- Data Mining
- Data Quality Management
- Data Validation
- Data Wrangling
Data Quality Management involves continuously checking and ensuring the quality of data throughout the project life cycle. It includes processes to identify and correct errors, inconsistencies, and inaccuracies in the data.
What is the impact of big data technologies on data-driven decision making?
- Enhanced scalability and processing speed
- Increased data security concerns
- Limited applicability to small datasets
- Reduced need for data analysis
Big data technologies, with enhanced scalability and processing speed, enable organizations to process and analyze vast amounts of data quickly. This facilitates more informed and timely data-driven decision making.
In time series analysis, _______ is used to identify and describe cyclic patterns in the data.
- Exponential Smoothing
- Fourier Transform
- Linear Regression
- Logistic Regression
Fourier Transform is used in time series analysis to identify and describe cyclic patterns in the data. It represents the time-domain signal in the frequency domain, allowing the detection of periodic components in the time series.
How do you optimize a query that takes too long to execute?
- Use indexes, optimize joins, and minimize the use of wildcard characters in WHERE clauses.
- Increase the complexity of the query to obtain more detailed results.
- Add more tables to the FROM clause for a comprehensive dataset.
- Include redundant columns in the SELECT statement.
To optimize a slow query, you should use indexes, optimize joins, and minimize the use of wildcard characters in WHERE clauses. These practices help the database engine retrieve and process data more efficiently. Options 2, 3, and 4 are counterproductive and would likely worsen the performance.
_______ is an open-source tool for big data visualization which works particularly well with Hadoop data.
- Apache Superset
- Power BI
- QlikView
- Tableau
Apache Superset is an open-source tool designed for big data visualization. It integrates well with Hadoop data, providing a platform for creating insightful and interactive visualizations for large datasets. Tableau, Power BI, and QlikView are also popular visualization tools but may not be as tailored for Hadoop integration as Apache Superset.
What is the primary function of the SELECT statement in SQL?
- Create a new table
- Delete records from a table
- Retrieve data from one or more tables
- Update data in a table
The primary function of the SELECT statement in SQL is to retrieve data from one or more tables. It allows you to specify the columns you want to retrieve and apply conditions to filter the results.
What is the equivalent of SQL's JOIN operation in dplyr for merging two datasets?
- combine()
- inner_join()
- join()
- merge()
In dplyr, the inner_join() function is equivalent to SQL's JOIN operation. It merges two datasets based on matching keys, similar to the merge() function in Pandas. combine() and join() have different functionalities and are not direct equivalents to SQL JOIN.