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 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.
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.
For sequential pattern mining, the _______ algorithm is widely used to identify frequent sequences in data sets.
- Apriori
- DBSCAN
- FP-Growth
- K-Means
The FP-Growth algorithm is widely used for sequential pattern mining. It efficiently identifies frequent sequences in data sets by employing a tree structure to represent the relationships between sequential patterns.
For a dashboard handling large datasets, what strategy is crucial for maintaining performance and speed?
- Data Compression
- Data Duplication
- Data Normalization
- Indexing
Indexing is crucial for maintaining performance and speed in a dashboard handling large datasets. It allows for efficient data retrieval by creating a data structure that accelerates the retrieval of rows based on the values in one or more columns.
For recursive queries in SQL, the ________ keyword is often used.
- CONNECT BY
- HIERARCHY
- RECURSIVE
- WITH
The WITH keyword, also known as Common Table Expressions (CTE), is often used in SQL for handling recursive queries. It allows you to define temporary result sets that can be referenced within the context of the main query.
For a business requiring real-time analytics from geographically dispersed data sources, which cloud architecture would be most effective?
- Edge Computing
- Hybrid Cloud
- Multi-Cloud
- Serverless Computing
Edge computing would be most effective in this scenario. It allows real-time analytics by processing data closer to the source, reducing latency, and is ideal for geographically dispersed data sources.
In the context of time series, _______ refers to a model used for forecasting when data shows evidence of non-stationarity.
- ARIMA
- Exponential Smoothing
- Nonlinear Model
- Stationary Model
ARIMA (AutoRegressive Integrated Moving Average) models are suitable for forecasting when time series data exhibit non-stationarity, meaning the statistical properties change over time. ARIMA models involve differencing the series to achieve stationarity.
Which KPI would be most relevant for measuring customer satisfaction in a service industry?
- Employee Productivity
- Inventory Turnover
- Net Promoter Score (NPS)
- Revenue Growth
Net Promoter Score (NPS) is a widely used KPI for measuring customer satisfaction. It assesses the likelihood of customers recommending a company's products or services, providing valuable insights into customer loyalty and satisfaction.