Last updated on Nov 07, 2023
Businesses are searching for relationships between data sets to reveal valuable insights. Taking advantage of the best features of each data set is a business dream. The new and unexpected patterns obtained from the analysis of data can help businesses find new solutions to complex problems. Looker helps enterprises in building relationships in their data and getting insights out of it.
In this post, we will be giving you an overview of Looker interview questions. Go through the below frequently asked Looker interview questions and answers that help in enhancing your knowledge.
Ans: Organizations small and large, carry out several processes or transactions which will result in generating humongous data. The data holds valuable information that could help improve business. That’s where the Business Intelligence tools come into the picture and help us explore data in meaningful ways. Processing the data in time and proper reporting enhances the ability to make more informed and data-driven decisions.
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Ans: SSIS is the abbreviation for SQL Server Integration Service. It is a component of the Microsoft SQL Server database and is used to build workflows for data migration tasks. It is an ETL tool that extracts data from different sources, transforms it, and loads it in a different destination.
Ans: There are three categories in the data flow.
Ans: Looker's business intelligence software helps in exploring and analyzing data. We can combine data from different sources and create a unified view. We can then build real-time analytics on top of the data and share them easily. It offers great visualizations and drill-down dashboards.
Ans: Here are some of the many advantages of Looker BI.
Ans: Online transaction processing (OLTP) supports data processing of transaction-oriented applications. It focuses on the day to day transactions of an organization. It involves updating, inserting, deleting small chunks of data in a database. Since it operates on data of small size, the processing speed is faster.
Ans: The SQL Server Deployment is preferred when compared to File System Deployment. The processing time is faster, so it gives quick results. It also won't compromise the safety of the data.
Ans: There are three modes available in Looker.
Ans: Full cache mode is the default cache mode selection. The reference result set will be cached before the execution. It will then retrieve and store the entire set of data from the specified lookup location. Full cache mode is best used when we have to deal with a large data set.
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Ans: The no-cache mode is used when the reference data set is very large to load into memory. The partial cache mode is used when the size of the data is relatively small. The lookup index in the partial cache mode is well-indexed and gives faster responses.
Ans: Yes, the logs are related to the package level. You can enable logging for the package through the logging configuration.
Ans: The following are some of the differences between DTS and SSIS.
Ans: Drill down is a capability provided by most BI tools. It helps in viewing the data in a detailed manner and gives in-depth insights. You can drill-down on a component in a report or dashboard to get more granular details of it.
Ans: The "Rebuild Derived Tables and Run" button is used to rebuild all persistent derived tables given in the query. It will also rebuild all the upstream PDTs.
Ans: Yes, we can reference a derived table within the SQL of another derived table by using a concept called cascading. You can use the following syntax to achieve it.
Ans: No, we don't have to set up a scratch schema. For the MySQL family of databases, we need to perform some additional setup to allow ephemeral derived tables.
Ans: The Native derived tables (NDTs) is defined in the LookML. We can create a native derived table by specifying the explore parameter on the base table with desired columns.
Ans: Looking at data in multiple dimensions makes it easy to consume the data visually. To change the dimensions, we can use the pivot option that turns a dimension into a column. We can only change the pivoted dimensions order by changing the sort order.
Ans: Heap captures user behavior like clicks, taps, gestures, and more across websites and applications automatically. It allows data enrichment with custom APIs. This will help in analyzing user actions and present them visually.
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Ans: Below are the important stages of an analytical project.
Ans: The high-level steps of troubleshooting PDTs are,
Ans: Using templated filters is not usually recommended. The table will be rebuilt every time the filter changes, and it causes a lot of strain on the database.
Ans: When you change the SQL of a derived table and query it, a new copy of the table is built in the PDT. The table copies only get created when the SQL in dev mode is different from the production mode.
Ans: The sort order is very important when using an offset list function. It defines whether to go up the table or down the table.
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Ans: Yes, we can base a table calculation on a particular pivoted column using the pivot_where function. The column given for the pivot_where field specifies that it should be targeted for calculation.
Ans: Yes, we can filter data using yes or no logic in table calculations.
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Ans: Table calculations run after the query has returned. They operate on the data in the explore table.
Ans: Looker Blocks are the pre-built pieces of LookML code that accelerate analytics. We can use these Looker blocks and customize them to your specifications. They enable building quick and flexible analytics.
Ans: There are six types of Looker blocks.
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