Data Analytics

SQL commands Notes 🔥☺️

1. Define the term 'Data Wrangling. Data Wrangling is the process wherein raw data is cleaned, structured, and enriched into a desired usable format for better decision making. It involves discovering, structuring, cleaning, enriching, validating, and analyzing data. This process can turn and map out large amounts of data extracted from various sources into a more useful format. 2. What are the best methods for data cleaning? Create a data cleaning plan by understanding where the common errors take place and keep all the communications open. Before working with the data, identify and remove the duplicates. This will lead to an easy and effective data analysis process.Focus on the accuracy of the data. Set cross-field validation, maintain the value types of data, and provide mandatory constraints.Normalize the data at the entry point so that it is less chaotic. You will be able to ensure that all information is standardized, leading to fewer errors on entry. 3. Explain the Type I and Type II errors in Statistics? In Hypothesis testing, a Type I error occurs when the null hypothesis is rejected even if it is true. It is also known as a false positive. A Type II error occurs when the null hypothesis is not rejected, even if it is false. It is also known as a false negative. 4. How do you make a dropdown list in MS Excel? First, click on the Data tab that is present in the ribbon.Under the Data Tools group, select Data Validation.Then navigate to Settings > Allow > List.Select the source you want to provide as a list array. 5. State some ways to improve the performance of Tableau? Use an Extract to make workbooks run faster. Reduce the scope of data to decrease the volume of data. Reduce the number of marks on the view to avoid information overload. Hide unused fields. Use Context filters. Use indexing in tables and use the same fields for filtering. Remove unnecessary calculations and sheets.

1. What do you understand about the E-R model? Answer: E-R model is an Entity-Relationship model which defines the conceptual view of the database. The E-R model basically shows the real-world entities and their association/relations. Entities here represent the set of attributes in the database. 2. Explain the terms ‘Attribute’ and ‘Relations’ Answer: Attribute is described as the properties or characteristics of an entity. For Example, Employee ID, Employee Name, Age, etc., can be attributes of the entity Employee. Relation is a two-dimensional table containing a number of rows and columns where every row represents a record of the relation. Here, rows are also known as ‘Tuples’ and columns are known as ‘Attributes’. 3. What is the Database transaction? Answer: Sequence of operation performed which changes the consistent state of the database to another is known as the database transaction. After the completion of the transaction, either the successful completion is reflected in the system or the transaction fails and no change is reflected. 4. What do you understand about ‘Atomicity’ and ‘Aggregation’? Answer: Atomicity is the condition where either all the actions of the transaction are performed or none. This means, when there is an incomplete transaction, the database management system itself will undo the effects done by the incomplete transaction. Aggregation is the concept of expressing the relationship with the collection of entities and their relationships.

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1. What is the Difference Between a Shallow Copy and Deep Copy in python? Deep copy creates a different object and populates it with the child objects of the original object. Therefore, changes in the original object are not reflected in the copy. copy.deepcopy() creates a Deep Copy. Shallow copy creates a different object and populates it with the references of the child objects within the original object. Therefore, changes in the original object are reflected in the copy. copy.copy creates a Shallow Copy. 2. How can you remove duplicate values in a range of cells? 1. To delete duplicate values in a column, select the highlighted cells, and press the delete button. After deleting the values, go to the ‘Conditional Formatting’ option present in the Home tab. Choose ‘Clear Rules’ to remove the rules from the sheet. 2. You can also delete duplicate values by selecting the ‘Remove Duplicates’ option under Data Tools present in the Data tab. 3. Define shelves and sets in Tableau? Shelves: Every worksheet in Tableau will have shelves such as columns, rows, marks, filters, pages, and more. By placing filters on shelves we can build our own visualization structure. We can control the marks by including or excluding data. Sets: The sets are used to compute a condition on which the dataset will be prepared. Data will be grouped together based on a condition. Fields which is responsible for grouping are known assets. For example – students having grades of more than 70%. 4. Define Entity, Entity type, and Entity set. Entity can be anything, be it a place, class or object which has an independent existence in the real world. Entity Type represents a set of entities that have similar attributes. Entity Set in the database represents a collection of entities having a particular entity type.

1. List the different types of relationships in SQL. One-to-One - This can be defined as the relationship between two tables where each record in one table is associated with the maximum of one record in the other table. One-to-Many & Many-to-One - This is the most commonly used relationship where a record in a table is associated with multiple records in the other table. Many-to-Many - This is used in cases when multiple instances on both sides are needed for defining a relationship. Self-Referencing Relationships - This is used when a table needs to define a relationship with itself. 2. What are the different views available in Power BI Desktop? There are three different views in Power BI, each of which serves another purpose: Report View - In this view, users can add visualizations and additional report pages and publish the same on the portal. Data View - In this view, data shaping can be performed using Query Editor tools. Model View - In this view, users can manage relationships between complex datasets. 3. What are macros in Excel? Excel allows you to automate the tasks you do regularly by recording them into macros. So, a macro is an action or a set of them that you can perform n number of times. For example, if you have to record the sales of each item at the end of the day, you can create a macro that will automatically calculate the sales, profits, loss, etc and use the same for the future instead of manually calculating it every day.

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Data Analyst Interview Questions 1. Is indentation required in python? Indentation is necessary for Python. It specifies a block of code. All code within loops, classes, functions, etc is specified within an indented block. It is usually done using four space characters. If your code is not indented necessarily, it will not execute accurately and will throw errors as well. 2. What are Entities and Relationships? Entity: An entity can be a real-world object that can be easily identifiable. For example, in a college database, students, professors, workers, departments, and projects can be referred to as entities. Relationships: Relations or links between entities that have something to do with each other. For example – The employee’s table in a company’s database can be associated with the salary table in the same database. 3. What is a stored procedure? Stored Procedure is a function consists of many SQL statements to access the database system. Several SQL statements are consolidated into a stored procedure and execute them whenever and wherever required. 4. What is Auto Increment? Auto increment keyword allows the user to create a unique number to be generated when a new record is inserted into the table. AUTO INCREMENT keyword can be used in Oracle and IDENTITY keyword can be used in SQL SERVER. Mostly this keyword can be used whenever PRIMARY KEY is used. 5. Which operator is used in query for pattern matching? LIKE operator is used for pattern matching, and it can be used as -. 1. % – Matches zero or more characters. 2. _(Underscore) – Matching exactly one character.