Tuesday, March 26, 2024

Sql Interview Questions Data Science

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What Are Commits And Checkpoints

Real Data Science SQL Interview Questions and Answers # 1 | Data Science Interview Questions

The commit makes sure the data is consistent and maintained in the updated state after the current transaction ends. A new record is added to the log memory when a commit is used.

In the case of a checkpoint, it is used to write all the changes that are committed to disk up the system change number in the control files and header files.

Q57 What Are Entities And Relationships

Entities: A person, place, or thing in the real world about which data can be stored in a database. Tables store data that represents one type of entity. For example A bank database has a customer table to store customer information. The customer table stores this information as a set of attributes for each customer.

Relationships: Relation or links between entities that have something to do with each other. For example The customer name is related to the customer account number and contact information, which might be in the same table. There can also be relationships between separate tables .

Lets move to the next question in this SQL Interview Questions.

What Is The Significance Of P

p-value typically 0.05

This indicates strong evidence against the null hypothesis so you reject the null hypothesis.

p-value typically > 0.05

This indicates weak evidence against the null hypothesis, so you accept the null hypothesis.

p-value at cutoff 0.05

This is considered to be marginal, meaning it could go either way.

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Are You Wondering What Sql Interview Questions You Will Be Asked This Ultimate Guide Will Take You Through The Top Sql Interview Questions For Various Data Positions And The Tips To Approach Your Next Sql Interview

SQL is a must have tool in the arsenal of any aspiring data scientist. In this article we provide an outline to learn, prepare and ace your next SQL Interview for a Data Science role. We will explore why SQL is so widely used, then provide you a breakdown of SQL skills needed by each role viz Data Analyst, Data Scientist, Machine Learning Engineer, etc. Further, we provide you with real interview examples from the StrataScratch Platform illustrating a few of these skills and provide you with a step-by-step learning guide to become proficient with SQL even if you are not too familiar with SQL concepts and get your dream job.

So let us start off with why SQL is so widely used in the Data Science World.

Sql Interview Questions And Answers For Data Analyst

TOP 600 SQL SERVER INTERVIEW QUESTIONS ANSWERS EXAMPLES 4 FRESHER AND ...

30 Commonly Asked SQL Interview Questions and Answers for Data Analysts to nail their next analytics job interview.

Looking to land a job as a data analyst or a data scientist, SQL is a must-have skill on your resume. Everyone uses SQL to query data and perform analysis, from the biggest names in tech like Amazon, Netflix, and Google to fast-growing seed-stage startups in data. Before the world was taken over by the buzz of data science and analytics, data management still existed. Yes, you heard that right! Data was being managed, queried, and processed using a popular tool- SQL! SQL is considered the industry-standard programming language for extracting data, analyzing data, performing complex analysis, and validating hypotheses.

SQL is a highly desirable skill if you plan to become a data analyst or a data scientist. One cannot imagine having a successful career in data science or data analytics without mastering SQL.

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Aggregate Functions Used In Sql Interviews

Aggregate functions allow you to summarize information about a group of rows. For example, say you worked at JPMorgan Chase, in their Credit Card analytics department, and had access to a table called . This table has data on how many credit cards were issued per month, for each different type of credit card that Chase offered.

To answer a question like How many total cards were issued for each credit card youd use the aggregate function:

Entering this query on DataLemur yields the following output:

Similarly, if you wanted to count the total number of rows, you could use the aggregate function . To play around with this dataset, open the SQL sandbox for the JPMorgan SQL Interview Question.

While PostgreSQL technically has dozens of aggregate functions, 99% of the time you’ll just be using the big five functions covered below.

What are the most common SQL aggregate functions?

The 5 most common aggregate functions used in SQL interviews are:

  • – Returns the average value
  • – Returns the smallest value
  • – Returns the sum

While and aggregate functions may show up in advanced SQL interviews, they are extremely rare. To learn more about these uncommon commands, visit the PostgreSQL documentation.

What Is Dimensionality Reduction

Dimensionality reduction is the process of converting a dataset with a high number of dimensions to a dataset with a lower number of dimensions. This is done by dropping some fields or columns from the dataset. However, this is not done haphazardly. In this process, the dimensions or fields are dropped only after making sure that the remaining information will still be enough to succinctly describe similar information.

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Tiktok Data Science Interview Questions & Interview Prep Guide

If you’ve got an upcoming Data Scientist interview at TikTok, look no further â in this article we’ll cover 5 real TikTok Data Science interview questions, what these interviews generally cover, and tips and a guide on how to study for Data Science interviews at TikTok

Before we jump into real TikTok interview questions, I want to introduce myself so this isn’t just some random article by a random person you stumbled upon while frantically preparing for your TikTok interview. My name is Nick Singh, and I’m the author of the best-selling book Ace the Data Science Interview and founder of DataLemur . I’ve worked at Facebook and Google, so I absolutely understand how gruelling the technical interview process for data roles can be .

With that introduction out of the way, let’s get started with interview prep for TikTok!

Whats The Difference Between Inner And Left Join

Advanced Data Science SQL Interview Question [Amazon] (window functions & aliasing)

An SQL join allows you to display a result set that contains fields from two or more tables. Take a look at our Customer-Sale relationship without joins it would be impossible to display the customer name and the total sale amount in one result set. We need joins for that, and the two most widely used ones are INNER and LEFT join.

An inner join fetches only an intersection of two tables in our example that would be only the customers that have made the sale customer_id exists both in customer and sale tables.

A left join fetches all rows from the left table and tries to match them with the rows on the right table. If the value exists only in the left table, the columns from the right table will have the value of NULL. In our example that would mean that we fetch all the customers and match them with their sales, and put nulls to those customers who havent made the sale yet.

Lets examine this visually. Weve added another customer Jane that hasnt placed any orders yet. In the case of an inner join, she isnt displayed in the result set:

Image 4 Inner join demonstration

In the case of a left join, Jane is displayed in the result set, but her values for date of sale and the amount are NULL, as she didnt make any sales yet:

Image 5 Left join demonstration

SQL-wise, you would write these joins as follows:

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What Is Collation What Are The Different Types Of Collation Sensitivity

Collation refers to a set of rules that determine how data is sorted and compared. Rules defining the correct character sequence are used to sort the character data. It incorporates options for specifying case sensitivity, accent marks, kana character types, and character width. Below are the different types of collation sensitivity:

  • Case sensitivity:A and a are treated differently.
  • Accent sensitivity:a and á are treated differently.
  • Kana sensitivity: Japanese kana characters Hiragana and Katakana are treated differently.
  • Width sensitivity: Same character represented in single-byte and double-byte are treated differently.

Difference Between An Error And A Residual Error

The difference between a residual error and error are defined below –

Error

The difference between the actual value and the predicted value is called an error.

Some of the popular means of calculating data science errors are –

  • Root Mean Squared Error
  • Mean Absolute Error
  • Mean Squared Error

The difference between the arithmetic mean of a group of values and the observed group of values is called a residual error.

An error is generally unobservable.

A residual error can be represented using a graph.

A residual error is used to show how the sample population data and the observed data differ from each other.

An error is how actual population data and observed data differ from each other.

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What Is The Difference Between The Long Format Data And Wide Format Data

LONG FORMAT DATA: It contains values that repeat in the first column. In this format, each row is a one-time point per subject.

WIDE FORMAT DATA: In the Wide Format Data, the datas repeated responses will be in a single row, and each response can be recorded in separate columns.

Long format Table:

Sql Job Interview Questions For Data Scientists

Facebook Data Science Interview Question and Solution in SQL

This article was posted by Ankit Gupta.

Introduction:

If there is one language, every data science professional should know it is SQL. SQL stands for Structured Query Language. It is a programming language used to access data from relational databases.

We conducted a skilltest to test our community on SQL and it gave 2017 a kicking start. A total of 1666 participants registered for the skilltest.

This test focuses on practical aspects and challenges people encounter while using Excel. In this article, we provide answers to the test questions. If you took the test, check out which areas need improvement. If you did not take the test, here is your opportunity to look at the questions and check your sill level independently.

Two sample questions from the skilltest

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Out Of Collaborative Filtering And Content

Content-based filtering is considered to be better than collaborative filtering for generating recommendations. It does not mean that collaborative filtering generates bad recommendations.

However, as collaborative filtering is based on the likes and dislikes of other users we cannot rely on it much. Also, users likes and dislikes may change in the future.

For example, there may be a movie that a user likes right now but did not like 10 years ago. Moreover, users who are similar in some features may not have the same taste in the kind of content that the platform provides.

In the case of content-based filtering, we make use of users own likes and dislikes that are much more reliable and yield more positive results. This is why platforms such as Netflix, Amazon Prime, Spotify, etc. make use of content-based filtering for generating recommendations for their users.

Q10 List The Different Types Of Relationships In Sql

There are different types of relations in the database:

One-to-One This is a connection between two tables in which each record in one table corresponds to the maximum of one record in the other.

One-to-Many and Many-to-One This is the most frequent connection, in which a record in one table is linked to several records in another.

Many-to-Many This is used when defining a relationship that requires several instances on each sides.

Self-Referencing Relationships When a table has to declare a connection with itself, this is the method to employ.

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How Is Data Modeling Different From Database Design

Data Modeling: It can be considered as the first step towards the design of a database. Data modeling creates a conceptual model based on the relationship between various data models. The process involves moving from the conceptual stage to the logical model to the physical schema. It involves the systematic method of applying data modeling techniques.

Database Design: This is the process of designing the database. The database design creates an output which is a detailed data model of the database. Strictly speaking, database design includes the detailed logical model of a database but it can also include physical design choices and storage parameters.

Sql Usage In Data Science By Role

Advanced SQL Questions From Amazon (Handling complex logic in data science interviews)

Not every position in Data Science uses the same SQL concepts. While some roles will focus heavily on queries and query optimization, others will tend towards data architecture and ETL processes. One can divide SQL Commands asked in Data Science Interviews into the following categories.

  • Data Definition Language
  • – GRANT- REVOKE

A Data Analyst or a Data Scientist will be expected to mostly be working with the SELECT statement and associated advanced level concepts like subqueries, Grouping / Rollups, Window Functions and CTEs. If you work as an analyst, you probably already use SQL. It does not matter if you are a data analyst, reporting analyst, product analyst, or even financial analyst. Your position generally requires handling the raw data and using your skills to provide the management and other stakeholders with the decision-making insight.

Machine learning engineers are hybrid experts who are bridging the gap between data scientists and software engineers. As they serve as a bridge between those two positions, they need to have a certain set of skills from both worlds. They use those skills to design, build, and maintain the machine learning systems. To achieve that, they usually use several sets of skills:

  • predictive analytics

Develop a naive forecast for a new metric: distance per dollar. Distance Per Dollar is defined as the in our dataset. Calculate the metric and measure its accuracy.

Algorithm Outline:

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Database And Systems Design Interview Questions

  • For each of the ACID properties, give a one-sentence description of each property and why are these properties important?
  • What are the three major steps of database design? Describe each step.
  • What are the requirements for a primary key?
  • A B+ tree can contain a maximum of 5 pointers in a node. What is the minimum number of keys in leaves?
  • Describe MapReduce and the operations involved.
  • Name one major similarity and difference between a WHERE clause and a HAVING clause in SQL
  • How does a trigger allow you to build business logic into a database?
  • What are the six levels of database security and briefly explain what each one entails?
  • Say you have a shuffle operator, whereby the input is a dataset and the output is simply a randomly ordered version of that dataset. Describe the algorithm steps in English.
  • Describe what a cache is and what a block is. Say you have a fixed amount of total data storage – what are the some trade-offs in varying block size?
  • Explain Indexing In The Database

    Indexing is a data structure technique to optimize the database performance by reducing disk access during the time a query is being processed.

    Indexing has the following attributes:

    • Access Types: Based on the search type
    • Access Time: Based on search time
    • Insertion Time: Based on quick insertion
    • Deletion Time: Based on quick deletion
    • Space Overhead: Based on additional overhead space.

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    Get To Know The Your Potential Employer

    This is important in general, not only for the SQL part of the interview. It is important to be informed about your future employer, their products, and their industry. It is especially important when the SQL questions are regarded. Why is that?

    As we discussed earlier, the FAANG companies will usually ask you very practical SQL coding questions that will have you use the same data and solve the same problems as you would have to when you get employed. The FAANG companies are not the only ones who do that. So when you prepare for the interview, try to think which data is important to this company, how their database could look like, etc. When you practice the SQL questions, try to find the real questions from the companies you are interested in or at least from their competitors. If the companies are in the same industry, its quite likely the data they use will be more or less the same.

    Question #3 Find The First Unique Character In A String

    Noom SQL Interview Questions for Data Science

    Its a common question that will assess your basic programming skills.

    Problem description: Given a string s, find the first non-repeating character and return its index. If it doesnt exist, return -1.

    Seems easy, so lets give it a try. Remember to lowercase the input string, as letters A and a are identical:

    Heres the result from our test cases:

    Image 4 First unique character indices

    The first test string was Appsilon, and the first letter A occurs only once. In the string Appsilon Poland, both A and p are repeated, and the first unique letter is s. As for the last string, no character occurs only once, so -1 is returned.

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    How To Ace Data Science Interviews: Sql

    This is part of an ongoing series on interviewing for data science roles. You can check out the next part, covering statistics, here, and the third part on R and Python here..

    Data science interviews can be tough to navigate. The fact that its such a multi-disciplinary field means that the sheer volume of material you need to cover to feel properly prepared can become overwhelming.

    But Im here to help. Ive broken down what you need to know into four areas and will cover one in each part of this series: SQL, Statistics, Scripting, and Product. Each post will cover resources for learning the basics, an overview of important technical areas along with examples, and some notes on my general approach to interviewing in that area.

    If this is your first time interviewing for a data science role, going through this series should give you a solid idea of what to expect and how to prepare. But even if youve done this all before, Im hoping these articles will be useful in focusing your preparation on the skills that are most likely to be tested.

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