AI News, The Best Way to Learn SQL for Data Science

The Best Way to Learn SQL for Data Science

This is an open source course designed to teach you the SQL skills necessary for data science as quickly as possible.

In practice data science frequently involves taking a company’s data and figuring out how to make more money with that data.

This course uses the Microsoft’s Adventuresworks dataset because this artificial data is designed to mimic a real company’s data.

Once you feel that you have successfully completed the test questions there is a form at the bottom of the page where you can request the solutions for self review.

46 Questions on SQL to test a data science professional (Skilltest Solution)

If there is one language, every data science professional should know –

It is a query 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.

This test focuses on practical aspects and challenges people encounter while using Excel.

If you did not take the test, here is your opportunity to look at the questions and check your sill level independently.

More than 700 people participated in the skilltest and the highest score was 41. Here are a few statistics about the distribution.

I think we are seeing 3 different profiles of people here: How much did you score and where do you fit?

Basics of SQL and RDBMS – must have skills for data science professionals SQL commands for Commonly Used Excel Operations 1) Which of the following is the correct order of occurrence in a typical SQL statement?

Extract the unique course ids(cid) where student receive the grade C in the course C.

None of these Solution:  A The query will extract the course ids where student receive the grade “C” in the course.

None of these Solution: B By using DISTINCT keyword you can extract the Distinct course ids where student receive the grade of C in the course.

Query: SELECT name, cid FROM student, enrolled WHERE student.sid = enrolled.sid AND enrolled.grade = 'C' A.

None of these Solution: B The above query first joined the ENROLLED and STUDENT tables then it will evaluate the WHERE condition and then it will return the name of students and corresponding course id where they received the grade of C.

None of these Solution: A The above query first joined the ENROLLED and STUDENT tables then it will evaluate the where condition and then it will return the name, grade of the students, those took 15-415 and got a grade ‘A’ or ‘B’ in the course.  But for the given two tables it will give zero records in output.

SELECT DISTINCT e1.sid FROM enrolled AS e1, enrolled AS e2 WHERE e1.sid != e2.sid AND e1.cid != e2.cid B.

SELECT DISTINCT e1.sid FROM enrolled AS e1, enrolled AS e2 WHERE e1.sid = e2.sid AND e1.cid = e2.cid C.

SELECT DISTINCT e1.sid FROM enrolled AS e1, enrolled AS e2 WHERE e1.sid != e2.sid AND e1.cid != e2.cid D.

SELECT DISTINCT e1.sid FROM enrolled AS e1, enrolled AS e2 WHERE e1.sid = e2.sid AND e1.cid != e2.cid Solution: D Option D would be a right option.

This query will first apply self join on enrolled table and then it evaluate the condition e1.sid = e2.sid AND e1.cid != e2.cid.

Query1: INSERT INTO student (sid, name, login, age, gpa) VALUES (53888, ‘Drake’, ‘[email protected]’, 29, 3.5) Query2: INSERT INTO student VALUES (53888, ‘Drake’, ‘[email protected]’, 29, 3.5) A.

Both queries will not be able to insert the record successfully Solution: A Both queries will successfully insert a row in table student.

The Query 1 is useful when you want to Provide target table, columns, and values for new tuples and Query 2 is a Short-hand version of insert command

Q10) Consider the following queries: Query1: select name from enrolled LEFT OUTER JOIN student on student.sid = enrolled.sid;

Query 2 will produce an error and Query 1 will run successfully Solution: A In (LEFT, RIGHT or FULL) OUTER joins, order matters.

But both query will give the same results because both are dependent on records present in table and which column in selected.

None of these Solution: C In a relational schema, there exist only one primary key and it can’t take null values.

Primary key can take null values but unique key cannot null values D.

In relational schema, you can have only one primary key and there may be multiple unique key present in table.

None of these Solution: B TRUNCATE is faster than delete bcoz truncate is a ddl command so it does not produce any rollback information and the storage space is released while the delete command is a dml command and it produces rollback information too and space is not deallocated using delete command.

None of these Solution: A Each column must possess behavioral attributes like data types and precision in order to build the structure of the table.

Whereas B is the example of foreign key because all values present in this column are already present in column A.

Q23) What are the tuples additionally deleted to preserve reference integrity when the rows (2,4) are deleted from the below table.

Since C is a foreign key referring A with delete on cascade, all entries with value 2 in C must be deleted.

As a result of this 5 and 7 are deleted from A which causes (9, 5) to be deleted.

Query 1 will give last 4 rows as output (excluding null value) B.

Query 2 will give first row as output (only record containing null value) C.

2 and 4 Solution: B If a relation is satisfying higher normal forms, it automatically satisfies lower normal forms also.

Q29) Consider a relation R with the schema R (A, B, C, D, E, F) with a set of functional dependencies F as follows: {AB->C, BC->AD, D->E, CF->B} Which of the following will be the output of DA+?

You will get the following intermediate table after apply natural join

Query 1: Select name from AV1 where name like '%a%' Ans: B Solution: The query will search for records in column ‘Name’

Note: The above operation contains 6 underscores (‘_’) used with LIKE operator.

It will return names where number of characters in names are greater than or equals to 6 B.

Query 1 output = 1400 and Query 2 output =1400 Solution: A Both queries will generate the second-highest salary in AV1 which is 1200.

Students(rollno: integer, sname: string) Courses (courseno: integer, cname: string) Registration (rollno: integer, courseno: integer, percent: real) Now, which of the following query would be able to find the unique names of all students having score more than 90% in the courseno 107?

None of these Solution: A Option A is true, Option B will give the error (“UNIQUE” is not used in SQL) and in option C unique names will not be the output.

Suppose there are numbers between 1 and 100 and you want to search the number 35 using Binary Search Tree algorithm.

79, 14, 72, 56, 16, 53, 55 Solution: C In BST on right side of parent number should be greater than it, but in C after 47, 43 appears that is wrong.

None of these Solution: B The addition of the index made the query execution faster since the sequential scan is replaced by the index scan.

Now, you run Query 1 as given below and get the following output: Query 1: EXPLAIN select * from train where Product_ID = 'P00370853';

rows) You have now created Product_ID column as an index in train table using the below SQL query: CREATE INDEX product_ID ON train(Product_ID) And, you run Query 2 (same as Query 1) on “train” and get the following output.

Can’t say Solution: B For Query Plan for Query 1 execution time is 79723.88 and for Query Plan of Query 2 execution time is  40738.85.

Then, you created product_ID columns as an index in ‘train’ table using below SQL query: CREATE INDEX product_ID ON train(Product_ID) Suppose, you run Query 2 (same as Query 1) on train table.

Can’t say Solution: C The addition of the index didn’t change the query execution plan since the index doesn’t help for the ‘LIKE’

Can’t say Solution: C The addition of the index didn’t change the query execution plan.  The index on rating will not work for the query (Salary * 100 >

Query:  select c1, c2, c3 from ( select id,  lag(word) over (order by id) as c1, word as c2, lead(word) over (order by id) as c3 from words ) as t where c2 = ‘Mining’

using below SQL query: Query : CREATE TABLE avian ( emp_id SERIAL PRIMARY KEY, name varchar);

We tried to clear all your doubts through this article but if we have missed out on something then let me know in comments below.

If you have any suggestions or improvements you think we should make in the next skilltest, let us know by dropping your feedback in the comments section.

Complete guide to the top 16 data science bootcamps

For at least five years, analyst firms and other experts have warned of a coming shortage of data science practitioners: McKinsey Global Institute said in 2011 there would be a shortage of between 140,000 and 190,000 people with 'deep analytic skills' and another 1.5 million managers and analysts.

Gaining practical data science knowledgedoesn't require a complicated degree path because, as has happened with programming, there has been a spike in the growth of boot camps for data science.

No data analysis makes sense if you don't understand the basics of the business, including key value drivers, strategic goals, and the connection between them and data analysis.

And then there is learning how to communicate the results to managers and executives, balancing between so much data that you lose people and so little that they don't understand the most subtle issues.

We contacted dozens of data science boot camps, of which 12 responded with answers to the following questions: The answers collected from these emails have been combined to make an excellent resource for anyone exploring data science bootcamps.

You may find that if two providers seem equivalent in terms of raw information, one may ultimately be a better fit once you have a chance to talk with a representative.

Here is the data for each bootcamp in alphabetical order: Visit website Visit website Visit website Visit website Visit website Visit website Visit website Visit website Visit website Visit website Visit website View website Visit website Visit website Visit website Visit website Have you tried any of these bootcamps before?

2018 Best Data Science Bootcamps

Our recommendations are based on thousands of alumni reviews and data points such as price, location, job support, and instructor quality.

Here is a list of date science programs who have also made it onto our shortlist, but do not currently have a lot of data science related alumni reviews.

Data science bootcamps are immersive training programs that help students (usually with technical backgrounds) to transition into data-oriented careers.

However, due to the huge variety of data-related jobs and the specific skillsets needed for different positions, navigating through the complex career transition is challenging.

Market Growth: By 2018, data science jobs in the U.S. will exceed 490,000, with fewer than 200,000 available data scientists to fill these positions (McKinsey &

If you are comparing tech careers, you’ve probably heard some of the hype surrounding Data Science jobs.

Sure, the hype might sound like an exaggeration, but there’s no question that data science job growth isn’t slowing down anytime soon.

For example, you could be working for a B2C company that is looking to better understand their customer base, or you might be working for a company that offers data as the product.

Once you’ve learned the basics, a Data Science bootcamp can help you fill any gaps in your knowledge and get you ready for an entry-level data science job.

Once you get more experience as a data analyst, you can take more advanced courses, earn a master’s degree or consider a data-science bootcamp to jump into a more research-based, analytical role.

Things like bar charts, pie charts, trend lines, simple regression analysis, box plots, etc., will be common day-to-day tasks.

Medium Data Analyst Salary (entry level): $56,164 The data scientist uses a range of tools to take a project from start to finish.

Skills and tools: While a data analyst simply may be doing work in excel to present summary statistics of small datasets, a data scientist will be managing larger data sets from different sources.

As new data comes in and new problems come up, these data scientists are employed to find ways to optimize a company’s marketing campaign, optimize a hedge fund’s trading algorithm, or come up with new ways to predict or model consumer behavior.

Data engineers essentially lay the groundwork for a data analyst or data scientist to easily retrieve the needed data for their evaluations and experiments.They focus on creating robust data systems that can aggregate, process, clean, transform, and store large amounts of data.

Instead of data analysis, data engineers are responsible for compiling and installing database systems, writing complex queries, scaling to multiple machines, and putting disaster recovery systems into place.

You will need the ability to learn whatever technology the company is using to manage their data systems, and there are a wide variety of them, although the core underlying principles are very similar.

The primary job responsibility includes building robust, fault-tolerant data pipelines that clean, transform, and aggregate unorganized and messy data into databases or data sources.

The McKinsey Global Institute has predicted that by 2018 the U.S. could face a shortage of between 140,000 to 190,000 people with deep analytical skills, and a shortage of 1.5 million managers and analysts who know how to leverage data analysis to make effective decisions.

According to PayScale, national salary ranges for the following data job are as follows: Entry level: $40,405 - $77,615.

19 big data certifications that will pay off

Data and big data analytics are fast becoming the lifeblood of any successful business.

Not surprisingly, that challenge is reflected in the rising demand for big data skills and certifications.  If you're looking for a way to get an edge, big data certification is a great option.

They also need big data systems architects to translate requirements into systems, data engineers to build data pipelines, developers who know their way around Hadoop clusters and other technologies, and systems administrators and managers to tie everything together.

IDC is predicting a 30 percent CAGR over the next five years, while McKinsey is expecting IoT to have a $4 trillion to $11 trillion global economic impact by 2025 as businesses look to IoT technologies to provide more insight.'

While the market value of noncertified advanced analytics skills has actually increased faster as a percentage of base salary than the value of certified big data skills, according to Foote Research, Foote believes pay premiums for both noncertified and certified skills will steadily rise over the next 12 to 24 months.

The Analytics: Optimizing Big Data Certificate is an undergraduate-level program intended for business, marketing and operations managers, data analyst and professionals, financial industry professionals, and small business owners.

It introduces students to the tools needed to analyze large datasets, covering topics including importing data into an analytics software package, exploratory graphical and data analysis, building analytics models, finding the best model to explore correlation among variables and more.

Offered in Hyderabad and Bengaluru, India, the Certificate in Engineering Excellence Big Data Analytics and Optimization is an intensive 18-week program that consists of 10 courses (lectures and labs) for students of all aspects of analytics, including working with big data using Hadoop.

The Certified Analytics Professional (CAP) credential is a general analytics certification that certifies end-to-end understanding of the analytics process, from framing business and analytic problems to acquiring data, methodology, model building, deployment and model lifecycle management.

The CCA Administrator credential certifies an individual has demonstrated the core systems and cluster administrator skills required by organizations deploying Cloudera in the enterprise, including: The credential requires passing the remote-proctored CCA Administrator Exam (CCA131), which consists of eight to 12 performance-based, hands-on tasks on a pre-configured Cloudera Enterprise cluster.

SQL developer who earns the CCA Data Analyst certification demonstrates core analyst skills to load, transform and model Hadoop data to define relationships and extract meaningful results from the raw output.

It requires passing the remote-proctored CCP: Data Engineer Exam (DE575), a hands-on, practical exam in which each user is given five to eight customer problems each with a unique, large data set, a CDH cluster and four hours.

It includes deploying the data analytics lifecycle, reframing a business challenge as an analytics challenge, applying analytic techniques and tools to analyze big data and create statistical models, selecting the appropriate data visualizations and more.

The IBM Certified Data Engineer – Big Data certification is intended for big data engineers, who work directly with data architects and hands-on developers to convert an architect's big data vision into reality.

The MCSE: Data Management and Analytics credential demonstrates broad skill sets in SQL administration, building enterprise-scale data solutions, and leveraging business intelligence (BI) data in both on-premises and cloud environments.

Designed for software engineers, statisticians, predictive modelers, market researchers, analytics professionals, and data miners, the Mining Massive Data Sets Graduate Certificate requires four courses and demonstrates mastery of efficient, powerful techniques and algorithms for extracting information from large datasets like the Web, social network graphs and large document repositories.

It covers installing Oracle Business Intelligence Enterprise Edition (OBIEE), building the BI Server metadata repository, building BI dashboards, constructing ad hoc queries, defining security settings, and configuring and managing cache files.

Organization: SAS Academy for Data Science Price: $9,000 for classroom (Cary, NC), $4,725 for blended learning (combination of 24/7 online access and instructor-led training) How to prepare: At least six months of programming experience in SAS or another programming language is required to enroll.

The SAS Certified Data Scientist Using SAS 9 credential demonstrates that individuals can manipulate and gain insights from big data with a variety of SAS and open source tools, make business recommendations with complex learning models, and then deploy models at scale using the SAS environment.

The Data Mining and Applications Graduate Certificate certifies the ability to: Geared at strategy managers, scientific researchers, social sciences researchers, data analysts and consultants, and advertising and marketing executives, the certificate requires candidates complete three courses, starting with either Data Mining and Analysis or Introduction to Statistical Learning.

Organization: Stanford Center for Professional Development Price: $11,340 - $12,600 (9-10 units) How to prepare: To pursue the graduate certificate, candidates must have taken introductory courses in statistics or probability, linear algebra, and computer programming.

Yelawolf - Daddy's Lambo

Sign up for updates: Music video by Yelawolf performing Daddy's Lambo. (C) 2011 DGC Records Best of Yelawolf: ..

Bebe Rexha - I Can't Stop Drinking About You [Official Music Video]

Check out the official music video for Bebe Rexha's "I Can't Stop Drinking About You"! Bebe Rexha's "I Don't Wanna Grow Up" EP is available now on iTunes!

Yelawolf - Punk ft. Travis Barker, Juicy J

Yelawolf “PUNK” feat. Juicy J & Travis Barker is Out Now! Follow Yelawolf: .

Kendrick Lamar - Ignorance Is Bliss

Kendrick Lamar O.D 9/15/10 Written by Kendrick Lamar Dir by dee.jay.dave & O.G Michael Mihail.

Balmak Institucional

Vídeo institucional da empresa Balmak Balanças, que em 2013 comemora 20 anos.