TRUNCATE vs DELETE in SQL: Need to delete all rows from a large table and speed is important? Use TRUNCATE TABLE. Need to delete specific rows based on a condition? Use DELETE TABLE. Need to be able to roll back the deletion: Use DELETE TABLE.

In every interview I've had for data related roles, there has been at least one SQL question. If you can't handle them well, it's an instant rejection. Here are 3 case study-style SQL interview questions and the answers I would give:

Basic commands for SQL beginners:

Keys in SQL explained in simple terms: Primary Key: It's a unique identifier that helps SQL distinguish one row from another.  Think of it as a customer ID in a business.  Foreign Key: It helps establish relationships between tables by pointing to the primary key of another table.  Think of it as a reference or a link. Unique Key: Similar to a primary key, but it doesn't have to be the main identifier for a table.  It's a column (or columns) that contains unique values, like a primary key. However, a table can have multiple unique keys while it can only have one primary key.

How much Excel, SQL and PowerBI did I actually use as a data analyst? (Honest take):

5 types of data analysis that cover 99% of business needs:  Descriptive: Summarises historical data. Diagnostic: Identify root causes. Predictive: Forecast future outcomes. Prescriptive: Recommend actions. Exploratory: Uncovers hidden insights.

One of the hardest parts of learning SQL is sitting through hours of material. Let's be honest... It can be pretty boring. Want to learn at a rapid pace whilst having fun? Here are 3 SQL games to help you escape classroom learning:

If you want to learn Python for Data Analysis: Don't try and learn everything it on offer. Instead, focus on: Pandas (cleaning, transforming, and analysing) NumPy (for math) Matplotlib (for data visualisation) That'll get you up and running.

Data cleaning is one of the most important skills for a data analyst. Not Excel. Not SQL. Not PowerBI Without clean data, any analysis done is unreliable. Here's my data cleaning 101:

10 Python libraries every data analyst should know: ➡️ Matplotlib ➡️ Seaborn ➡️ Plotly ➡️ Requests ➡️ BeautifulSoup ➡️ PyODBC ➡️ Numpy ➡️ Pandas ➡️ OS ➡️ Selenium What would you add to this list?:

A lot of data work doesn't involve data.  Don't neglect: - Critical thinking - Emotional intelligence - How to work with others AKA the soft skills. Being able to knit soft skills and technical skills together is the secret sauce of a successful data career.

Data Analysis and Data Science are not the same thing. It's ok to be a Data Analyst and not a Data Scientist. It's ok to be a Data Scientist and not a Data Analyst Both are equally important.

When I'm hiring a data analyst, here's what SQL I'd expect candidates with 1-2 years of experience to know:

Here's the fastest way to use Python if you already know SQL:

Don't build dashboards so you can answer stakeholders questions. Build dashboards so they can do it themselves.

When preparing to deliver data analysis, you should be able to explain it to anyone, and they should grasp the reason for the work, approach, and action immediately.  If they don't, it's too complicated. Try again.

After 8 years working in data, here are the 5 biggest lessons I learnt the hard way. (so you don't have to): 🧵

Everyone talks about how to get a data analyst job. Very few tell you how to do well when get there. Based on my 8 years experience, here are 4 things you'll be judged on:

YouTube is not the best way to learn data analysis Books are not the best way to learn data analysis Online courses are not the best way to learn data analysis The best way to learn data analysis depends on you Understand how you learn best and find resources that suit

Data analyst starter kit: - Become an expert at SQL and data wrangling. - Learn to help others understand data through visualisations. - Seek to answer specific questions and provide clarity. - Remember, everything ends up in Excel.