DATA ANALYSIS MADE EASY

If you registered for our cohort that will be starting tomorrow, check you email for the link to join the class. If you are yet to register register now: https://paystack.com/pay/DataAnalysisMadeEasyDiscountLink I will send the link to you immediately after you've registered.

EXCEL A-Z for every professionals. Hands-on project at the end of the classes. Starts this Saturday for 4 Saturdays. Register NOW with this special link with discount code: https://paystack.com/pay/DataAnalysisMadeEasyDiscountLink

Power BI Desktop: https://www.microsoft.com/en-us/download/details.aspx?id=58494 SSMS: https://learn.microsoft.com/en-us/sql/ssms/download-sql-server-management-studio-ssms?view=sql-server-ver16 SSMS Server: https://www.microsoft.com/en-US/Download/confirmation.aspx?id=14630 Anaconda: https://www.anaconda.com/download-success

4 weeks intensive EXCEL training with hands on projects after the classes. Register here today with this discount link: https://paystack.com/pay/DataAnalysisMadeEasyDiscountLink

We are starting our DATA ANALYSIS MADE EASY classes in July Registration link will be posted soon, Hope you’re excited?✨

Your experiences are what make you unique and special: Every experience, whether good or bad, has played a significant role in shaping who you are today. Instead of dwelling on the past and feeling defeated, you should focus on the lessons that you have learned and the positive changes that have resulted from those challenges. Remember, Life is not always easy, but every struggle that you have overcome makes you stronger and more capable of overcoming future obstacles.

5 Websites to get Data Sets for your Data Science Projects. 1. KAGGLE: https://www.kaggle.com/datasets 2. United Kingdom Gov Datasets https://data.gov.uk 3. Awesome Github Datasets: https://github.com/awesomedata/awesome-public-datasets 4.Paper With Code Datasets: https://paperswithcode.com/datasets 5. Data World: https://data.world/datasets/images

10 MOST USED FUNCTIONS IN SQL 1. SELECT: The SELECT statement is the fundamental function in SQL and is used to retrieve data from one or more tables in the database. It allows you to specify the columns you want to retrieve and apply filtering and sorting conditions. 2. COUNT: The COUNT function is used to calculate the number of rows that match a specified condition. It is often used in combination with the GROUP BY clause to perform aggregate calculations. 3. SUM: The SUM function is used to calculate the sum of values in a numeric column. It is frequently used to calculate totals or subtotals in a result set. 4. AVG: The AVG function calculates the average value of a numeric column. It is useful for calculating average scores, ratings, or other types of aggregated averages. 5. MAX and MIN: The MAX and MIN functions are used to find the maximum and minimum values in a column, respectively. They are commonly used to retrieve the highest and lowest values or to identify outliers. 6. GROUP BY: The GROUP BY clause is used in conjunction with aggregate functions to group rows based on one or more columns. It is used to perform calculations on groups of data rather than on individual rows. 7. JOIN: The JOIN operation is used to combine rows from two or more tables based on a related column between them. It is essential for retrieving data from multiple tables simultaneously. 8. WHERE: The WHERE clause is used to filter rows based on specified conditions. It allows you to retrieve only the rows that meet the specified criteria. 9. ORDER BY: The ORDER BY clause is used to sort the result set based on one or more columns. It allows you to specify the desired sorting order, such as ascending or descending. 10. DISTINCT: The DISTINCT keyword is used to eliminate duplicate values from a result set. It ensures that only unique values are returned. If you are yet to get my new book with this special discount link: https://selar.co/TechiesGuideDISCOUNT Do so now, The link will soon become invalid.

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Dear Data Analyst!!! The world needs data analysts who possess not only technical skills but also a resilient spirit. It is the passion and determination that you bring to the table that will set you apart. Embrace the challenges with open arms, for they are the catalysts that will fuel your growth and development. Every obstacle you overcome will make you stronger, more adept, and better equipped to face the next one that comes your way. Remember, success is not a destination; it is a journey. Along this path, always strive for continuous learning and improvement. Stay curious and remain hungry for knowledge. The field of data analysis is constantly evolving, and it demands that we stay at the forefront of emerging technologies, methodologies, and best practices. Embrace new tools, explore different techniques, and never settle for mediocrity. Your commitment to growth will ensure that you are always ahead of the curve.

Share with us your learning progress so far. Challenges and/or what you are enjoying about DATA ANALYSIS MADE EASY. You can also post about it on Twitter and make sure you tag me @ezekiel_aleke so I can help you retweet it.

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Websites to practice SQL for FREE. 1. SQLITE - https://sqliteonline.com/ 2. Hackerrank - https://t.co/TMLNUb9T9Y 3. w3school - https://t.co/jKUsRP64kL 4. LeetCode - https://t.co/3OUvZhMdWU 5. DataLemur - https://t.co/kjKNsh6ZGJ 6. StrataScratch - https://t.co/tXMAAoMYhx 7. SQL-Practice - https://t.co/9TpvxJFHf4

10 INTERVIEW TIPS🔥 1. Don’t fear rejection, be bold. 2. Nail the resume. 3. Nail the cover letter. 4. Do your research. 5. Take a notebook with you for an interview. 6. Prepare for tell me about yourself. 7. Embrace “I don’t know”. 8. Learning is a goal. 9. Show your passion. 10 Ask questions.

DIFFERENCES between Data Mart, Database, Data Warehouse and Dataset Data Mart: A data mart is a subset of a data warehouse that is focused on a specific functional area or department within an organization. It contains a curated collection of data that is designed to support the specific needs of a particular group of users, such as marketing, sales, or finance. Database: A database is a structured collection of data that is organized and stored in a systematic way to facilitate efficient data management and retrieval. It is designed to store, manage, and manipulate data using predefined schemas and database management systems (DBMS). Data Warehouse: A data warehouse is a centralized repository that stores large amounts of structured and historical data from various sources within an organization. It is specifically designed for supporting business intelligence (BI) activities, such as reporting, analysis, and data mining. Dataset: A dataset is a structured collection of data that represents a specific set of information. It can consist of various types of data, such as text, numbers, images, or videos, organized in a tabular or hierarchical format. A dataset can be as simple as a single spreadsheet or as complex as a collection of interconnected tables within a database. Datasets are commonly used in data analysis, machine learning, and other data-driven applications for training models, conducting research, and extracting insights. Differences: Scope: A data warehouse is a comprehensive and centralized repository that stores data from multiple sources, while a data mart is a subset of a data warehouse focused on specific functional areas or departments. Purpose: Data warehouses are designed to support business intelligence activities and provide a unified view of data across an organization. Data marts, on the other hand, are built to cater to the specific needs of a particular business unit or department. Size and Complexity: Data warehouses are typically larger and more complex than data marts since they consolidate data from multiple sources and require extensive integration and transformation processes. Data marts are smaller in scale and can be built more quickly to address specific requirements. Data Structure: Data warehouses often use a dimensional or star-schema model to enable efficient querying across multiple dimensions. Data marts can adopt various structures depending on the specific needs of the business unit they serve. Data Source: Data warehouses integrate data from multiple operational systems and external sources. Data marts are usually created by extracting and transforming data from a data warehouse or other sources to serve the needs of a specific department. User Focus: Data warehouses serve the analytical needs of a wide range of users across an organization, including executives, managers, and analysts. Data marts are designed to cater to the specific analytical requirements of a particular business unit or user group. Accessibility: Data warehouses provide a centralized and unified view of data, whereas data marts offer a more focused and department-specific view. This often leads to easier and faster data access in data marts for targeted analysis and reporting.

This is how you use IF function in Excel👌

Kindly share with us what you’re learning this weekend😁

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PROPER, UPPER, and LOWER functions in EXCEL🔥 1. PROPER Function: The PROPER function converts the first letter of each word in a text string to uppercase and converts the remaining letters to lowercase. It's commonly used to format names, addresses, or any other text where proper capitalization is required. Example: Suppose cell A1 contains the text "hello world." To apply the PROPER function, you can use the following formula in another cell: =PROPER(A1) The result will be "Hello World." 2. UPPER Function: The UPPER function converts all letters in a text string to uppercase. It's useful when you want to convert an entire text string to uppercase, regardless of the original case. Example: Let's assume cell A1 contains the text "hello world." To convert it to uppercase using the UPPER function, you can use the following formula in another cell: =UPPER(A1) The result will be "HELLO WORLD." 3. LOWER Function: The LOWER function converts all letters in a text string to lowercase. It's useful when you want to convert an entire text string to lowercase, regardless of the original case. Example: Consider cell A1 with the text "Hello World." To convert it to lowercase using the LOWER function, you can use the following formula in another cell: =LOWER(A1) The result will be "hello world."

Split text to multiple columns with this shortcut🔥