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SQL : Learn SQL for data analysis

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SQL : Learn SQL for data analysis

Step by Step SQL with MySQL Database for Beginners, Non-Techs, newbs - Quick way to learn SQL using MySQL Database

  • No Rating
  • (0 Reviews)
  • 0 students enrolled
  • ₹ 2000.00
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Prashant Bhise
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What learn

  • Be comfortable putting SQL on their resume
  • Use SQL to perform data analysis
  • Be confident while working with constraints and relating data tables
  • Tons of exercises that will solidify your knowledge

Requirements

  • You needn't bother with long stretches of talks to learn SQL and MySQL, that is actually how I moved toward this course.

Description

This is a novice level course. On the off chance that you have earlier information on SQL than this course may fill in as boost yet won't show you many propelled ideas. Why you ought to gain from me? I have been in Digital Marketing and Analytics for more than 15 years. I have prepared individuals from various foundations and have changed over them into high performing Digital Marketers and Analysts. I comprehend both the innovation and promoting side of business. I have managed numerous investigation advancements path before Google Tag chief existed and know the inward working of Digital Analytics. Likewise, I have created different course and showed understudies from everywhere throughout the world. 

Course Content

6 sections • 18 lectures •
Data definition language (DDL) commands
Data Definition Language (DDL) commands are a set of SQL statements used to define, modify, and manage the structure of database objects. These commands enable users to create, alter, and drop database objects such as tables, indexes, views, and constraints.
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Data Manipulation language (DDL) commands
Data Manipulation Language (DML) commands are used to interact with and manipulate data within a database. These commands facilitate operations such as inserting, updating, deleting, and querying data stored in tables. Among the essential DML commands is the INSERT statement, which adds new records into a table.
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Data Query language (DQL) commands
Data Query Language (DQL) commands in SQL are designed for retrieving and manipulating data stored in relational databases. Among DQL commands, the SELECT statement stands out as a powerful tool for fetching specific data from tables based on defined criteria.
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Data Control language (DCL) commands
Data Control Language (DCL) commands in SQL are crucial for managing access control and permissions within a database system. These commands, such as GRANT and REVOKE, enable database administrators to grant or revoke privileges to users or roles, controlling their ability to perform various actions on database objects.
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Transaction Control language (TCL) commands
Transaction Control Language (TCL) commands are vital for managing transactions within a database system. These commands enable users to control the flow and integrity of transactions, ensuring that changes to the database are made reliably and consistently.
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Joining Tables
Joining tables is the process of combining rows from two or more tables based on a related column between them. This enables users to retrieve data that spans across multiple tables, creating meaningful connections between different datasets.
mb
Window Functions
Window functions are advanced SQL features that enable performing calculations across a set of rows related to the current row within a query result, without altering the result set. These functions provide a flexible and powerful way to analyse and manipulate data within partitions defined by specific criteria.
mb
Understanding E-commerce Business Processes
E-commerce business processes encompass a wide range of activities involved in conducting online retail operations. Business processes is essential for identifying relevant data sources and defining key performance indicators (KPIs) for e-commerce data analysis.
mb
Common Data Models and Schemas in E-commerce
E-commerce data analysis relies on structured data models and schemas to organize and store data effectively.
mb
Customer analysis
Customer analysis is a crucial aspect of managing an online retail store, as it helps understand customer behaviour, preferences, and purchasing patterns. By analysing customer data, such as demographics, purchase history, and browsing behaviour, businesses can make informed decisions to improve marketing strategies, optimize product offerings, and enhance customer experience.
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Product analysis
Product analysis is crucial for an online retail store to understand the performance of various products in its inventory. It involves analysing sales data, customer preferences, trends, and other factors to make informed decisions about product management, marketing strategies, and inventory optimization.
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Order analysis
Order analysis is crucial for an online retail store to understand various aspects of customer purchasing behaviour, product popularity, and sales performance. By analysing orders, the store can gain insights into which products are selling well, identify trends over time, and make informed decisions about inventory management, marketing strategies, and product recommendations.
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Sales analysis
Sales analysis is a critical aspect of managing an online retail store, as it provides valuable insights into the performance of products, customers, and sales channels. By analyzing sales data, retailers can identify trends, evaluate the effectiveness of marketing campaigns, optimize inventory management, and make informed business decisions to drive growth and profitability.
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Marketing and campaigning
Marketing and campaigning are vital aspects of running an online retail store, focusing on promoting products, engaging customers, and driving sales. Utilizing SQL queries, retailers can analyse customer data, track campaign performance, and target specific customer segments to optimize marketing strategies.
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Logistics and supply chain
Logistics and supply chain management are critical components of an online retail store's operations. Efficient management of logistics ensures timely delivery of products to customers while minimizing costs and maximizing customer satisfaction. Using SQL queries, businesses can track inventory, monitor shipment statuses, and optimize logistics processes to streamline the supply chain.
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Key Performance Indicators (KPIs) for E-commerce
Key performance indicators (KPIs) for e-commerce encompass a diverse range of metrics that evaluate different facets of online retail operations. These metrics provide valuable insights into various aspects such as website performance, customer behaviour, sales effectiveness, marketing ROI, inventory management, and fulfilment efficiency.
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Importance of Key Performance Indicators (KPIs) in E-commerce
.KPIs serve as vital tools for e-commerce businesses to monitor their performance, measure success against predefined objectives, and drive continuous improvement. By focusing on relevant KPIs, businesses can gain actionable insights into their operations, customer behaviours, and market trends, enabling them to make data-driven decisions and adapt strategies in real-time.
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Common KPIs in E-commerce
In the realm of online retail, various metrics play a crucial role in assessing the performance and success of the business. From understanding customer behaviour to evaluating financial performance, these metrics provide valuable insights that can guide strategic decision-making. Among the key metrics are Conversion Rate, Average Order Value (AOV), Customer Acquisition Cost (CAC), Customer Lifetime Value (CLV), Cart Abandonment Rate, Website Traffic and Visitor Behaviour, Return on Investment (ROI), Inventory Turnover Rate, Customer Retention Rate, and Fulfilment and Shipping Metrics. Let's delve into each of these metrics with examples tailored to an online retail store.
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About Instructor

instructor
Prashant Bhise
About Instructor

I am an experienced Data Analytics and Data Science professional with over 8 years in the industry. As an educator, I specializes in creating practical, hands-on courses designed to equip students with real-world skills. My courses include best practice sessions, ensuring that learners not only understand theoretical concepts but also know how to apply them effectively in their careers. Through his expert guidance and well-structured curriculum, My aims to provide an engaging and efficient learning experience, helping students master the intricacies of Data Analysis, Data Science, Machine Learning and Artifical Intelligence.

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Step by Step SQL with MySQL Database for Beginners, Non-Techs, newbs - Quick way to learn SQL using MySQL Database

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