DATA VISUALIZATION AND DATA ANALYTICS USING JDBC AND SQLITE WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE PDF Download
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Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 523
Book Description
In this project, we developed data visualization and data analytics with step by step implementation of JDBC/SQLITE using object-oriented approach. We uses the SQLite version of BikeStores database as a sample database to help you work with SQLite quickly and effectively. You can download the sample database from https://viviansiahaan.blogspot.com/2023/03/my-book-data-visualization-and-data.html. In this project, we plotted: the bar chart that displays the distribution of products by category; the pie chart that displays the distribution of products by brand; the distribution of stores by city; the distribution of stores by state; the top 10 stock distributions by category name; the top 10 stock distributions by brand name; the top 10 stock distributions by store name; the top 10 stock distributions by city; the customer distribution by state; the customer distribution by city; the bar chart distribution of staff by state; the bar chart distribution of staff by city; the bar chart that shows the distribution of orders based on the store name; the pie chart that shows the distribution of orders based on the customer name; the pie chart showing the order distribution by store city; the pie chart showing the order distribution by store state; the pie chart showing the order distribution by customer city; the pie chart showing the order distribution by customer state; the pie chart sales distribution by staff name; the pie chart sales distribution by brand name; the pie chart sales distribution by customer city; the pie chart sales distribution by customer state; the pie chart sales distribution by store city; the pie chart sales distribution by store state; the pie chart sales distribution by product name; the pie chart sales distribution by category name; pie chart sales distribution by customer name; and the pie chart sales distribution by store name. The stores table includes the store’s information. Each store has a store name, contact information such as phone and email, and an address including street, city, state, and zip code. The staffs table stores the essential information of staffs including first name, last name. It also contains the communication information such as email and phone. A staff works at a store specified by the value in the store_id column. A store can have one or more staffs. A staff reports to a store manager specified by the value in the manager_id column. If the value in the manager_id is null, then the staff is the top manager. If a staff no longer works for any stores, the value in the active column is set to zero. The categories table stores the bike’s categories such as children bicycles, comfort bicycles, and electric bikes. The products table stores the product’s information such as name, brand, category, model year, and list price. Each product belongs to a brand specified by the brand_id column. Hence, a brand may have zero or many products. Each product also belongs a category specified by the category_id column. Also, each category may have zero or many products. The customers table stores customer’s information including first name, last name, phone, email, street, city, state, zip code, and photo path. The orders table stores the sales order’s header information including customer, order status, order date, required date, shipped date. It also stores the information on where the sales transaction was created (store) and who created it (staff). Each sales order has a row in the sales_orders table. A sales order has one or many line items stored in the order_items table. The order_items table stores the line items of a sales order. Each line item belongs to a sales order specified by the order_id column. A sales order line item includes product, order quantity, list price, and discount. The stocks table stores the inventory information i.e. the quantity of a particular product in a specific store.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 523
Book Description
In this project, we developed data visualization and data analytics with step by step implementation of JDBC/SQLITE using object-oriented approach. We uses the SQLite version of BikeStores database as a sample database to help you work with SQLite quickly and effectively. You can download the sample database from https://viviansiahaan.blogspot.com/2023/03/my-book-data-visualization-and-data.html. In this project, we plotted: the bar chart that displays the distribution of products by category; the pie chart that displays the distribution of products by brand; the distribution of stores by city; the distribution of stores by state; the top 10 stock distributions by category name; the top 10 stock distributions by brand name; the top 10 stock distributions by store name; the top 10 stock distributions by city; the customer distribution by state; the customer distribution by city; the bar chart distribution of staff by state; the bar chart distribution of staff by city; the bar chart that shows the distribution of orders based on the store name; the pie chart that shows the distribution of orders based on the customer name; the pie chart showing the order distribution by store city; the pie chart showing the order distribution by store state; the pie chart showing the order distribution by customer city; the pie chart showing the order distribution by customer state; the pie chart sales distribution by staff name; the pie chart sales distribution by brand name; the pie chart sales distribution by customer city; the pie chart sales distribution by customer state; the pie chart sales distribution by store city; the pie chart sales distribution by store state; the pie chart sales distribution by product name; the pie chart sales distribution by category name; pie chart sales distribution by customer name; and the pie chart sales distribution by store name. The stores table includes the store’s information. Each store has a store name, contact information such as phone and email, and an address including street, city, state, and zip code. The staffs table stores the essential information of staffs including first name, last name. It also contains the communication information such as email and phone. A staff works at a store specified by the value in the store_id column. A store can have one or more staffs. A staff reports to a store manager specified by the value in the manager_id column. If the value in the manager_id is null, then the staff is the top manager. If a staff no longer works for any stores, the value in the active column is set to zero. The categories table stores the bike’s categories such as children bicycles, comfort bicycles, and electric bikes. The products table stores the product’s information such as name, brand, category, model year, and list price. Each product belongs to a brand specified by the brand_id column. Hence, a brand may have zero or many products. Each product also belongs a category specified by the category_id column. Also, each category may have zero or many products. The customers table stores customer’s information including first name, last name, phone, email, street, city, state, zip code, and photo path. The orders table stores the sales order’s header information including customer, order status, order date, required date, shipped date. It also stores the information on where the sales transaction was created (store) and who created it (staff). Each sales order has a row in the sales_orders table. A sales order has one or many line items stored in the order_items table. The order_items table stores the line items of a sales order. Each line item belongs to a sales order specified by the order_id column. A sales order line item includes product, order quantity, list price, and discount. The stocks table stores the inventory information i.e. the quantity of a particular product in a specific store.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 665
Book Description
In this project, you will use SQLite version of Northwind database which is a sample database that was originally created by Microsoft and used as the basis for their tutorials in a variety of database products for decades. The Northwind database contains the sales data for a fictitious company called “Northwind Traders,” which imports and exports specialty foods from around the world. The Northwind database is an excellent tutorial schema for a small-business ERP, with customers, orders, inventory, purchasing, suppliers, shipping, employees, and single-entry accounting. You can download the sample database from https://viviansiahaan.blogspot.com/2023/04/data-analysis-using-jdbc-and-sqlite.html. In this project, you will design the form for every table and you will plot: the territory distribution by region; the employee distributions based on city, country, title, and region; the employee distributions based on birth date, hire date, and employee name; the employee distributions based on city, country, territory, and region; the three supplier distributions based on city, region, and country; the product distributions based on city, region, country, categorized unit price, categorized units in stock, and categorized units on order; the customer distributions based on city, region, and country; the order and freight distributions based on year, month, and week; the order and freight distributions based on day, quarter, and ship country; the order and freight distributions based on ship region, ship city, and ship name; the order and freight distributions based on shipper company, customer company, and customer city; the order and freight distributions based on customer country, employee name, and employee title; the sales distributions based on year, month, week, day, quarter, and ship country; the sales distributions based on ship region, ship city, ship name, shipper company, customer company, and customer city; the sales distributions based on customer region, customer country, employee name, employee title, employee city, and employee country; the sales distributions based on product name, category name, supplier company, supplier city, supplier region, and supplier country.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 490
Book Description
In this project, you will develop step by step implementation of JDBC/SQLITE with object-oriented approach using SQLite version of an Oracle sample database named electronics. You will be taught how to plot country distribution in each region; location distribution in each country and region; warehouse distribution in each country, region, and city; product distribution by category name; categorized standard cost and categorized list price values distribution in products table; categorized values in inventories table; employee distribution by job title; customer distribution by categorized credit limit; order distribution by customer employee, status, and by categorized credit limit; the top 10 sales distribution by product name; the top 10 sales distribution by category name; the order distribution by category; and order distribution by status. The electronics database itself is based on a global fictitious company that sells computer hardware including storage, motherboard, RAM, video card, and CPU. You can download the sample database from https://viviansiahaan.blogspot.com/2023/03/book-jdbc-and-sqlite-with-object.html. In the database, the company maintains the product information such as name, description standard cost, list price, and product line. It also tracks the inventory information for all products including warehouses where products are available. Because the company operates globally, it has warehouses in various locations around the world. The company records all customer information including name, address, and website. Each customer has at least one contact person with detailed information including name, email, and phone. The company also places a credit limit on each customer to limit the amount that customer can owe. Whenever a customer issues a purchase order, a sales order is created in the database with the pending status. When the company ships the order, the order status becomes shipped. In case the customer cancels an order, the order status becomes canceled. In addition to the sales information, the employee data is recorded with some basic information such as name, email, phone, job title, manager, and hire date.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 851
Book Description
This book uses the Sakila sample database which is a fictitious database designed to represent a DVD rental store. The 15 tables of the database include film, film_category, actor, customer, rental, payment and inventory among others. The Sakila sample database is intended to provide a standard schema that can be used for examples in books, tutorials, articles, samples, and so forth. You can download the sample database from http://viviansiahaan.blogspot.com/2023/04/data-science-using-jdbc-and-mysql-with.html. In this project, you will design the form for every table and you will plot: top 10 film distribution by release year; top 10 film distribution by rating; top 10 film distribution by rental duration; top 10 film distribution by language; film distribution by categorized rental rate; film distribution by categorized length; film distribution by categorized replacement cost; top 10 film distribution by actor name; top 10 actor name distribution by average rental rate; top 10 actor name distribution by average replacement cost; film distribution by rating; rating distribution by average rental rate; rating distribution by average replacement cost; top 10 film distribution by category name, category distribution by average replacement cost; category distribution by average rental rate; category distribution by length; top 10 city distribution by by country; top 10 address distribution by district, top 10 address distribution by country; top 10 address distribution by city; top 10 address distribution by district; top 10 address distribution by country; top 10 address distribution by city; top 10 inventory distribution by release year; top 10 inventory distribution by film rating; top 10 inventory distribution by film language; top 10 inventory distribution by film rental duration; top 10 inventory distribution by city; top 10 inventory distribution by country; top 10 customer distribution by country; top 10 customer distribution by city; top 10 customer distribution by district; top 10 customer distribution by store country; top 10 customer distribution by store city; top 10 customer distribution by store district; top 10 staff distribution by country; top 10 staff distribution by city; rental distribution by year of rental date; rental distribution by month of rental date; 10 rental distribution by week of rental date; rental distribution by day of rental date; rental distribution by quarter of rental date; rental distribution by film release year; rental distribution by film duration; rental distribution by film rating; top 10 rental distribution by staff name; rental distribution by film language; top 10 rental distribution by film title; rental distribution by customer active; top 10 rental distribution by film category; top 10 rental distribution by actor name; top 10 rental distribution by customer name; top 10 rental distribution by customer city; top 10 rental distribution by customer country, top 10 rental distribution by customer district; payment distribution by year of payment date; payment distribution by month of payment date; top 10 payment distribution by week of payment date; payment distribution by day of payment date; payment distribution by quarter of payment date; payment distribution by film release year; payment distribution by film duration; payment distribution by film rating; top 10 payment distribution by staff name; payment distribution by film language; top 10 payment distribution by film title; payment distribution by customer active; top 10 payment distribution by film category; top 10 payment distribution by actor name; top 10 payment distribution by customer name; top 10 payment distribution by customer city; top 10 payment distribution by customer country; and top 10 payment distribution by customer district.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 1066
Book Description
This book is SQL SERVER version of our previous book titled “DATA SCIENCE USING JDBC AND MYSQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE”. This book uses the SQL SERVER version of Sakila sample database which is a fictitious database designed to represent a DVD rental store. The tables of the database include film, film_category, actor, customer, rental, payment and inventory among others. The Sakila sample database is intended to provide a standard schema that can be used for examples in books, tutorials, articles, samples, and so forth. You can download the sample database from https://viviansiahaan.blogspot.com/2023/05/data-science-using-jdbc-and-sql-server.html. In this project, you will design the form for every table and you will plot: top 10 film distribution by release year; top 10 film distribution by rating; top 10 film distribution by rental duration; top 10 film distribution by language; film distribution by categorized rental rate; film distribution by categorized length; film distribution by categorized replacement cost; top 10 film distribution by actor name; top 10 actor name distribution by average rental rate; top 10 actor name distribution by average replacement cost; film distribution by rating; rating distribution by average rental rate; rating distribution by average replacement cost; top 10 film distribution by category name, category distribution by average replacement cost; category distribution by average rental rate; category distribution by length; top 10 city distribution by by country; top 10 address distribution by district, top 10 address distribution by country; top 10 address distribution by city; top 10 address distribution by district; top 10 address distribution by country; top 10 address distribution by city; top 10 inventory distribution by release year; top 10 inventory distribution by film rating; top 10 inventory distribution by film language; top 10 inventory distribution by film rental duration; top 10 inventory distribution by city; top 10 inventory distribution by country; top 10 customer distribution by country; top 10 customer distribution by city; top 10 customer distribution by district; top 10 customer distribution by store country; top 10 customer distribution by store city; top 10 customer distribution by store district; top 10 staff distribution by country; top 10 staff distribution by city; rental distribution by year of rental date; rental distribution by month of rental date; 10 rental distribution by week of rental date; rental distribution by day of rental date; rental distribution by quarter of rental date; rental distribution by film release year; rental distribution by film duration; rental distribution by film rating; top 10 rental distribution by staff name; rental distribution by film language; top 10 rental distribution by film title; rental distribution by customer active; top 10 rental distribution by film category; top 10 rental distribution by actor name; top 10 rental distribution by customer name; top 10 rental distribution by customer city; top 10 rental distribution by customer country, top 10 rental distribution by customer district; payment distribution by year of payment date; payment distribution by month of payment date; top 10 payment distribution by week of payment date; payment distribution by day of payment date; payment distribution by quarter of payment date; payment distribution by film release year; payment distribution by film duration; payment distribution by film rating; top 10 payment distribution by staff name; payment distribution by film language; top 10 payment distribution by film title; payment distribution by customer active; top 10 payment distribution by film category; top 10 payment distribution by actor name; top 10 payment distribution by customer name; top 10 payment distribution by customer city; top 10 payment distribution by customer country; and top 10 payment distribution by customer district.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 680
Book Description
In this project, you will use Northwind MySQL database which is a sample database that was originally created by Microsoft and used as the basis for their tutorials in a variety of database products for decades. The Northwind database contains the sales data for a fictitious company called “Northwind Traders,” which imports and exports specialty foods from around the world. The Northwind database is an excellent tutorial schema for a small-business ERP, with customers, orders, inventory, purchasing, suppliers, shipping, employees, and single-entry accounting. You can download the sample database from https://viviansiahaan.blogspot.com/2023/04/data-analysis-using-jdbc-and-mysql-with.html. In this project, you will design the form for every table and you will plot: the territory distribution by region; the employee distributions based on city, country, title, and region; the employee distributions based on birth date, hire date, and employee name; the employee distributions based on city, country, territory, and region; the three supplier distributions based on city, region, and country; the product distributions based on city, region, country, categorized unit price, categorized units in stock, and categorized units on order; the customer distributions based on city, region, and country; the order and freight distributions based on year, month, and week; the order and freight distributions based on day, quarter, and ship country; the order and freight distributions based on ship region, ship city, and ship name; the order and freight distributions based on shipper company, customer company, and customer city; the order and freight distributions based on customer country, employee name, and employee title; the sales distributions based on year, month, week, day, quarter, and ship country; the sales distributions based on ship region, ship city, ship name, shipper company, customer company, and customer city; the sales distributions based on customer region, customer country, employee name, employee title, employee city, and employee country; the sales distributions based on product name, category name, supplier company, supplier city, supplier region, and supplier country.
Author: Rismon Hasiholan Sianipar Publisher: Independently Published ISBN: Category : Languages : en Pages : 0
Book Description
This book is PostgreSQL version of our previous book titled "DATA SCIENCE USING JDBC AND MYSQL WITH OBJECT-ORIENTED APPROACH AND APACHE NETBEANS IDE". This book uses the PostgreSQL-version of Sakila sample database which is a fictitious database designed to represent a DVD rental store. The 15 tables of the database include film, film_category, actor, customer, rental, payment and inventory among others. The Sakila sample database is intended to provide a standard schema that can be used for examples in books, tutorials, articles, samples, and so forth. In this project, you will design the form for every table and you will plot: top 10 film distribution by release year; top 10 film distribution by rating; top 10 film distribution by rental duration; top 10 film distribution by language; film distribution by categorized rental rate; film distribution by categorized length; film distribution by categorized replacement cost; top 10 film distribution by actor name; top 10 actor name distribution by average rental rate; top 10 actor name distribution by average replacement cost; film distribution by rating; rating distribution by average rental rate; rating distribution by average replacement cost; top 10 film distribution by category name, category distribution by average replacement cost; category distribution by average rental rate; category distribution by length; top 10 city distribution by country; top 10 address distribution by district, top 10 address distribution by country; top 10 address distribution by city; top 10 address distribution by district; top 10 address distribution by country; top 10 address distribution by city; top 10 inventory distribution by release year; top 10 inventory distribution by film rating; top 10 inventory distribution by film language; top 10 inventory distribution by film rental duration; top 10 inventory distribution by city; top 10 inventory distribution by country; top 10 customer distribution by country; top 10 customer distribution by city; top 10 customer distribution by district; top 10 customer distribution by store country; top 10 customer distribution by store city; top 10 customer distribution by store district; top 10 staff distribution by country; top 10 staff distribution by city; rental distribution by year of rental date; rental distribution by month of rental date; 10 rental distribution by week of rental date; rental distribution by day of rental date; rental distribution by quarter of rental date; rental distribution by film release year; rental distribution by film duration; rental distribution by film rating; top 10 rental distribution by staff name; rental distribution by film language; top 10 rental distribution by film title; rental distribution by customer active; top 10 rental distribution by film category; top 10 rental distribution by actor name; top 10 rental distribution by customer name; top 10 rental distribution by customer city; top 10 rental distribution by customer country, top 10 rental distribution by customer district; payment distribution by year of payment date; payment distribution by month of payment date; top 10 payment distribution by week of payment date; payment distribution by day of payment date; payment distribution by quarter of payment date; payment distribution by film release year; payment distribution by film duration; payment distribution by film rating; top 10 payment distribution by staff name; payment distribution by film language; top 10 payment distribution by film title; payment distribution by customer active; top 10 payment distribution by film category; top 10 payment distribution by actor name; top 10 payment distribution by customer name; top 10 payment distribution by customer city; top 10 payment distribution by customer country; and top 10 payment distribution by customer district.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 48
Book Description
Sakila for SQLite is a part of the sakila-sample-database-ports project intended to provide ported versions of the original MySQL database for other database systems, including: Oracle, SQL Server, SQLite, Interbase/Firebird, and Microsoft Access. Sakila for SQLite is a port of the Sakila example database available for MySQL, which was originally developed by Mike Hillyer of the MySQL AB documentation team. The project is designed to help database administrators to decide which database to use for development of new products. In this project, you will: read sqlite database and every table in it; read every actor in actor table, read every film in films table; plot case distribution of film release year, film rating, rental duration, and categorize film length; plot rating variable against rental_duration variable in stacked bar plots; plot length variable against rental_duration variable in stacked bar plots; read payment table; plot case distribution of Year, Day, Month, Week, and Quarter of payment; plot which year, month, week, days of week, and quarter have most payment amount; read film list by joining five tables: category, film_category, film_actor, film, and actor; plot case distribution of top 10 and bottom 10 actors; plot which film title have least and most sales; plot which actor have least and most sales; plot which film category have least and most sales; plot case distribution of top 10 and bottom 10 overdue costumers; plot which customer have least and most overdue days; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005.
Author: James Lee Publisher: Packt Publishing Ltd ISBN: 1788626087 Category : Computers Languages : en Pages : 293
Book Description
Solve all big data problems by learning how to create efficient data models Key FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learnGet insights into big data and discover various data modelsExplore conceptual, logical, and big data modelsUnderstand how to model data containing different file typesRun through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modelingCreate data models such as Graph Data and Vector SpaceModel structured and unstructured data using Python and RWho this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.
Author: Vivian Siahaan Publisher: BALIGE PUBLISHING ISBN: Category : Computers Languages : en Pages : 450
Book Description
This book uses SQL SERVER version of MySQL-based Sakila sample database. It is a fictitious database designed to represent a DVD rental store. The tables of the database include film, film_category, actor, customer, rental, payment and inventory among others. The Sakila sample database is intended to provide a standard schema that can be used for examples in books, tutorials, articles, samples, and so forth. Detailed information about the database can be found on website: https://dev.mysql.com/doc/index-other.html. In this project, you will develop GUI using PyQt5 to: read SQL SERVER database and every table in it; read every actor in actor table, read every film in films table; plot case distribution of film release year, film rating, rental duration, and categorize film length; plot rating variable against rental_duration variable in stacked bar plots; plot length variable against rental_duration variable in stacked bar plots; read payment table; plot case distribution of Year, Day, Month, Week, and Quarter of payment; plot which year, month, week, days of week, and quarter have most payment amount; read film list by joining five tables: category, film_category, film_actor, film, and actor; plot case distribution of top 10 and bottom 10 actors; plot which film title have least and most sales; plot which actor have least and most sales; plot which film category have least and most sales; plot case distribution of top 10 and bottom 10 overdue customers; plot which customer have least and most overdue days; plot which store have most sales; plot average payment amount by month with mean and EWM; and plot payment amount over June 2005.
Author: Vivian Siahaan
Author: Vivian Siahaan
Author: Vivian Siahaan
Author: Vivian Siahaan
Author: Vivian Siahaan
Author: Vivian Siahaan
Author: Vivian Siahaan
Author: Rismon Hasiholan Sianipar
Author: Vivian Siahaan
Author: James Lee
Author: Vivian Siahaan