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Database Design

Database design is referred as collection of processes which is used in organisation of data, designing, implementation, development and maintenance of enterprise data management systems for high performance and meeting the requirements of the users. Database design includes two design models i.e. logical model and physical data design model where logical model focuses on data requirements and physical data design model includes the translation of logical design of the database into physical media via hardware resources and software systems.

  • databases and database design
  • DBMS
  • Conceptual modeling
  • ER diagramming
  • relational model
  • Logical modeling
  • Normalization
  • SQL
  • Issues and Trends in DBMS

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Database Design Report writing, case studies , essays & proposal writing including masters thesis & dissertation: 

  • Database Fundamentals,Advantages of database,Relational database design,Entity relationship diagrams, Normalization, Modify CRM database for Normalization, Create MS Access CRM database with tables
  • form, reports, Structured query language, Data definition,Queries, SQL views, Create SQL database with tables, queries, views
  • Database Design, Requirements analysis,Data modeling ,entity relationship model,Transforming data model into database design, Database Management, Database administration, Control
  • security , reliability, database security plan, Database Processing Applications,Triggers , stored procedures, Set up Web database processing
  • Business Intelligence Systems, data warehousing, data marts, dimensional databases, data mining
  • Data analysis, Relational model, ER diagramming, Normalisation, Database implementation , management using Oracle, Data manipulation language SQL, Data definition language

DATABASEDatabase is a data structure which stores data and more databases contain multiple tables. The tables of database would have different fields which store relevant information.

Types of Database:

  • Hierarchical Databases: Hierarchical database is organized in pyramid fashion like the branches of a tree. The records in this database are grouped together. The top record in this database is called as root record. A child record which is linked to root record always has only one parent record.
  • Network Databases: These are similar to hierarchical databases. But there are interconnected network of records there is one difference. The children node is called members and parents are called owners in network databases. In this database there can have more than one parent for each children.
  • Relational Databases:  Relational databases define the relationship between data files is relational. Relational databases connect data in different files by the use of a key field. Data in these databases is stored in different tables. It is more flexible than the hierarchical and network database structures.
  • Object-oriented Databases: it can handle graphics, photographs, and audio and video data types. It can also handle structured data. It can be used to store data from a variety of media sources like photographs and text.


  • Self-Describing Nature of a Database System:  It describes data structure and constraints also which makes database different from the traditional file-based system.
  • Insulation between Program and Data:
  • In the database, the data structure is stored in the system catalog not in the programs. 
  • Support multiple views of data:
  • A view which is a subset of the database. It contains only useful data. Multiple users in the system might have different views of the system.
  • Sharing of data and Multiuser system:
  • it allows multiple users can access the database at the same time.
Beginning Database Design
  • Evolution of Database Modeling , File Systems, Hierarchical Database Model
  • Network Database Model , Relational Database Management System , Object Database Model , Object-Relational Database Model , Examining the Types of Databases , Transactional Databases , Decision Support Databases , Hybrid Databases , Database Model Design.
  • Database Modeling in the Workplace: Incorporating the Human Factor , People as a Resource, Talking to the Right People , Getting the Right Information
  • Dealing with Unfavorable Scenarios , Computerizing a Pile of Papers , Converting Legacy Databases , Homogenous Integration of Heterogeneous Databases , Converting from Spreadsheets , Sorting Out a Messed-up Database. Database Modeling Building Blocks: Information, Data and Data Integrity, the of Tables , Records, Rows, and Tuples , Fields, Columns and Attributes
  • Datatypes, Simple Datatypes, Complex Datatypes, Specialized Datatypes, Constraints and Validation, Relations for Normalization , One-to-One, One-to-Many, Many-to-Many, Zero, One, or Many
  • Identifying and Non-Identifying Relationships , Referential Integrity , Alternate Indexing , Foreign Key Indexing , Types of Indexes
  • Designing Relational Database Models: Concept of Anomalies , Dependency, Determinants, and Other Jargon , Defining Normal Forms
  • 1NF ,2NF , 3NF , One-to-One NULL Tables , Boyce-Codd Normal Form , 4NF , 5NF , Domain Key Normal Form
  • Reading and Writing Data with SQL: SELECT , Filtering with the WHERE Clause , Sorting with the ORDER BY Clause , Aggregating with the GROUP BY Clause , Join Queries, Nested Queries, Composite Queries, Changing Database Metadata.
  • Advanced Relational Database Modeling: Denormalization, Reversing Normal Forms , Data Warehouse Database Model
  • Data Warehouse :Surrogate Keys in a Data Warehouse , Referential Integrity in a Data Warehouse , The Dimensional Database Model , Data Warehouse Modeling , Types of Dimension
  • Building Fast-Performing Database Models: Factors Affecting OLTP Database Model Tuning , Factors Affecting Client-Server Database Model Tuning , Factors Affecting Data Warehouse Database Model Tuning , Database Model Tuning , Writing Efficient Queries ,HAVING and WHERE Clauses , Joins, Auto Counters, Efficient Indexing for Performance
  • A Case Study in Relational Database Modeling: Planning and Preparation Through Analysis,Steps to Creating a Database Model , Step 1: Analysis , Step 2: Design, Step 3: Construction

Database Design includes:

  • Normalization and Data Integrity
  • Discovering Business Rules , Case Study: The Data Warehouse Model , Establishing Company Operations , Project Management, Project Planning and Timelines , Budgeting.
  • Creating and Refining Tables During the Design Phase: OLTP Database Model , Data Warehouse Database Model , Referential Integrity, Primary , Unique and Foreign Keys , Identifying versus Non-Identifying Relationships , Parent Records without Children, Child Records with Optional Parents, Referential Integrity , Denormalization , Case Study , Deeper Normalization Layers.
  • Datatypes , Simple Datatypes , Microsoft Access Datatypes , Specialized Datatypes , Case Study: Datatypes
  • Keys and Indexes , Business Rules and Field Settings: Classifying Business Rules in a Database Model, Normal Forms, and Relations, Classifying Relationship Types , Explicitly Declared Field Settings
  • Storing Code in the Database , Stored Function, Event Trigger, External Procedure, Encoding Business Rules
  • Advanced Database Structures and Hardware Resources: Clusters, Auto Counters, Views , Materialized Views , BTree Index, Bitmap Index, Hash Keys and ISAM Keys , Clusters, Index Organized Tables, and Clustered Indexes , Auto Counters , Partitioning and Parallel Processing.
  • Reverse and Forward Engineering , Create, Update, Delete operations via SQL , Contemporary non-relational approaches, Relational models, object-oriented models.
  • Unified modeling language, spatial databases on the cloud, spatial data standards, metadata, spatial indexes, data , legal issues, Modeling principles, impact of the correctness of database design to information system, organizational and management patterns.
  • People, roles, competences, tasks , Organizational units, partners , Products, composition, material , Procedures, work orders, resources usage , Processes, flows, monitoring , Assets and its usage , Contracts and certificates, items, contract roles, deliveries , Documents, authors and other roles, contents, structure, versions, formats , Regions and locations, addresses, spatial relationships , Time and temporality , Standby Databases , Replication, Grids and Computer Clusterin.
  • Logistics and Database , Advanced,Transactions,Mechanisms for Transactions: Logging and Locking,IO Cost Models and External Sort,Indexing,Access Methods and Operators,Dark Data and Analytics Systems
  • Formal relational language
  • Relational algebra, Database Architecture, Database System, Transactions processing and concurrency control, Recovery,Indexing,Query processing and optimization, Security and access control
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