Data Modeling

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Data Modeling

With a variety of multiple different applications, databases and nosql data stores, many businesses currently discover their data inconsistent, complex, leading to under-utilization, unsureness, inaccuracy, wariness, not easy to work with and less informed decision making in the business. This can frequently lead to misunderstandings, suspicion, disorganization, errors, under utilization and ultimately resulting in poor decision making for the business. As part of its data modeling services we at biztechnosys whole heartedly work with our valuable clients to create a complete data architecture roadmap that is essentially based on best practices, industry standards and latest proven techniques. Data modeling is an analysis which determines how data is exposed to the end user. Data modeling is an integral part of any organization’s ability to analyze and extract value from its data.

data modeling

Every individual who is involved, starting from collection to consumption, should know what data modeling is and how they a stakeholder can put up to a successful data modeling practice. Data modeling is an analysis of data objects and their relationships to other data objects. Data modeling is the primary step in database design and object driven programming as the designers first begin with creating a conceptual model of how data items relate to each other and then process further.

Why do you need to use data model?

The major goals of using data model in your business projects include -

  • Data modeling ensures that the complete data objects desired by the database are accurately represented because wrongful omission of data will lead to creation of faulty reports and produce incorrect results.
  • A data model helps design the database at all levels starting from conceptual, physical and logical levels.
  • Data model structure assists to define the relational tables, primary and foreign keys and stored procedures.
  • Data modeling provides a clear picture of the base data and can be used by database developers to create a physical database.
  • Data modeling is also helpful to identify missing and redundant data.
  • Though the initial creation of data model is stressful and time consuming, but in the long run it makes your it infrastructure upgrade and maintenance cheaper and way faster.

Major advantages and disadvantages of data modeling:

Advantages of data model include -

  • Data model also helps to recognize correct sources of data to populate the model..
  • The main aim of designing data model is to make sure that the data objects offered by the functional team are represented accurately.
  • The data model contains detailed information that can be rightly used for building the physical database.
  • The information provided in the data model can be used for defining the relationship between tables, primary and foreign keys, and stored procedures
  • Data model helps businesses to communicate within the organization as well as across organizations.
  • Data model helps documenting data mappings in etl process

Disadvantages of data model include -

  • To develop data model one should clearly know physical data stored characteristics.
  • Even a smaller change made in structure requires modification in the entire application.
  • There is no set data manipulation language present in dbms.
  • This is a navigational system which produces complex application development, application management. Thus, it requires deep knowledge of the biographical truth.

Biztechnosys offers the following data modeling services

Biztechnosys focuses on a sturdy and powerful data modeling approach based on well-defined standards, practices, and techniques to form a comprehensive data architecture roadmap.

Our data modeling structure equips your business with a strong methodology to model data in a standard, consistent and predictable way that allows you to make use of data as a corporate resource while also being able to freely adjust with the changing environment.

By developing data models at different levels, biztechnosys professional data modelers record the requirements of the business as they are provided. This strategy leads to physical data models that are integrated, consistent and usable at all levels of the business.

Biztechnosys team actively works on the data models, while transferring knowledge to the client’s participating team members.

Biztechnosys team of professionals delivers mentoring services and provides advice and support to their clients.

Team at biztechnosys reviews models developed by the clients and provides best practice recommendations to the clients.

Different types of data models

There are mainly three different types of data models which are discussed below -

Conceptuals - conceptual type of data model is a clear depiction of a system, comprised of hybrid of concepts which are used to help people know understand or simulate a subject the model represents. This type of data model mainly defines what the system actually contains. This conceptual model is typically created by business stakeholders and data architects. The purpose of conceptual model is to organize scope, clearly define business concepts and rules.

A logical model is a completely attributed conceptual model. The attributes are completely spelled out with no abbreviations. High-level data types like string, number etc. Are provided at this point but do not involve any details of the physical implementation in the logical model. The logical model will give the customer a more detailed review of how the dimensions and facts will perform. This model is occupied to the business user who understands in detail how the business works and the reporting that is required from the warehouse. This type of data model mainly defines how the system should be implemented regardless of the dbms. This type of model is typically created by data architects and business analysts. The purpose is to successfully develop technical map of rules and data structures.

finally we reach to the physical data model, this is a logical model with suitable abbreviations where necessary and the suitable physical data structure attributes like datatypes, primary, foreign keys, storage location etc. Defined for the fact and dimension tables. This model is used predominantly used by the database administrators and the application developers and shall only be shared with the customers as and when required or requested. This type of data model describes how the system will be implemented using a specific dbms system. This model is primarily created by dba and developers. The purpose of physical data model is actual implementation of the database.

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