Through our database engineering we can help businesses to structure and analyse Big Data, making the most out of it.
During any database engineering, our database developers ensure that a database management system (DBMS) can handle massive quantities of data. From designing to modifying and editing databases we cover the whole development process in dedicated teams for each project, using a typical three-step approach for any new database to implement the conceptual, logical and physical design.
A vast range of great database engineering tools helps developers build and maintain proper and flawless database structures to support uncounted business applications. Once a database structure or data warehouse structure has been created, it is necessary to implement countless test series, using and editing test data.
User Defined Functions (UDF) and the creation of data tracks (for stored data) are also integral parts of any solid database engineering.
Range of industries we have been working for
Tax & Legal Service
Database Strategy - A Path to Data Warehousing
A database management system (DBMS) is a computer software application that interacts with end-users, other applications, and the database itself to capture and analyze data. A general-purpose DBMS allows the definition, creation, querying, update, and administration of databases.
Database design is the process of producing a detailed data model of a database. This data model evolves during the database engineering process and contains all the needed logical and physical design choices and physical storage parameters needed to generate a design.
- Step 1: Define the Purpose of the Database (Requirement Analysis).
- Step 2: Gather Data, Organize in tables and Specify the Primary Keys.
- Step 3: Create Relationships among Tables.
- Step 4: Refine & Normalize the Design.
Strategic & tactical planning
Our renowned Database Engineering and Developments will allow you to:
- Safe storage of Bulk Data (Big Data)
- Data Warehousing Upgrades – Analyse and Structure your Data
- Retain high Data quality, attracting paying customers
- Manage your time so you’ll get more done in less time
- Cut expenses without sacrificing quality
- Automate business processes, saving time and expenses