Software Development

Software Development

Developing Software solutions for your Business Enterprise.

Software Development

We are special because Mind Solvit’s development team is much capable of handling complicated business affairs using broad range of business solutions. We are energetic with software development solutions which provides the ability to grow your business world-wide. The software development methodologies ensure high productivity and rapid delivery of software solutions to our clients.

Our clients admire the way our software team handles the business solutions in a clear, transparent and innovative manner. Clear means that we are capable of producing perfect span for your requirements. Transparent means that we are authentic in the software methodologies and also we share our views with clients. Innovative means that we are always confident in what we are doing and this helps us to discover better ideas to make the software solutions better and better.

Innovation Ahead - Sometimes the best way to envision the future is to invent it.

Our software development team is capable of emerging Innovations in Agile Software Development which mainly focuses on the use of agile methodologies to manage, design, develop, test and maintain software projects. Our team is transforming innovative ideas into reality.

Application design is the process by which an agent creates a specification of a software artifact, intended to accomplish goals, using a set of primitive components and subject to constraints. Software design may refer to either all the activity involved in conceptualizing, framing, implementing, commissioning, and ultimately modifying complex systems or the activity following requirements specification and before programming, as in a stylized software engineering process. Software design usually involves problem solving and planning a software solution. This includes both a low-level component and algorithm design and a high-level, architecture design.

Application development is the process of computer programming, documenting, testing, and bug fixing involved in creating and maintaining applications and frameworks resulting in a software product. Software development is a process of writing and maintaining the source code, but in a broader sense it includes all that is involved between the conception of the desired software through to the final manifestation of the software, sometimes in a planned and structured process. Therefore, software development may include research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities that result in software products.

Application maintenance is the process of modifications done in the software product after their delivery to fix defects and to improve performance of the application each time. Application maintenance is a very broad activity that includes error detection and correction, enhancements of capabilities, deletion of obsolete code and optimization. The key software maintenance issues are both managerial and technical. Key management issues are: alignment with customer priorities, staffing, which organization does maintenance, estimating costs. Key technical issues are: limited understanding, impact analysis, and testing and maintainability measurement.

Big Data

Big data is extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. Big Data refers to technologies and initiatives that involve data that is too diverse, fast-changing or massive for conventional technologies, skills and infra- structure to address efficiently.

Database Management

Discover a cloud database with no boundaries.

Database design is the process of producing a detailed data model of database. This data model contains all the needed logical and physical design choices and physical storage parameters needed to generate a design in a data definition language, which can then be used to create a database. A fully attributed data model contains detailed attributes for each entity. The term database design can be used to describe many different parts of the design of an overall database system. Principally, and most correctly, it can be thought of as the logical design of the base data structures used to store the data. In the relational model these are the tables and views. In an object database the entities and relationships map directly to object classes and named relationships. However, the term database design could also be used to apply to the overall process of designing, not just the base data structures, but also the forms and queries used as part of the overall database application within the database management system (DBMS).

Data integration involves combining data from several disparate sources, which are stored using various technologies and provide a unified view of the data. Data integration becomes increasingly important in cases of merging systems of two companies or consolidating applications within one company to provide a unified view of the company's data assets. The later initiative is often called a data warehouse. Probably the most well-known implementation of data integration is building an enterprise's data warehouse. The benefit of a data warehouse enables a business to perform analyses based on the data in the data warehouse. This would not be possible to do on the data available only in the source system. The reason is that the source systems may not contain corresponding data, even though the data are identically named, they may refer to different entities.

Database mining is an interdisciplinary subfield of computer science. It is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD.