Gallive Infotech

Gallive Infotech

IT Consulting

Solution Architecture

  • Solution architecture is a consolidated of role, process and documentation merged together to address specific problems and requirements, usually through the design of specific information systems or applications. The term solution architecture can be used to mean either or both: Manuscript describing the structure and outcome of a solution to a problem, or A route for describing a solution and the work to deliver it. Solution Architecture will play a major role in kind of business. Solution architecture starts with Feasibility study, Gap analysis and suggesting the solutions. Based on solutions the business will decide to go or no go steps.

Typical outcomes of Solution Architecture

  • Solution Architecture will give a clear picture of baseline state to target state. Solution Architecture manuscript described in the level of a vision or in detailed solution outline. It exactly specifies a system (usually a secondary in a wider enterprise system) objective to solve a specific problem and/or satisfy a specific set of requirements. It may be an IT system to help a single business role or process. For example, an end-to-end Supply Chain Management system that allows customers to place orders for goods and services; or an end-to-end Supply system that enables an enterprise to order new stock from its suppliers. A solution outline typically defines the business context, business data to be created or used, the application components needed, the technology platform components needed, along with whatever is needed to meet non-functional requirements (speed, throughput, availability, reliability recoverability, integrity, security, scalability, service ability, etc.).

Database Re-engineering

  • Database reengineering: In general, any process which delivers an updated version of a legacy database according to definite criteria (correctness, freeing from obsolete constructs, normalization, optimization, distribution, using modern technologies, etc.). Requires a detail, up-to-date documentation of the source DB to proceed with re-engineering which will reduce time & cost.

Some database Facts


  • A database may be used by several thousand programs routines;
  • A database schema may include more than 1,000 entity types and 30,000 attributes (technically, 1,250 files/tables and 40,000 fields/columns);
  • ERP’s =15,000 - 30,000 tables and 2,00,000 columns;
  • Some database schemas have got so large and’s complex that no single associate can master it any longer;
  • The precise description of an entity type and its attributes may span from 1 to 100 pages;
  • The functional documentation of a large database may (should) comprise more than 5,000 pages; what about your database?
  • The SQL-DDL code of a database (tables, constraints, indexes, triggers, checks, etc.) may comprise 2,00,000 LOC (5,000 pages);

D M / DWH / BI

DLM (Data Lifecycle Management)

Data governance will help top level people of the access, regulatory compliance, and risk mitigation clubbed with an company’s important data. By monitoring the data, enterprise not only recovering their valuable data, but have cycles and drive process and practices in place to make better concrete resolutions to get back clients and acquire new businesses.  

Boon of Data Governance

  • Guarantees data quality
  • Increases effectiveness of all sources data processes
  • Diminishes overall system maintenance by catching flaws early stage
  • Verifies immediate defiance with organization standards
  • Eradicates rise of faulty data

Our Offerings

  • Putting into practice of data cleansing sequences, which are based on data quality principles and the enterprise business rules
  • Construct an operational corporate process model for handling data and the rigid supervision to implementing it
  • Endorse IT background that provisions business goals in a cost-effective fashion.

Boon of Data Assessment

  • Evaluates the effect of data against corporate performance and metrics Discovers data disputes such as partial and replica records Empowers better conclusion making based on eminence data that results from the clean records Enhances applications and safeguards reporting reliability

Our Offerings

  • Finding routes and mapping of data elements, data quality statistics, graphs, and measurements that highlight data integrity Tester Model Assessment