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Consulting and survey of IT infrastructure
and architecture of data storage, processing and visualization systems
and architecture of data storage, processing and visualization systems
15
30
analyzed
source
systems and
systems and
options for data storage and processing systems
IT consulting
transport
Customer
A large transport company with 25 branches, subsidiaries and joint ventures
CHALLENGES/FEATURES
1. Lack of a unified digital ecosystem:
imperfect data synchronization between current IT systems
Slow change implementation due to complex and outdated systems slowed response to market demands and increased the risk of errors and data loss
The monolithic architecture of IT solutions and their reliance on outdated technologies created compatibility issues and complicated the implementation of modern solutions.
The scaling process was difficult: each new division presented a separate integration challenge
2. Poor quality of data from many sources limited the effectiveness of managers at different levels in making management decisions
3. Cloud implementation of IT infrastructure
Pre-project review of the customer's IT infrastructure, source systems, and reports, preparation of a review report, and drafting of specifications for the transition to a modern data storage, processing, and analysis architecture
Task
solution
Technical solution
architectural model of the current solution for storing, processing and analyzing data
functional architecture To Be
To Be component architecture
conceptual data model for 3 indicators
formalization of the register of sources, business glossary and list of indicators
Result
Business values
Отчет о предпроектном обследовании
analysis of bottlenecks in the current architecture and data management processes
ТЗ для перехода на современную архитектуру хранения, обработки и анализа данных
As Is architecture model
list of current sources and integration methods, volumes of downloaded data
architectural solution diagram
list of sources for integration
list of indicators and method of their calculation
data quality requirements
business glossary
data catalog
15 source systems were analyzed
30 options for data storage and processing systems (DBMS, ETL, DG, DQ, BI solutions) were analyzed
analysis of the current level of maturity in data management - data quality processes, cataloging, business glossary
recommendations for increasing the level of maturity in terms of data management and the transition to modern architectural components
non-functional requirements for the system, including scalability and performance
functional requirements; list of subsystems, their interrelations, list of components and functions of each component
other sections of the technical specifications completed in accordance with GOS
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