Data Warehouse

Data Warehousing platform is at the core of any reliable and
efficient Business Intelligence and Analytics solution.

We have an extensive experience of working in a wide variety of data environments
and building best-in-class Data Warehousing infrastructures to make your data trustworthy.

Challenges

  • You are restricted in reporting and anlytical capabilities due to limited access to data,
    especially in cross-functional, internal/external and historical scenarios.
  • Your data is stored in multiple data sources, which makes data collection and reuse a
    laborious and extensive job, leading to multiple versions of the truth.
  • You experience problems with performance of your transactional systems as their
    normal operations are disrupted by loads of queries for reporting and analysis purposes.

Services

Analyze
1
Business, functional and metadata requirements
Technology and tool selection
Infrastructure requirements and technical readiness
Data quality audit
Architect
2
Solution architecture
Logical and physical views
QA and metadata strategy
Technical architecture
Design
3
Data warehouse and data mart models
Data sources analysis
Physical database design
Presentation layer
Build
4
Physical database
Data quality process
Data integration process
Presentation layer
Test
5
Testing strategy and readiness
System testing
Acceptance conduction
Performance tuning
Deploy
6
Solution deployment
User training
Development to production migration
Documentation
Operate
7
Support
Monitoring
Maintaining and upgrading
Operational discovery

Value

  • Increased trust in information, based on a single view of all company data, collected from disparate and potentially incompatible internal and external locations.
  • Enhanced agility in access to business information, enabled by converting masses of data from operational systems to a format that is current, actionable and easy to understand.
  • Increased performance of operational systems, since queries generated by users are switched to data warehouse and do not interfere with processing of system transactions.

Case Study

  • A big Telco company used a home-baked system for its network quality and capacity management. The system capabilities were quite limited. Its low productivity couldn’t cope with company’s constant growth of data; absence of alert notification feature hid problems occurring with network; and limited facilities in producing reports caused delays in reports producing as only few individuals could create them.
  • We developed a Data Warehouse System with operational, detailed and analytical data layers in it to increase system’s productivity and reduce time on data processing. On the basis of this Data Warehouse System we developed a Network Management Performance System that was to give the client a possibility for monitoring and effective management of network performance.
  • The client received a single source of accurate data with reports creating facilities for all users who could now work with data effectively. A new integrated system’s productivity was able to satisfy client’s needs in data processing. It provided alert and monitoring features for analysing changes occurred within network indicators and replying to these changes effectively.
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