Services Offered
Business Intelligence Practice at Global Landmark offers a range of services in development and management of data warehouse, reporting and OLAP applications.
End-to-End Solution Implementation
The end-to-end solution offering addresses the complete BI application development life cycle both from a process perspective as well as from a function perspective.
Process Perspective
From a process perspective Global Landmark consultants engage with the customer at all stages of the life cycle of BI application development.
Step-1
Business Case: Partner with users to estimate 'size of opportunity' and carryout cost benefit analysis.
Step-2
Technology Selection: Compile broad (strategic and tactical) business requirements matrix and map the same to standard functionality available with market leading Data Warehousing and BI tools. Make a recommendation based on best fitment of the two.
Step-3
Requirements Gathering and Analysis: Interview key stakeholders on long and short-term objectives of the initiative, business metrics/KPI to be measured, reporting and performance requirements. In addition carryout source system analysis and identify gaps in data requirements and data quality issues.
Step-4
Architecture and Design: Articulate technical approach and key components of the solution.
 |
Design data architecture |
|
Design back end data extraction and transformation based on business rules |
|
Articulate reporting architecture |
Step-5
Development: Create physical database, develop and test ETL and reports.
Step-6
System Test: Carry out end-to-end functional and performance testing.
Step-7
User Acceptance Test: Support for user acceptance testing by way of bug fixes and clarifications.
Step-7
Deployment and Post Implementation Support: Post go-live warranty support.
 Top
Function Perspective
The other aspect of this offering is that it addresses a complete Data Warehousing and BI application development life cycle from a functional angle. The functional areas can be broken down into three major parts.
|
Data architecture |
|
ETL design and development |
|
Report and OLAP design and development |
|
Design integration between all three components |
Data Architecture
The data architecture is designed based on current user requirements, cost considerations, long and short-term strategic objectives. Some of the frequently used data deliver-models considered for a range of scenarios are:
|
Enterprise data warehouse |
|
Operational Data Stores (ODS) |
|
Subject area data-marts |
In most practical cases a hybrid model dictated by various factors like objectives and goals, business benefits vis-à-vis cost is adopted.
A three step database design process follows involving
|
Logical data-model |
|
Physical data-model |
|
Database sizing |
ETL Design and Development
Refer Data Sourcing, ETL Design and Development.
Report Design and Development
Refer Customer Reporting and Dashboard Visualization
and OLAP Design and Cube Building
Business Requirements Gathering
This offering focuses on helping the client organization to articulate a coherent set of business requirements that undertakes to holistically address organizational needs. Some of the key strategic considerations for this are:
|
Key business drivers for the initiative |
|
Long-term business objectives of the initiative |
|
Critical capabilities that are required in the solution to meet the long and short-term objectives |
|
Manner in which the business would utilize the application |
|
Level of integration necessary between the BI application and business processes in context |
|
Key business areas that would benefit from the initiative |
|
Data security issues |
|
Business perception of data quality |
|
Business perception of data sufficiency |
In addition to the above, the requirements gathering exercise focus on the following aspects of the requirements:
Functional Requirements
|
Key Performance Indicators (KPIs) |
|
Static custom reporting along with tabular/graphical presentation of data |
|
Drill down and drill through requirements |
|
Ad hoc querying |
|
Exception Reporting and Alerting |
|
Slicing and dicing (OLAP) of data |
|
Report Presentation |
|
Report/Data Delivery |
|
Data-migration/pre-population |
Non-Functional Requirements
|
Business User Base and geographical distribution |
|
Business User Roles |
|
Standard Query Performance |
|
Recovery of data loss |
|
System Availability |
|
Backup of system and data |
|
Restoration of backup |
|
Error Logging |
|
Database Sizing Statistics (Current/Projected future) |
|
Data availability for querying (Lag from real time) |
|
Online data storage requirements |
|
Data Quality/Report and Audit |
|
Business Security and data protection |
|
Training of User base |
|
Documentation |
|
Long-term storage and archival requirements |
|
Long-term storage and archival retrieval |
Data Modeling
The offering focuses on developing data architectures driven by business requirements and long-term organizational needs. Some of the classical models considered are:
|
Enterprise Data-warehouse with subject area data-marts
(Hub and Spoke Model) |
|
Stand-alone subject area data-mart |
|
Operational Data-store (Need for quasi-real time data integration) |
In most practical cases a hybrid model based on business requirements and drawing on the strengths and capabilities provided by the classical models are used.
The main essence of this exercise to understand and address enterprise-wide data integration needs and devise strategies in achieving the same.
Data Sourcing, ETL Design and Development
This service offering centers around source system analysis with the help of subject-matter experts to assess data gaps against reporting/data requirements from the data warehouse/data-marts. This is followed by:
|
Devising data extraction strategies from source system. |
|
Finalizing data warehouse update strategy based on requirements for storing historical data. |
|
Devising mechanisms for data transfer. |
|
Finalizing data cleansing and validation rules. |
|
Finalizing data transformation business rules. |
|
Mechanism for process logging, error handling, rejected data processing etc. |
The final output results in population of target data warehouse or data-mart structures.
Customer Reporting and Dashboard Visualization
Business Intelligence Practice at Global Landmark also engages in application development to enhance the users' experience. Global Landmark's competence lies in the ability to develop mechanisms for enabling customers to make informed decision by leveraging their data investments and performing in-depth analysis to ferret out trends, patterns and events in organization-wide transactional data. Some of the main types of user interfaces developed are:
|
Customer reporting with or without graphical representation of data. |
|
Enterprise/departmental dashboard visualization. |
|
Custom reporting with drill down to explore data relationships and varying levels of summarization. |
OLAP Design and Cube Building
This offering capitalizes on Global Landmark's competence in designing and constructing data cubes using market leading tools to enable the business users to slice and dice data to fulfill there analytical needs.
Slice and dice requirement is collated during business requirements collection and centers on the Key Performance Indicators (KPI) and the related data required to measure the KPI.
Data Migration for Go-live
Most of the data warehouses/data-marts require historical data from transactional systems to be pre-populated before 'Go live' in the production environment. In many cases, this requires specific data-migration strategies and data-migration application to be written to pre-populate the target data structures.
Global Landmark leverages on its competence in handling large data volumes found in a Data Warehousing environment and experience with scalable ETL tools to provide this service.
Application Management
The application support offering at Global Landmark includes:
Tier-2 Support
This involves receipt of tickets/MR from the Tier-1 Support teams and carrying out initial/business analysis on the same. The support analyst would contact the business user/s who raised the request with queries and clarifications on the requirement. They would then complete the remaining analysis and offer resolution to the problem at hand if the same can be done without any modifications to the application code. If the same cannot be done then the analyst would reassign the ticket/MR to the Tier-3 Support team.
Tier-3 Support
This team comprises mainly of technical analysts who would conduct detailed impact analysts based on the initial analysis/information provided by the Tier-2 support team. Following this they would contact the Tier-2 analyst for any queries and clarifications on the tickets/MR. In effect the Tier-2 analyst would function as an interface between Tier-3 and business user. Following analysis and design the cod modification would be carried out and then followed by regression testing, user acceptance testing and deployment.
Top
|