August 14, 2018

Data Warehouse & Business Intelligence

Strategies and success of businesses heavily rely on accurate and flexible data reports thanks to the technical advancement in Business Intelligence tools and technologies. Many great software have failed in the industry because they are not backed by the perfect reporting solutions. We come with hands-on experience of the working with small to big-sized enterprise systems and their data warehouse solutions. We are also well versed with tools and techniques that can fit well with the business needs.

Challenges & Approach

Is your team choosing the right data warehouse architecture standard?
We know what to choose when it comes to designing data warehouse. Be it 3NF, Star Schema or Data vault, we can advise you what works best for your business and why.
Is your team conducting data sourcing exercise before even starting on data warehouse project?
We do one-on-one sessions, joint application design (JAD) sessions with your business stakeholders and meet with your technical teams to derive business requirements for DWH. We perform in-depth data source research to check quality of data and derive transformation standards.
Is your Metadata clearly defined?
We conduct sessions with your business stakeholders to define and document “your” Metadata, including definitions, values, security characteristics, ownership, timeliness, quality, data type and length. We consider this as a crucial stage for future data analysis needs.
Have you considered desired privacy and security implementation for data warehouse?
Data warehouse is not only essential for the business that owns the data but also for the customers and many other entities. However, it creates a risk of the data being compromised or/and accessed without authority. We consider this vital and our approach is to have equal security considerations that you generally have for originating storage.
Have you excluded data warehouse from your testing/QA processes?
Testing of ETL/ELT and refined data is vital to your data warehouse. Along with user acceptance testing, we conduct test for documentation as well as performance of ETL.
Do you know Agile methodology is possible for DWH?
With our proper planning aligning to a single integration layer, data warehouse projects can be broken down into smaller, faster deliverable pieces that return value much more quickly. This also allows you to prioritise the warehouse as the business needs change.
Do you favor ELT over ETL?
Moving corporate data, as is, to a single platform should be job #1. Then legacy systems can be bypassed and retired along the way, helping the business realise savings faster. Once data is collocated, it is much more efficient to let the power of a single cloud engine do integrations and transformations (i.e. fewer moving parts, push down optimisations, etc.)