Data Lake / Data Warehouse
Majority of the company’s focus more on the real time transactional system however when it comes to analytical systems such as Data Warehouse, the value is quite very less understood.
With more and more transactions, the amount of data that needs to be tracked, consolidated and audited is more than ever before. Irrespective of whether its logging data or devops data or transactional data such as order, shipment, inventory data – all this data has a relevance of lifetime which needs to be tracked outside the real time repository to understand the lifetime value of either a customer, product usage, patterns, trends and other useful KPIs, measures which shall relate directly to business outcome and business goals.
Using Data Warehouse, we can get the right information to right people, scale your transactional systems by unburdening the history and tracking elsewhere, improve data governance, predict useful business indicators around customer, products, services etc., This not only helps from a business perspective but also in terms of the overall data quality and reporting, business intelligence, analytical needs.
In cases where predefined structure or business need is not necessarily understood, the concept of Data Lake helps to gather the data from various sources without any normalization making it readily available for various types of analytical, analysis and modelers to explore as various use cases come.
Using our data specialist, We use a combination of approaches such as but not limited to Data Virtualization, Dimensional Data Warehousing cube designs, tabular models, Data Lake to help realized untapped value that resides in the data as these below use cases.
- Data lake (ELT) based Digital Banking Environment
- ETL based Data Warehouse with In-memory based tabular model reporting services
- Manufacturing based Operational Analytics and Analysis Platform
- 360 Degree View of the Customer in e-Retail/e-Commerce environment