Nowadays, aggregation of data becomes vital for creating a successful analytics environment and data-driven culture in organization. Many global corporations have turned to data warehousing to organize data streaming from corporate branches and operation centers around the world. In SMEs, the warehouse mostly used to aggregate raw data that collected across all business units.
Our team will help to refine data from multiple sources such as ERP, CRM, databases, raw files, external applications or manufacturing equipment towards a single data warehouse, with advanced architecture to unlock deeper insights for data-centric decisions. It ensures flawless creation of reporting, analytics and building customized KPIs. Hence, it will maintain all high level of data security, governance and compliance.
Further in result, building Data Warehouse based on Microsoft Azure will ensure strong BI and advanced analytics that can be built with an ease using services such as Azure Synapse Analytics, Power BI and Machine Learning.
1. You want to calculate Conversion Rate of each Sales Manager and for that calculation, you have Customer Traffic from your CRM system on one hand and Daily Sales figures from ERP on the other hand
2. Data is widely scattered across the departments within your organization in different formats and software, you need to consolidate data and review them in comparison, juxtaposing or interactive format for data-oriented decision, e.g. Actual vs Budget comparison.
Data warehouses are programmed to apply unified format to all collected data, which makes it easier for corporate decision-makers to analyze and share data insights with their colleagues around the globe. Standardizing data from different sources also reduces the risk of an error in interpretation and improves overall accuracy of information. Data warehouse use cases focus on providing high-level reporting and analysis across all business units and at different levels of organization. Use cases include:
Carrying out data mining to gain new insights from the information held in many large databases
Conducting market research by analyzing large volumes of data in-depth
An online business analyzing user behavior to make business decisions