<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=974250883405448&amp;ev=PageView&amp;noscript=1">
Creating a Data Centric Enterprise

Cloud, Analytics, DWC

Creating a Data Centric Enterprise

Shashank Paritala
Shashank Paritala | Oct 26, 2022

In today’s rapidly evolving world, organizations understand that data is essential for growth and success. In most organizations, they do not have the proper tools and processes that empower leaders to make more informed, data-driven business decisions, and predict future market trends. As a result, over 90% of organizations are unprepared for a data-centric future due to a variety of reasons. Some key reasons include:

  1. Enterprise Wide Data Silos - Data silos created by inconsistent architecture, typically driven by impulsive tool purchases before implementing a well thought out data strategy and platform.
  2. Development/IT Bottlenecks - Data centric organizations thrive by empowering users to explore data freely under rapidly evolving circumstances. Most analytics landscapes are built by tools and processes that are managed by  IT teams, rather than business users.  This can effectively turn any ad-hoc requests into a weeks-long process. 

SAP Data Warehouse Cloud (DWC) help organizations transform into data driven enterprises while preserving and complementing their current analytics systems. SAP DWC is a cloud-hosted data warehouse as a service (DWaaS) running on SAP HANA Cloud database and is a key part of SAP’s Business Technology Platform (BTP). This comprehensive solution combines data warehousing, data integration, and the latest analytics capabilities. 

Building a Modern Unified Data Platform using DWC

The modern enterprise IT landscape is typically made up of a core ERP, HR system(s), CRM system(s), POS system(s), and other specialized applications that all generate data in various databases and  in various hyperscalers (Azure, AWS and etc).  

Creating a unified data platform involves 4 steps:

  1. Aggregate: Combining data from every source in the organization
  2. Define and Categorize: create an agreed upon data dictionary for all data entities
  3. Validate: creating a data quality framework to ensure trust in the data platform
  4. Democratize: Ensure consumption tools and training protocols are in place for the entire organization to access the “single source of truth” 

How DWC creates modeling capabilities for different departments:


 Modeling Environment

 User Group

Native HANA DB modeling with an IDE IT Developer
Full Service SQL data warehouse IT Developer/Data Analyst
Graphical Data Modeling Interface IT Developer/Data Analyst
Business Builder Layer Business Analysts/End Users/Data Analysts


SAP DWC’s unique “data warehouse as a service” approach creates a single integrated product that can achieve all of the above. DWC goes beyond the traditional data warehousing duties due to its ability to centralize data from a wide array of sources (e.g. Azure, AWS, GCP, On-Prem etc). Furthermore, DWC has the capability to redefine disparate data entities to conform to unified enterprise data definitions, while subjecting all data to business defined data quality rules. This allows organizations with complex landscapes and large on-premise investments to create a single unified data platform that provides reliable data to all its users.