Enterprises today increasingly rely on data-powered innovation to drive digital transformation. Hence, it’s critical for organizations to harness real-time data insights to make intelligent business decisions. Artificial Intelligence (AI) and Machine Learning (ML) have become the preferred technologies that organizations depend on to solve this challenge. As digitization, flexibility, and agility become the need of the hour, AI and ML-based solutions serve as the backbone of the system that can help business leaders achieve their objectives of expansion, governance, and compliance through innovation.
Platforms for data analytics
SAP HANA is one of the leading database management platforms that can be deployed either on premise or in cloud environments. SAP HANA enables business leaders to make effective, intelligent insight-driven decisions. Additionally, it can help dismantle data silos by serving as a single foundation for all disparate legacy systems, thereby meeting the data requirements of a business. However, as businesses scale and evolve, their data and analytics requirements get more complicated and the technical limitations of SAP HANA warrant a data platform that can generate data insights both within and across business channels.
Google BigQuery is an economic and fully managed, petabyte-scale, serverless enterprise data warehouse of choice for start-ups, as well as Fortune 500 companies. The ability of Google BigQuery to work with Google’s cloud storage to scan petabytes of data in real time makes it one of the most preferred technologies for global enterprises. This provides enterprises and data analysts, the ability to analyze data at scale and share these insights in a secure and simplified manner with significantly lower TCO (reduce cost of operation by upto 46%).
Innovation powered by collaboration
So, is it worthwhile for enterprises to move SAP HANA data to Google BigQuery and use the pre-build/post-build AI and ML models?
Recent advancement in AI and ML-powered smart data access technology makes it possible to combine SAP HANA datasets with Google BigQuery facilitated data ingestion and data federation inside the HANA platform. The combined power of SAP HANA and Google BigQuery empowers organizations across industries to take rapid, informed, and data-driven decisions.
Figure1. Move SAP HANA Data to Google BigQuery using existing AI and ML models
There are significant business advantages of combining SAP HANA with Google Cloud, such as:
- A smart infrastructure that is secure and compliant, and can simultaneously maximize uptime and performance
- A best-in-class disaster recovery (DR) network
- Advanced citizen analytics, freed resources, high-speed deployment, and machine learning techniques that allow organizations to enhance the efficiency of business processes and expand new revenue streams
- An exceptional client response, thanks to the ability of SAP HANA and Google custom solutions to cater to different business requirements
So how do organizations integrate SAP HANA with Google BigQuery?
Thankfully, the process is relatively simple and straightforward. Multiple ready-made technologies such as pipes and connectors are available in the market. Organizations can choose what works best for them based on their budget and specific requirements. Many of the solutions also offer both incremental loads as well as a complete data refresh that ensures data synchronization between the applications.
Figure2. How to integrate SAP HANA with Google BigQuery : A representation of HCL solutioning
The basic integration process involves the following steps:
- The data retrieved from SAP HANA acts as the data source. This data is integrated with the source Google BigQuery through Google cloud that supports data virtualization. Depending on the volume of transaction, the data can either be processed completely in one go or in incremental batches.
- Data from both the sources is then directed toward the target storage environment.
- Finally, the stored data is processed in the data studio using several business-intelligence tools such as Microsoft Excel and Looker, etc. This processed data can then be accessed by users across enterprises, giving them the required insights to augment effective business decisions.
Address your business challenges with HCL: Industry Use Cases
Integration of SAP HANA with Google BigQuery through pipelines has multiple applications across industries such as financial services, media and entertainment, healthcare, oil and gas, energy, manufacturing, retail, and the public sector. Every industry can leverage this highly integrated business intelligence solution in different ways.
Use cases and benefits
For a financial services organization, SAP HANA and Google BigQuery integration can create a single logical data warehouse through which it connects all the disparate data sources, creates a standardized rule or logic for accessing data, and finally, allows the data to be accessed through several standard interfaces including Open Database Connectivity (ODBC) and Java Database Connectivity (JDBC). This enables the enterprise to overcome significant hurdles such as poor data quality and a lack of transparency, auditability, and accountability, while driving digital use cases and bottom-line impact.
For the e-commerce industry, real-time insights into customer behavior and market trends are critical for business success. E-commerce organizations can easily test datasets, derive deep, limitation-free insights from data, and enhance their attribution analysis models across multiple channels using this solution.
SAP drives supply chain for enterprises who adopt it. This integrated solution can help generate faster and accurate data for insights using SAP along with the Google Cloud Platform (GCP). Supply chain, across industries is going through serious disruption and there is a need for integrated control tower that can alleviate the challenges in an enterprise’s supply chain to ensure business continuity.
A BigQuery-enabled control tower can help an enterprise to proactively identify and resolve exceptions and deviations from business-as-usual issues by combining three interwoven components.
- Insights and decision support platform that monitors transactional data from internal and external sources and automatically separates issues from the mass
- An organization of analytical experts that understand supply chain business issues and have the analytical capability to generate the required insights to drive process improvement
- A revamped way of working that is insight-driven and exception-based, promoted across the supply chain organization and beyond
Figure 3. Google BigQuery enabled Control towers: Ensure supply chain continuity across industries
As a response toward solutioning, HCL Google Ecosystem Business Unit has developed a control tower specifically for supply chain businesses across the industry. This control tower can support the planning and distribution of critical parts across the supply chain by facilitating network management and analytically bringing together demand and supply from various data sources.
The way forward is through innovation
In a world differentiated by technology, it is imperative that such innovations are harnessed to generate business intelligence by collecting, analyzing, and integrating critical business data. It is estimated that the global business intelligence market is slated to grow to $29.48 Bn by 2022 with a CAGR of 11.1%. As the volumes of data keep growing and markets become more turbulent, taking the correct business decisions can define organizational success. It is crucial for organizations across sectors to select an appropriate data integration process with SAP HANA and Google BigQuery integration to generate intelligent, insightful data, and foster efficient and correct decision making.
Visit us to know more about HCL Google Ecosystem Business Unit and how we can help you harness the power of real-time insights through integrated data analytics solutions.