Qlik Expands Google BigQuery Solutions, Adding Mainframe to SAP Business Data for Modern Analytics

Many mission-critical business applications continue to run on mainframes. It's the backbone of many global enterprises including the financial sector, manufacturing and the public sector. However, with increasing reliance on mainframes to run these businesses, costs are increasing too, including those for hardware, licensing, and MIPS (millions of instructions per second) usage.

In addition to the increasing costs of just running existing mainframe workloads, it's becoming increasingly difficult to innovate on a platform with a dwindling skill set. And being locked into a legacy platform prevents organizations from accessing the innovations taking place in public clouds.

That’s where Qlik’s mainframe modernization approach can help. Qlik, in partnership with Google Cloud, addresses business imperatives and challenges from legacy platforms and helps organizations embark on new digital journeys. Mainframe modernization provides exponential benefits to organizations by increasing business agility and operational efficiency. This drives high business growth and the adoption of newer business models while reducing software, hardware, and operational costs and minimizing risks from shrinking talent pools and dated technologies.

Qlik augments Google Cloud's data-modernization approach to help organizations unlock mainframe data and move it to the cloud so you can get more value without impacting important mainframe workloads. You can retain mainframe infrastructures while building out use cases such as offline queries with a modern data platform and take advantage of AI/ML and cloud capabilities as well as API technology.

Qlik can help organizations leverage repeatable analytics solution accelerators by delivering real-time data from SAP and other data sets into a consolidated enterprise data warehouse with built-in data cataloging capability. Additionally, organizations can combine data from everyday business processes such as financials, inventory management, procure-to-pay, and order-to-cash with other cross-enterprise data sets for advanced insights. Organizations also benefit from predefined operational data marts, change data processing, and machine learning templates for common business scenarios as part of the Google Cloud Cortex Framework.

The latest Qlik innovations and the growing market embrace of active intelligence has facilitated real-world developments of best practices while deploying Qlik alongside Google Cloud. Here are a few standout successes earned through the combined implementation of Qlik with Google BigQuery:

• Luxury department store Breuninger is one of Germany’s most successful fashion and lifestyle businesses. This 140-year-old company prides itself on delivering excellent customer service while protecting and growing market share. Breuninger lacked end-to-end visibility of processes and data due to a fragmented tech stack throughout the company. They chose Google Cloud BigQuery for quick access to data for analysis. Qlik consolidates and delivers SAP data in near real-time, at scale, to BigQuery. Now they have faster data analysis and high-speed reporting across the business, enabling greater insights into business activities, resulting in immediate cost savings and a scalable ROI.
• Gordon Food Service is one of America’s largest family-managed food service businesses with more than 170 stores, dozens of warehouse distribution centers, and a delivery network covering food service operators east of the Mississippi River in the USA and coast-to-coast in Canada. As data volumes grew, it became increasingly difficult to free the data and act. Gordon Food Service chose Google Cloud because of its machine learning, AI, and analytics capabilities and Qlik to populate it with data. Gordon Food Service’s cloud data pipeline now incorporates over 12 TB of data from six SAP environments, 50+ subject areas, and 900+ tables, reducing the time to act on insights, going from a data latency of over 24 hours to a few minutes.
• In 2020, Jaguar Land Rover (JLR) sold 425,974 vehicles in 127 countries. However, the COVID-19 pandemic disrupted many supply chains, global chip shortages threatened to impact production, and the need to produce electric cars brought increasing demands. Jaguar Land Rover has adopted DataOps methodologies, created a 2 PB data lake in Google BigQuery, and implemented Qlik to feed IoT, streaming, and batch data from various sources — including mainframe and SAP — into the lake with near real-time delivery. Taking this approach resulted in JLR quickly responding to the regulatory demands of global markets, including warranty safety recalls in North America to VAT submissions in the UK. JLR is also looking to expand its use of other solutions within the Qlik Data Integration and Data Analytics platform.

Learn More.

Together, Qlik and Google Cloud drive value and innovation for enterprises with SAP and mainframe that help you get the most out of your investment. To learn more, visit the Google Cloud Migration & Data Transfer - Google Cloud Platform | Qlik page or request a demo.