WECO Pyrotechnische Fabrik, a leading fireworks producer in Europe, faced challenges in managing its multi-stage in-house production system and purchasing merchandise from abroad. The company required accurate logistics planning to ensure all branch outlets received their stocks in time for New Year’s Eve sales. The same level of accuracy was needed for planning production and import schedules. For a long time, data analysis was done using Microsoft Dynamics NAV business management software coupled with individually programmed reports. However, this procedure proved to be time-consuming and error-prone. The data was first exported from the inventory management system into various different Excel worksheets and then collated. This process led to errors and could only assess and optimise processes in retrospect.

Wegter, a non-food wholesaler, was facing several challenges. They needed a faster business analysis for their customers and a reduction in the time it took to generate reports on licensing and royalty agreements. Their customers were also demanding more detailed reports on available inventory, delivery schedules, and royalties. The company was using different packages to retrieve data, organize it, and present it, which was inefficient and time-consuming. They were also struggling to meet their customers' demand for a delivery reliability rate of more than 92 percent.

Weir Services, a part of The Weir Group, a global engineering services company, needed an ERP reporting tool capable of delivering quick, executive-level, dashboard views of division operations and finances to ensure optimal performance levels. The company had been sharing an ERP system with the Group’s Weir Pumps manufacturing business and recognized the need to implement its own ERP solution for its various facilities in the U.K, Middle East, and potentially other facilities around the world. The company wanted to leverage the invaluable data locked in its systems from Movex and SAP to its Environmental, Health and Safety system.

Yamaha Music Europe, a subsidiary of Yamaha Corporation of Japan, is responsible for selling Yamaha musical instruments and audio-visual equipment across Europe. The company faced the challenge of harmonizing sales logistics and other data from six European sales divisions. They needed to unify all information into a single BI tool to facilitate cross-selling and upselling across Europe. The company also wanted to offer managers tools for immediate ad hoc query and analysis of data. Prior to the consolidation, the six subsidiaries held business critical information in disparate databases. From a business perspective, Yamaha was keen to improve the potential for cross selling and upselling across the region to take advantage of the growing integration of European markets and the growth of sales via internet.

York Minster, a world-renowned cathedral, is a large organization with around 150 employees and 500 volunteer workers. The operational costs of the Minster are incredibly high, amounting to £9 per minute, 24 hours a day. As a registered charity, it depends on donations and visitors fees to survive. This means that the Minster has had to become increasingly aware of its income streams in order to improve margins and keep reinvesting in its many community and regeneration projects. The IT department is relatively small, with two employees including IT Manager David Wilkinson. Wilkinson also acts as Assistant to the Chief Accountant, and it is this dual role that brought him to QlikView. “When we started charging for entry into the Minster, we needed to be able to analyse visitor trends and tills data. We also wanted to identify where we were improving, especially how much income was coming through from GiftAid and the sale of guide books,” says Wilkinson.

The Réunion Southern Regional Hospital was facing challenges in accessing data from numerous sources and systems. They were using simple single-database query tools which were insufficient to allow users to efficiently access all data. The hospital needed a solution that could integrate data from various different sources and systems, and provide instant access to greater amounts of information in the form of visually rich interactive dashboards, and reports. They also needed a solution that could deliver greater independence and self-sufficiency for users.

Globus, a retail chain of supermarkets, was facing challenges in reducing time to value, consolidating data from multiple unstructured sources, and gaining better insight into ongoing campaigns and promotions to increase the efficiency and profitability of operations. The management information system used by Globus was provided by an external company and was based on static Excel reports published in a web environment. The online reporting system could only use a limited number of dimensions and as a result many decisive processes were based on not completely identical outputs, while some reports were not available at all and many were created by manually copying from various systems into Excel tables.

Health Market Science (HMS) is a leading manufacturer of healthcare provider data in the United States. The company's flagship product, the HMS Provider Master File, includes detailed reference information for over 4.5 million individual practitioners and 1.0 million healthcare organizations. However, the company faced challenges in continuously tracking, integrating, analyzing, cleansing, and packaging millions of records of data from thousands of sources. The company's business analysts depended on as many as three programmers to write SQL code for a new, complex analysis. This process was time-consuming and sometimes led to different answers to a query depending on who was writing the code. HMS needed a solution that would enable business analysts to analyze data without support from programmers and meet requirements without the cost, complexity, and time required by traditional OLAP cube solutions.

IDG Denmark, a business unit of IDG, world’s leading technology media, research, and event company, was facing challenges with data analysis. Their business processes were supported by a Siebel® CRM system and a MBS (Microsoft® Business Solutions) Navision ERP system, which churned out static paper reports. Analysis of data across systems was only possible by manual creation of spreadsheets – a tedious and risky process which provided outdated information. With millions of lines of data to analyze, Excel® exceeded the ability to provide IDG Denmark with the needed detail. The company had limited resources to do this – both on staff and financially. They needed a powerful, yet easy-to-use Business Intelligence tool for interactive data analysis, enabling IDG Denmark to effectively and proactively monitor, manage, and optimize the business.

Laureate Education Asia, a part of the Laureate International Universities network, was facing challenges in financial forecasting and reporting. The process of preparing monthly analysis and reporting at their regional office was time-consuming, taking up to seven hours to run a comparison of financial performance of their different institutions from Oracle Hyperion. They wanted to reduce this time and improve the quality of their reporting. They also wanted to enable their staff to archive their own data and extract forecasts on a self-service basis for quicker decision-making.

Purity Life Health Products LP, a leading distributor of natural health products in Canada, was facing challenges with its legacy system for business data analysis. The system was cumbersome and only a few employees had access to useful and timely data. This lack of data accessibility and transparency was hindering work efficiency and visibility into the business. The company needed a solution that would liberate its data and make it accessible to more people within the organization.

Direct Relief, a global humanitarian aid organization, faced a significant challenge in managing its supply chain. The unpredictable nature of world events and the receipt of products from donors made it difficult to plan and execute logistics efficiently. Furthermore, the organization had to deal with medical products with expiration dates stored in warehouses worldwide. The complexities of shipping times and customs protocols posed a risk of these products being wasted unless Direct Relief could move quickly and maintain full visibility of their supply chain. The data essential for this agility and visibility was trapped in their SAP system, making it inaccessible for effective decision-making.

Medair, a humanitarian organization, was facing a challenge in gathering and analyzing data from the field. They were using Open Data Toolkit (ODK) to collect health and nutrition metrics in the field, which would drive their programming and the work of other NGOs in the region. However, they needed specific analytic visualization to better understand the survey data and respond most effectively with their program work. The potential for impact was enormous, as the data would be used by hundreds of personnel working in the region daily to make better-informed decisions and save more lives.

IHS Markit, a world leader in critical information, analytics, and expertise, was facing challenges in providing effective SAP user support due to the tightly controlled and audited nature of its SAP production system. The system required multiple layers of authorization to access any data, which often resulted in delays before access to production was granted. Prior to implementing Qlik Gold Client, Markit was manually creating, matching, and reviewing a massive amount of information to mimic production data in QA, which was proving to be an inefficient process. The company was looking for a solution that could reduce the excessive use of Firefighter access while still addressing compliance issues.

BITMARCK, the largest full-service provider in the German IT market for statutory health insurance, needed to streamline data integration and enable self-service, real-time business intelligence for its customers. The public health insurance companies use information to measure customer retention and turnover, generate financial reports, manage cash flow, and estimate risk. To support customers’ business intelligence and analytics initiatives, the BITMARCK team routinely had to gather data from several different technical sources and move it into a central target. These data sources ranged from IBM DB2 to MySQL, Microsoft SQL Server, and Informix. BITMARCK had been using IBM Q Replication, but this solution only supported replication between DB2 sources and targets. To replicate data to other sources, the BITMARCK team had to do lots of SQL scripting or use proprietary programs.

DomainPower, a leading real-time bidding exchange connecting online advertisers to rich native advertising inventory, was dealing with a high volume of transactional data from its online auctions. The company recognized the need for a data warehouse to analyze market trends related to its supply inventory and the value of advertising. They decided to explore Amazon Web Services, but the daily source data changes proved to be a challenge. Daily batch data updates between DomainPower’s on-premises Microsoft SQL Server system and an Amazon Redshift data warehouse would not meet the business needs. This represented an obstacle to using Amazon Redshift, since keeping the environments in sync might require significant development effort and ongoing maintenance.

Glidewell Laboratories, the largest dental lab in the United States, faced a significant challenge when they adopted the CAD/CAM Digital Manufacturing standard. The adoption led to a tenfold increase in the amount of data the company had to store and analyze, reaching over 150 million records. To manage this change, Glidewell aimed to create a more responsive, cloud-based infrastructure to support business intelligence and analytics. However, cloud migrations can be tricky, often requiring custom coding that slows down the process, reducing the time-based value of analytics for quick business decision-making. Glidewell's on-premises data storage solution included over 80 separate databases, adding to the complexity of the migration.

Colmobil, Israel's largest importer and distributor of vehicles, was executing several SAP projects in parallel across the company’s SAP landscape. This included migrating two subsidiaries’ legacy systems to SAP, which required updating testing environments to develop new business logic and properly connect all the data. However, creating a new system or refreshing an existing one with updated data for a new project was extremely time-consuming. It could take up to a week of intensive work to complete these tasks. As a result, teams always questioned whether it was worth creating a fresh system or whether they could risk working on an outdated one. Dependence on the Basis team created bottlenecks. The Application team had to rely on the Basis team to refresh a QA or Dev environment. Bottlenecks inevitably led to long lead times to create new environments. It was difficult to recreate erroneous events or research bugs. Discrepancies between the production environment and Dev or QA limited the company’s ability to address issues when they arose. Issues usually appeared in the newest customizations or development work, where the gap between production and Dev or QA existed.

Mercedes-Benz USA implemented SAP Finance and Controlling in 2000, followed by Parts Logistics, Materials Management, Sales and Distribution, and Production Planning in recent years. With five business units running on two instances of SAP, the environment has become progressively more complex. The total SAP system now houses two terabytes of data, with pricing tables alone adding up to 400 million records. The primary issue caused by the refreshes was that they took the non-production systems offline for several workdays in the middle of the week, which would negatively affect ongoing projects. Mercedes-Benz wanted to be able to provide developers with the data they needed for testing on an as-needed basis while reducing the number of full refreshes required per year. The company also wanted to be able to protect version information.

Tangerine, a direct bank in Canada, was looking to become a more full-service digital bank. They wanted to listen closely to their customers and create services that their customers were looking for. This required Tangerine to have access to customer data in real time so they could respond quickly to their needs. As they began this journey, they reached out to their customers to find out what they wanted from a bank. The first step was to develop a responsive website with a user interface that easily adapts to the device customers are using to access it. The next step was to leverage customer data differently. They needed to keep track of customer feedback and complaints, which included every face-to-face and phone interaction with a customer, in addition to social media sentiment. This requirement had Tangerine’s IT team looking at the data in their current data warehouse as well as the expected growth for their data over the next several years. It also had the team looking at the time it took to move their data so that their bank managers could analyze it while the data was fresh.

University of Maryland University College (UMUC) was facing the challenge of organizing and deriving insights from four core datasets, totaling 10 terabytes. These datasets included data related to online student activities, student enrollments, financials, and customer relationship management. The data was stored in a mix of on-premises Oracle and SQL Server databases, Salesforce, and other cloud-based service applications. UMUC’s challenge was to aggregate these disparate data sources, normalize the data, and then load it into a data warehouse for analysis. This was a classic ‘data integration challenge’ that included extracting data from source systems, staging the data in a relational database and applying transformations, loading data into a data warehouse, and running analytics and providing a visualization layer.

PRIMAGAS, a utility company with regional headquarters in Krefeld, Dresden, and Würzburg, was facing challenges in analyzing Oracle data for its subsidiary. The data was analyzed by manual reports in Excel, which was a time-consuming process. The company was under high pressure due to its business operations. The parent company was using another tool which was not suitable for PRIMAGAS's business. The company was dealing with large quantities of data.

Prince William Health System faced several challenges. They lacked real-time visibility into their Accounts Receivable (AR) process due to the outsourcing of management and tracking, coupled with limited reporting. This lack of visibility was a significant issue as it hindered their ability to effectively manage their revenue cycle. Additionally, they were struggling with high write-offs for insurance claims, which was negatively impacting their financial performance. Another challenge was the assessment of physician performance for the contract renewal process. The hospital needed a way to track and analyze physician performance to make informed decisions about contract renewals.

Procurement Lincolnshire, a shared service partnership between eight local authorities in the East Midlands, wanted to respond to the need for efficiency savings by analysing its expenditure in more detail than ever before. They decided to improve its visibility over procurement activity with a new software platform to help meet the budget reduction targets posed by the government Comprehensive Spending Review in 2010. The procurement activities under scrutiny already cover around 30 categories. They range from reviews of high spending services, such as adult social care and children services, to outlays on photocopiers, pest control, and even dog kennelling. The challenge was finding a user friendly dashboard solution to access customised data mining reports for a more holistic view of the organisation spend.

The Office for Computing, Geography and Statistics of the Autonomous Province of Bolzano manages the entire information system and serves 6,000 workstations. Its main client is the Provincial Statistics Institute, which runs provincial statistics analyses. The Office needed to find a user-friendly tool that presents detailed findings and a system that does not require complex technological infrastructures. They also needed to analyze highly complex data combinations efficiently. The Office conducted a study to find the tool that best suits the Provincial Administration’s environment – an agile, customizable tool that would not require complex technological infrastructure and that guarantees good performance.

PT. Kapal Api Global, a manufacturer and distributor of Fast Moving Consumer Goods (FMCG), was facing performance issues when analyzing huge amounts of data (1.5 billion records, 200 million rows). There was a 2-3 week gap needed to prepare analysis, which was affecting decision making. The conventional reporting tools they were using were unable to cope with the huge data sets and frequent user changes to analytical requirements. The company has a distribution footprint that includes more than 500,000 stores nationwide, mostly consisting of small family-owned shops.

Qualcomm, a leading developer and innovator of advanced wireless technologies, products, and services, faced challenges in analyzing the usage of its major enterprise applications. The existing Business Intelligence (BI) tools required up to six months to build each new application, which was time-consuming and inefficient. The team needed a solution that was more rapid and analytically driven to analyze enterprise application usage throughout the company. The search for a solution led Qualcomm Senior Programmer Analyst Steve Rimar to discover QlikView online. He was intrigued by the appealing visual analysis and the ability to rapidly develop new applications.

Radiometer, a pioneer and international market leader for blood gas analyzers, was facing increasing cost pressures and needed to optimize its corporate efficiency. The company was using a complex Excel solution with numerous macros for data evaluation. This procedure was not only error-prone and complex, but it was also difficult to use. In addition, the data volume became too large for such a solution to reliably and quickly handle the evaluations. The company considered adopting an OLAP-based business intelligence solution that was already in use at the parent company in Denmark. However, it quickly became clear that this system also could not satisfy the requirements of Radiometer in Germany.

Region Skåne Habilitation and Assistive Technology Services, a group within healthcare organization Region Skåne, was facing several challenges. They needed to coordinate six different operational systems, improve the presentation of analysis in a visually engaging format, and reduce manual data collection and analysis. The services they provide are based on the principle that all people are equal regardless of age, gender, disability, and ethnic or religious background. They help treat people with permanent disabilities with exercise and assistive technology to enable participation in everyday life. The services are based on each patient’s expressed needs, which change in nature and extent throughout a person’s lifetime.

Reifenhäuser, a leading supplier of machines and manufacturing plant for the plasticisation of thermoplastic synthetic materials, faced challenges due to the changing landscape of the synthetic materials and plastic processing industry. The industry faced demands for plastics to bear the “green dot” to show their suitability for recycling and it’s now necessary to meet even tougher environmental standards to find solutions which are not hydrocarbons-based. The company also had to consider the environmental conditions at manufacturing sites. The company was also facing issues with its previous systems which had failed to provide any comprehensive evaluation of the in-house databases. The costs involved in making even the slightest modifications were prohibitive. Using Excel spreadsheets when working on complex analysis operations was unproductive and the results could not be easily reproduced.