JB Hunt 是财富 500 强公司，也是北美最大的运输物流公司之一，正处于全公司范围的数字化转型之旅中。此旅程的关键部分是实施 Microsoft Azure Databricks 数据湖，以实现数据仓库现代化，从而提高整个组织的效率和数据访问。然而，随着工程和技术团队开始推出，他们注意到作为 JB Hunt 360（其尖端数字货运匹配平台）支柱的运营数据存储面临越来越大的压力。在评估数据管道后，团队确定需要加速数据流入湖中，以确保 JB Hunt 360 用户保持高质量的体验，没有性能滞后。

Atlas Copco Construction Tools, a leading manufacturer of hydraulic, pneumatic, and gasoline-powered breakers and drills, was facing a challenge in extending its product leadership with continuous improvements in product innovation and quality. The company was struggling to consolidate data from a suite of disparate systems and improve the availability, speed, and accuracy of business data. The disparate systems were causing inefficiencies and inaccuracies in data analysis, which was affecting the company's ability to make informed business decisions and improve product quality and delivery performance.

MAPCO Express, Inc., a leading convenience store operator in the Southeast United States, was struggling with inaccurate reporting due to the use of Excel as its only reporting tool. The company had significant amounts of valuable data but lacked the ability to extract meaningful information from it. For instance, it was unable to track customer loyalty trends per store. The timeliness of the data was another issue, with reports taking weeks to aggregate, which hindered efficient business decision-making. MAPCO needed a single source of truth and the ability to see the underlying trends and patterns that led to discrepancies.

Condé Nast, a dominant player in the international magazine market, embraced the digital revolution to engage with its audience in new ways. However, with its new digital applications, Condé Nast soon encountered more data than ever before. Hidden inside that data were key customer trends that could help Condé Nast create content more precisely aligned to customer appetites and seize advertising opportunities with sharper accuracy. Realizing this, Condé Nast began developing business intelligence infrastructure to make smarter use of its data, and it knew choosing the right partners in the digital transformation journey would be key.

Greenway Automotive Group, a Florida-based organization running 46 full-service car dealerships across several states, was struggling with its Dealer Management Systems (DMS). The DMS was designed for single dealerships, making it difficult to compile consolidated financial reports, track productivity and trends, or compare the performance of different stores. The old DMS could only achieve one update a day and had limited capabilities for drilling down on various issues and generating automated reports. This compromised effective forward planning. Greenway wanted an enterprise-wide view and a reporting layer above the DMS that could show trends and market conditions, and where views could be easily customized and modified without having to log into 46 different computer systems.

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.

HSBC, a global bank serving over 40 million organisations and individuals, was grappling with the complexity and scale of its data. The bank recognised the need for a strong commitment to analytics to thrive in the future. However, the challenge was not just about collecting data but making it usable and accessible across the organisation. The bank needed to ensure data quality, make data-driven decisions easier, and enable every staff member to contribute to business intelligence. The sheer size of HSBC and its commitment to data collection and analysis necessitated a simplified approach to data management.

Amcor Limited, a world leader in innovative packaging, was undergoing a significant global operational and strategic review. The company aimed to transition to deliver sustainable shareholder value with a strategy of being more customer and market-focused. This was to be achieved through superior customer service & value, in a manufacturing environment where differentiation is typically focused on driving down costs. As part of this strategic initiative to ‘get fit’, Amcor globally initiated the ‘Value Plus’ project as a means to build sales and marketing excellence. The two main objectives were firstly understanding and improving returns by identifying & capturing commercial opportunities; and secondly to upgrade the sales and marketing capabilities across the company.

De Hypotheekshop, a leading Dutch mortgage advice provider, needed to adapt to the changing financial market environment, which was marked by a recession and new compliance regulations. The company wanted to operate based on up-to-date information rather than gut feeling. They needed a Business Intelligence tool that could be deployed in different ways: standalone, mobile, in the cloud or on-premise. The tool needed to link to multiple data sources, combining the internal data of De Hypotheekshop with third-party data sources from their growing network of franchisees. This would provide users across the network with insights that would have an impact on the business. Additionally, the company faced the demand for transparency and compliance enforced by the Autoriteit Financiële Markten (the Netherlands Authority for the Financial Markets).

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.

At UOB, the traditional approach to data discovery was a per-project process used for regular reporting purposes. Extracting data for these reports was often manual and time-consuming. The reports created were also often one-dimensional and not in real-time as there were limitations when analyzing historical data on Excel files. The bank wanted to make data discovery more accessible, insightful, and relevant to business real-time needs. They also wanted to create a culture driven by data analytics across the organization.

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.

Shoppers Stop, a leading Indian retail department store, was facing challenges with its data analysis process. The company had been using traditional BI tools and Microsoft Excel for internal reporting, but the process was both limited and time-consuming. The team was seeking a new business discovery solution to improve its data analysis with the long-term goal of streamlining business operations and ultimately increasing sales. The company wanted to enable a 'self-service' data analysis model and increase the efficiency of data analysis.

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.

IndianOil, the largest public sector oil and gas company in India, first turned to data analytics with QlikView in 2012. Dashboards were created, mainly for the company’s chairman and directors. During a review of its IT infrastructure, IndianOil identified an opportunity to make more use of the increasing amount of data being held throughout the organization. The company saw the potential of leveraging this data to drive business value across the organization.

Odyssey, a logistics and supply chain management company, was in need of a business intelligence solution that could help them keep up with competitors and add value for their customers. The solution had to be a non-cloud, on-premise solution to allow the company to maintain complete control over the operation. It also needed to be flexible enough to extend into a true 'visibility' platform on the front-end. The company spent almost all of 2016 trying different solutions during the discovery phase of the project, but none of them were the right fit.

Volvo Group, a global manufacturer of trucks, buses, construction equipment, and marine applications, faced a significant challenge in managing its complex material flow. The company had to connect with the right suppliers for the right spare parts and find the most efficient way of getting the right parts to the right trucks at the right time. The company's existing tools, such as MS Excel, were inefficient and left a lot of room for error. The team spent an excessive amount of time gathering data and making it understandable and presentable. This inefficiency led to a culture where teams and individuals quickly became siloed, missing out on opportunities to improve workflows or identify suppliers whose products weren't up to standards.

CSC Financial Co., Ltd (China Securities) needed to better understand asset movements in real-time to maximize investment strategies. It also wanted to provide its clients with a real-time display that would clearly show the status of their portfolio from the China Securities application and other investment channels. The company had to deal with large data volumes and many databases which required up to 18 replication tasks. Frequent system upgrades also meant that replication environments had to be constantly rebuilt and replicating from heterogeneous databases was a cumbersome operation.

Ecenarro, a Spanish manufacturer specializing in the production and supply of fasteners and special parts for the automotive industry, was struggling with its legacy business intelligence system. The data to be analyzed was exported from the enterprise resource planning (ERP) system to Excel spreadsheets and then processed manually to obtain the required results. This process was time-consuming and inefficient, often resulting in the data being outdated by the time it was ready for analysis. The company needed a solution that could provide immediate access to key performance indicators and other critical business data.

ThedaCare, the largest healthcare provider and employer in Northeast Wisconsin, was facing challenges with its existing reporting systems. The systems were becoming cumbersome and not user-friendly. Ad hoc requests required end users to have IT develop the report. The process could take days to answer business and clinical questions—a situation worsening with increasing data volume. With 43 customer sites, 5400 employees and a commitment to improve healthcare value for its employer plan purchasers and 225,000 patients annually, ThedaCare needed to upgrade its reporting tools—but not at the high capital investment in server hardware and software licenses that its existing dependence on SAP Crystal Reports would require.

TVH experienced rapid growth due to several successful takeovers, leading to a significant increase in data volume. Their existing reporting system, which relied heavily on Excel, was unable to handle the increased data load, resulting in slow processing times and a lack of clear overview. The company was using multiple data sources, including AS400, Oracle, and Progress, which further complicated the situation. The old system lacked flexibility and was unable to make necessary links, leading to insufficient collection of sales, customer, and item-related information. There was an urgent need for a new reporting system.

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.

Gazprom Neft, one of the top three oil-producing companies in Russia, was facing challenges in making data-based decisions due to the lack of a robust Business Intelligence (BI) unit. The company was already a year into their journey with Qlik, a data analytics platform, when the BI Department Head joined in 2013. The task was to further develop the internal Qlik-based processes. However, the allocation of resources was a major challenge, especially server resources. The company was also not always on schedule in the purchasing of new equipment. Change management was another challenge, particularly overcoming internal resistance without clear signaling from company leadership.

Quooker, the creators of a tap that produces boiling water almost instantly, has been experiencing rapid growth, with a 100 percent increase every three years. To sustain this growth and expand operations across a complex global market, the company needed more precise forecasting and analytics tools.

The Chinese Academy of Agricultural Sciences (CAAS) is a national innovation center for agricultural IT. It monitors agricultural information, risk analysis, food safety, and data acquisition. CAAS is in the process of refining big data for smart agriculture through its own application. The application handles heterogeneous data resources from a variety of data sources including local governments, commercial databases, and Internet of Things (IoT). However, the business intelligence (BI) products previously deployed by CAAS were seen as inadequate. They were generally limited to static data analysis and visualized representation, making it difficult to fulfill in-depth data interaction and analysis. CAAS wanted more specialized and powerful functionality. With such a huge volume of data, CAAS was concerned about performance load.

Borealis, a global chemical company, was struggling with the efficient management of its procurement process due to the vast amount of data originating from different sources. The company used standard tools for business analysis, but these could only produce static and pre-defined reports. With data volumes growing and new data sources constantly coming on stream, Borealis found it difficult to obtain actionable insights from its analysis. It needed a new analytical platform that would support informed decision-making across the global procurement organization.

Austin Fire Department (AFD) was facing tough economic times and needed to identify ways to increase efficiency and effectiveness of operations in order to streamline spending and improve services. The department collected high-level annual performance measures, but daily operational data was spread across multiple divisions in different data sources. AFD lacked a useful tool for extracting or integrating it efficiently. The department began the search for a Business Intelligence (BI) solution.

Newham University Hospital NHS Trust (NUHT) was facing challenges in managing information in a responsive manner. The process of collecting and analyzing data for monthly board papers, setting out KPIs and performance, was lengthy and inefficient. The Trust needed a system that could facilitate instant decision-making in an environment where even the smallest changes can have a huge impact on patients’ lives. For instance, if there was a sudden rise in demand for a certain medical procedure affecting operating room availability, the decision-makers couldn’t wait until an end of month report to analyze what could be done about it.

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.

Royal Jordanian Airlines, the flag carrier of the Hashemite Kingdom of Jordan, was struggling to manage the increasing volumes of big data in its Oracle system. The airline needed a better understanding of the business, which required detailed data on many aspects of operations, including fuel consumption, cabin and cockpit functions, mail and courier traffic, and catering costs. The airline relied heavily on Microsoft Excel spreadsheets for business discovery, but pulling data from disparate sources was time-consuming and required dedicated IT resources. It took the airline almost a month to aggregate data for a static report and then process the data. Given the highly competitive nature of the aviation industry, Royal Jordanian required a cost-effective business discovery platform that was sensitive to changes in market conditions.