Bentley Motors, a globally recognized luxury car brand, was facing a significant challenge in the wake of the automotive industry's unprecedented changes. The company, known for its bespoke luxury cars, realized the need for a transformation to ensure its long-term success. This transformation was not only about switching to an all-electric portfolio of vehicles by 2030 but also about implementing effective digital transformation throughout the company. The goal was to streamline operations, improve customer service, and solidify Bentley's position as a global automotive leader. The company also aimed to enhance its customer experiences, which are a key hallmark of Bentley, through a more data-driven approach. However, the challenge was to find a solution that could help them achieve these goals.

Before the implementation of Tableau, OptumHealth was struggling with managing and making sense of data from various sources. The company had different silos of reporting teams, data sources, and separate spreadsheets. This made it difficult to get a holistic view of operations and address customer issues promptly. The company was also facing challenges in tracking its various distribution partners and independent brokers. The spreadsheets used for this purpose were unmanageable and not very useful, providing little value to the sales team.

Clintel identified a growing need in drug development: enabling clinical development organizations to comply with FDA draft guidance on risk-based monitoring principles. They saw the potential to develop easy-to-use tools that could also improve quality and significantly reduce costs. The FDA advocates alternatives to regular, frequent onsite visits and verification of all data, which involve costly travel and provide little added benefit. Instead, they recommend approaches that identify risks to patient safety by utilizing critical data elements gathered in clinical data systems as a method of determining which sites warrant additional attention from clinical research associates (CRAs). The problem lies in getting that information to the right people at the right time, and in their language. Despite these issues, spreadsheets have become the default report technology for many business users because they have simply had no other option.

Nokia, a leading global supplier of mobile phones, telecom networks, and related customer services, was struggling with the vast amount of data they had. They needed a way to analyze and understand this data to guide their product development and understand their customer base better. The data was locked up in various databases, and the tools they had at their disposal, such as Excel and PowerPoint, were not sufficient for the task. They needed a tool that could handle large data sets and provide insights quickly and efficiently.

The University of California, Irvine Medical Center was struggling with the challenge of understanding and presenting their vast amounts of data to the community. They had spreadsheets, Access databases, and were on the path to a data warehouse, but they lacked a tool that could effectively visualize this data. They needed a solution that could work within their current environment and also in the future. The IT department did not want to be the report writers and wanted a self-service model where the people who knew the data could develop their own visualizations and reports.

BMW Group Germany, one of the largest commercial enterprises in Germany, was facing significant data challenges. The company was dealing with multiple data sources, databases, and in-house systems, making it difficult to collate, analyze, and visualize information effectively. Employees were conducting their own isolated analytics and reporting, leading to data discrepancies. The senior leadership team recognized the need for a unified analytics platform that would provide a 360-degree view of data, support data-driven decision-making, and foster cross-functional synergies within the company.

Dun & Bradstreet, a global company with over 6,000 employees and 4 million customers, was looking for a way to visualize their data to provide new offerings to their clients. They initially used Tableau to acquire a major client who wished to visualize their data. However, they soon discovered that they could also visualize their own data using Tableau, creating a synergy between client data and company data. The challenge was to dig deeper into the data and extract valuable insights that could be beneficial for their clients.

Supervalu Inc., one of the largest grocery and pharmacy companies in the United States, was facing numerous challenges and was in a state of turnaround. The company recognized the need to look at their data in new ways and seek out opportunities to improve efficiency, productivity, and revenue. They required an agile business intelligence tool that could support mobile data access to improve day-to-day operations, align the organization around a single, comprehensive view of data, quickly define and iterate on new metrics, draw simultaneously from multiple in-house and third party data sources, assess data opportunities without extensive up-front IT investment, and accelerate the work of analysts and business users with self-service functionality. Before Tableau, Supervalu had ten different business intelligence tools. Their primary tool was unable to build new reports rapidly or iterate in a timely fashion. It was also unable to reach into disparate data sources and create mash-ups without significant IT overhead and complexity.

Silvaris, a leading wholesale provider of industrial wood products and surplus building materials in North America, needed a real-time view into its data without having to move the data into a separate reporting format. The company works with rapidly fluctuating prices and large volumes of materials, making it crucial to have a system that can handle these variables. Silvaris had developed a proprietary online trading platform to manage transactions and share data with customers and partners in real time. However, the company needed a more efficient way to visualize and analyze this data.

Sveriges Television (SVT), the largest television channel in Sweden, was facing challenges in analyzing television viewing behavior in Sweden. The Audience Research team at SVT was tasked with monitoring television-viewing behavior to make better decisions on how to air programs. They were using Excel for their analysis, which was time-consuming and lacked the ability to perform in-depth analytics due to the manual work involved. They were also struggling to communicate their insights effectively with the executives who make programming decisions. The team needed a solution that could accelerate their analyses and improve their communication with the executives.

Ernst & Young's Fraud Investigation and Dispute Services (FIDS) practice works in a broad spectrum of providing analytical services related to identifying factors related to fraud and forensics. They analyze all types of fraud that can be coming from all types of different data sets, whether or not those data sets are transactional data in form. They also try to uncover elements of unusual patterns or unusual behavioral activity within unstructured data sets of text data – such as emails, instant messages, or SMS text messages that are exchanged in an organization from employee to employee. The challenge was to analyze these large volumes of data and present the results in a way that is easily understandable by a variety of individuals across an organization—from analysts and end users right up to C-suite professionals.

AREVA Group, a renewable energy company, was looking for a tool to help present data to their executive committee. They needed to analyze and visualize data to strategically meet the demand for delivering more wind turbines. The initial project that Tableau helped them to analyze was the production of 100 windmills a year at their plant. They needed to know when a 2nd and 3rd plant would be needed. They asked themselves when should they build? Where will they build? How many jobs will they create?

Anadolu Sigorta, Turkey's first national insurance company, was facing challenges in identifying and investigating fraudulent claims, a process that was extremely time-consuming and detracted from their ability to serve genuine claims efficiently. The company was dealing with disparate data sources, legacy systems, and manual work processes, making it difficult to identify and eliminate fraudulent claims. Additionally, as a 95-year-old company, Anadolu Sigorta had many legacy systems and applications throughout the business, creating a fragmented ecosystem that was hard to work with. They had multiple production environments for the same process, leading to problems with data quality, reliability, and effective governance. The company also faced cultural challenges, with employees and external distributors resistant to modern data visualization trends.

Belcorp, a Latin American beauty corporation, faced a significant challenge due to the COVID-19 pandemic, economic turmoil, and drastic changes in consumer behavior. The company, which operates in 13 different countries, had to rethink its line of beauty products and business model that had been in place for the past 53 years. The pandemic also posed a challenge to Belcorp's traditional direct selling model, as face-to-face interactions were no longer possible. The company had to quickly adapt to these changes and find a way to continue its operations and maintain its growth. The challenge was not only to survive the crisis but also to take advantage of it and transform the business to become more digital and consumer-centric.

The Dallas Cowboys Merchandising division, led by COO Bill Priakos, was in need of a more comprehensive view of their data to increase profitability. Microsoft was chosen as the platform for this upgrade, along with several other sales, logistics, and ecommerce applications. The Cowboys anticipated that this new information architecture would provide the necessary analytics and reporting. However, this was not the case, leading to a search for a robust dashboarding, analytics, and reporting tool to fill this gap.

FINN.no, Norway's largest online marketplace, was struggling with a fragmented assortment of business intelligence (BI) tools, including spreadsheets. These tools provided a narrow view of intelligence into advertising sales, unique users, and other metrics, but couldn't provide a holistic view of the business. Reporting was primarily an IT department affair: business users would request reports and wait sometimes days for the results to arrive. The company needed a solution that would allow for ad hoc reports, standard, drill-through reporting on KPIs, and self-service reporting for their customers.

The Analytics Group at Rosenblatt Securities is responsible for collecting, analyzing, and interpreting customer trading data. They needed to quickly examine hundreds of thousands of trades, compare those trades to multiple client-specified benchmarks and proprietary measures, highlight outliers and areas for continuous improvement, and prepare a summary for download into intuitive, graphical reports for its clients. The key challenge was to find an application that enabled iterative, visual analysis of thousands of data fields. The group searched for an effective front-end application to perform data analysis and reporting. Compatibility with existing tools such as Microsoft Excel and MySQL was critical.

Irish Life, a market leader in Ireland for life, pension, and investment plans, was facing the challenge of managing its business amidst a worldwide economic recession. The company needed a way to gain fast insight into the business to help business owners understand patterns and trends. They needed a solution that could provide visualizations and trend lines across finance, HR, sales, and customer service. The company was also looking for a way to distribute information to regional sales managers and across the company.

Valyoo, an e-commerce company based in New Delhi, India, was facing a challenge with its reporting efficiency. The company, which operates four different online shopping sites, was experiencing rapid growth and needed a way to keep up with increased reporting demands without having to hire additional staff. The analytics team was using Microsoft Access and Excel to meet reporting needs, but the demand was quickly outstripping what the team could produce using these tools. For a typical request, the team would pull data out of the Microsoft SQL Server database and then create pivot tables in Excel. This process was time-consuming and inefficient, with the team spending approximately four hours per day building these repeated reports with fresh data. The company needed a solution that could improve this process and help managers make decisions faster.

Informa, a large company with about £1 billion in revenue, is the world's largest events and conferences business. The company delivers in-depth proprietary market intelligence, real-time news content and analysis, bespoke consulting services, industry events, and specialist online training in nine industry sectors. However, the company faced a challenge in delivering data from spreadsheets and databases to customers easily and cost-effectively. The traditional method of delivering slides and spreadsheets required customers to build their own reports from the data. Furthermore, customers were not fully aware of the extent of data that they could leverage from Informa.

Ferrari and Maserati of North America were facing challenges in their data analysis process. The process of generating and sharing reports for retail sales analysis, service and repair orders, and monthly expenditures was time-consuming and involved manually entering data into Excel files and distributing that static information via email. This method was not only inefficient but also did not allow for real-time interaction with the data.

Belcorp, a leading beauty and cosmetics company in Latin America, was facing a challenge in its business intelligence model. The company was struggling with a high demand for business cases and was seeking solutions to empower its business areas and generate immediate responses to questions that previously took weeks to address. The traditional BI model was not serving the company's needs, and there was a need for a tool that could introduce the Self Service BI concept at Belcorp. This was part of the digital transformation initiated by the company's CTO & CDO, Venkat Gopalan. The company was also looking to involve its business areas in the selection of the new BI tool, a first in the company's history.

Bridgestone Sales Thailand, the local trading business for Bridgestone, was facing challenges with its data analysis process. The teams were heavily reliant on spreadsheets for data analysis, which had its limitations. The process was time-consuming, taking two to three hours to extract insights from data. The data had to be consolidated from different sources, including Bridgestone’s ERP, which added to the complexity and inefficiency of the process. The company was in need of a solution that could streamline this process, make it more efficient, and enable informed decision-making in line with the corporate philosophy of Bridgestone.

Pandora, the leading internet radio service, wanted to increase its use of data to drive business decisions. However, the company’s many silos of data storage created barriers. Only a few people knew how to write scripts to query the data, which meant most people couldn’t get the information they needed to make better decisions. Pandora had dozens of data analysts on staff, but their time was being used running reports instead of providing higher-value analysis. Pandora’s dramatic growth made enabling data-driven decision making a high-priority project.

Stardoll, a Swedish online community for girls who love fashion, faced a significant challenge with data management as its user base grew. The company had a wealth of data about its users, their preferences, and their behaviors, but extracting meaningful insights from this data was a slow and labor-intensive process. Traditional reporting methods, such as spreadsheets or HTML tables, took up to three days to produce and were often outdated by the time they reached the decision-makers. This delay in data reporting hindered the company's ability to make accurate and timely decisions, adapt its services, target new audiences, and increase revenues.

National Financial Partners (NFP) faced a significant challenge in monitoring and analyzing policy processing response rates for over 1,000 open cases. They needed to measure and report the performance of its insurance carriers to improve operational efficiencies and increase customer satisfaction. The Accounting Department was tasked with processing thousands of commission payments to its brokers. Its primary focus was to identify anomalies based on expected values and historical data. NFP was seeking an effective front-end application for data analysis and reporting. Compatibility with Microsoft SQL Server and Excel was critical. PowerPoint integration was also required due to the number of presentations that are given to company executives and to its insurance carriers. The primary evaluation criteria for the application were: (1) it had to be visual and easy to learn, (2) it had to be deployable without servers, IT consultants, and a long implementation cycle, and (3) it had to snap into the existing IT infrastructure.

The online retailer experienced a significant jump in revenue growth, which doubled. However, the cause of this increase was unknown, leading to concerns. The company had to analyze various factors, including the events in a typical conversion funnel, to understand the reason behind the revenue spike. The traditional conversion funnel elements were not applicable in 2008, and it was discovered that revenue was growing because people were buying higher-priced items. The company then sought to determine the root cause of this increased revenue per unit.

Kaleida Health, the largest health care provider in Western New York, was struggling with traditional reporting tools that were inadequate for handling its large data sets. The company needed a BI tool that could process large amounts of data quickly and efficiently. The existing Oracle Reporting system was found to be clunky and unfriendly, making it difficult for non-technical staff to interpret reports. The result was that important data often went unnoticed. The company wanted a solution that could provide users with reports they could understand and interact with.

Omega wanted to provide data visualization and analysis capabilities to its clients using data from Omega Legal’s finance and time tracking system. Omega sought an analytical software capability that could give its clients a more in-depth and interactive way to analyze their data than ever before possible, enabling users to quickly identify trends, make comparisons and focus on exceptions that may be affecting their firm’s overall performance. But they also wanted to deploy the solution in a fraction of the time typically required to build such capabilities from scratch.

The Epidemiology Department at the Louisiana State University Health Sciences Center- School of Public Health collaborates with hospitals and other providers around the state to meet the requirements of a grant from the Centers for Disease Control and Prevention. The grant funds the school’s Louisiana Breast and Cervical Health Program (LBCHP) to fulfill its mission to ensure that uninsured and underinsured Louisiana women have access to and receive high-quality screening and diagnostic services for the early detection of cancer. The challenge was to identify outliers for quality control and to improve program performance.