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The Movember Foundation, a charity focused on raising awareness for men's health issues, has grown into a global movement with offices in Melbourne, London, Los Angeles, and Toronto. The foundation fundraises in 20 countries, and its engineering team has to deal with the complexities of multiple payment gateways and localization issues. The team releases enhancements and new features every two weeks, and as part of their Scrum agile workflow, they need to ensure their endpoints are returning the expected responses. The team also supports a wide portfolio of investments in men's health programs, including clinical registries, health education, and recruitment for research trials.

Microsoft Education, a new team within the multinational technology company, Microsoft Corporation, was tasked with developing APIs for the K12 and higher education market. These APIs were designed to facilitate tasks such as homework assignments, rostering, and classroom notebook use. However, the team faced a challenge in setting up robust integration testing for their APIs. They needed a solution that would allow them to release new changes to production with confidence and efficiency, despite their small team size. Additionally, they wanted to have ultimate control over their tests and integrate them with their own source control.

Trucker Path, a logistics platform that connects carriers, shippers, and brokers in a single marketplace, needed a reliable security solution to ensure the safety and security of its fast-growing volumes of partners’ data. The solution had to protect both applications and APIs from OWASP Top 10 threats. Trucker Path deals with time-sensitive business-critical information, both from their broker partners and from their mobile application users. Therefore, it was crucial to have a strong security solution in place to make sure their data is safe and secure.

Her Majesty’s Land Registry (HMLR), the UK government department responsible for recording 25 million ownership titles on lands and properties valued at over £7 trillion, was facing several challenges in the real estate market. The existing process was cumbersome and costly, with high minimum tickets for investment, multiple dislocated parties and expensive intermediaries required for transactions, and low levels of transparency. The secondary markets were isolated and continued to rely on manual processing. Individuals and companies seeking to participate in the real estate sector had to rely on agents to manage the owner registry, transaction, and administration. This process was inefficient and added multiple layers of cost and friction.

Audi's Strategic Planning team was facing challenges with data analysis. The data was being accumulated faster, in greater quantities and in more diverse types than ever before in history. The current data analysis processes were inefficient and often ineffective. Data was scattered & fragmented, typically in many different places. Analysts were spending more time pulling data, transferring it into excel and then graphing it in neatly formatted powerpoint slides than exploring the data and actually analyzing what it means. There was a clear need for tools to empower data analysts, managers and executives - not IT - to explore and self-serve their own advanced data visualizations.

Clear Channel Outdoor, one of the largest outdoor advertising companies in the US, was facing several challenges. The company was dealing with unreliable business location data, which was previously addressed by licensing expensive, static datasets and geocoding addresses copied from websites. Additionally, the company's reports were constantly out of date and lacked visual appeal. These reports displayed all of the company's assets that affected each state and congressional district. The previous solution was an expensive, infrequently updated, and often incorrect report. Lastly, there was a resource bottleneck as the GIS Manager was the only person in the department with Alteryx, making the report unavailable if he was not present.

Delhaize America, a part of Delhaize Group with food supermarkets in 6 countries, was spending $1.5M/week on Sunday flyers. The company wanted to test the effectiveness of these flyers and determine whether they were providing a return on investment. The challenge was to conduct a test in a market representative of all Food Lion stores, where the test market would not receive a Sunday flyer. The company needed to understand the business reasons for the test, define criteria for success and failure, align on dates, stores, products that are involved, and identify blackout periods and other business initiatives that could potentially impact the test or control results.

Blend and Batch, a retail company, was facing challenges in generating store-level reports showing geographic sales trends, competitive impacts, and demographic summaries. They needed an accurate baseline for predicting new stores and remodels, which required block group-level sales, market share, and percent of store sales. They also needed to combine data sources to delineate a trade area and group stores to provide trends to measure performance. The company was using a combination of T-Log data from front end point-of-sale, MapInfo for geocoding, and MS Access for data calculations. However, this process was time-consuming and required manual steps.

Delhaize America, a grocery retailer with over 1300 stores across the Eastern USA, was facing challenges in various strategic areas including operations, supply chain, new site location, real estate, and marketing. The company was struggling with data discovery, report generation, handling ad hoc requests, mapping, spatial analysis, and querying databases. The process of trade area report creation was long, complex, and expensive. The company was also dealing with issues of replicability and continuity, with the output varying from run to run and difficulties in maintaining continuity with new staff.

GameStop, a $9B Specialty Retailer with operations in 14 countries, was facing several challenges. The demand for analysis was greater than the throughput, and the complexity of analysis requests or business questions was increasing. IT resources were constrained for reporting and data manipulation. The company needed to increase throughput, capability, and decrease dependency. They needed to reduce the need for complex coding (SQL), reduce time spent on repetitive tasks, and share analysis products and procedures across the team. They also wanted to focus on the problem, not manipulating data, provide insight versus analysis results, and increase analysis capability and skillset. Lastly, they wanted to remove IT from basic tasks such as reporting and data loading.

Hyatt Corporation, a global hospitality company, was facing challenges in increasing its corporate sales, which contributes to over 60% of revenue for its full-service hotels. The business environment was dynamic with high competition, long sales cycles, and complex customer relationships. The company was looking for ways to target and expand its share of the business. The challenges included limited customer insights, no global ranking, manual data extracts, and long durations for data refresh and ad-hoc analysis.

The national retailer of modern American-made home furnishings and accessories was facing challenges in understanding when to grow, how to grow, who to grow, and where to grow. They were struggling with identifying the right time in the buying cycle to introduce consumers to their brand. Their customer acquisition strategy was not data-driven, leading to an undifferentiated approach where all customers were treated the same. They were also unsure about their future consumer and how to reach them. Lastly, their retail expansion goals were not aligned with their customer acquisition and development strategy.

Ryder System, Inc., a leading provider of fleet leasing and maintenance, dedicated transportation, and supply chain management solutions, was facing several analytic challenges. They had an in-house analytics team of over five people, but there was no centralized data source. The team heavily relied on IT, resulting in long lead times for project completion. They were using various CRM systems that collected product line information on customer transactions, contacts, prospects, and pipeline opportunities for analysis. However, blending Salesforce data with other data sources was labor-intensive and sapped analyst productivity. Incorporating advanced analytics and visualizations complicated the process even further.

Sally Beauty, a global retailer with 3,673 stores worldwide, was facing challenges with its customer relationship management (CRM) and marketing analytics. The company's reporting was done in Access and Excel, and the transactional and customer data was not in a central location. The sales/transactional data was pulled from an application that did not support ad hoc reports and was no longer supported by IT. The company relied on IT to pull flat files for customer level analysis, which took days to weeks. Campaign data was not stored for performance trends or historical view, and month-end reporting took 2-3 weeks to pull all data and analyze.

The Toronto Star, a leading Canadian newspaper, was facing challenges in managing and analyzing its vast data resources. The company was using a variety of tools including MS Access, MapInfo Professional, and Tableau, but was struggling with data fear due to the potential for errors and the resulting legal implications. The company was also looking to improve its advertising targeting and circulation planning capabilities, and to support data-driven journalism. The existing tools were not providing the flexibility, speed, and ease of use that the company needed.

In early 2017, SCAN, a non-profit Medicare Advantage organization serving California, started receiving reports from members about receiving unwanted Lidocaine ointments by mail. This scheme had started affecting the industry in 2015, but had not yet impacted SCAN at a significant scale. The challenge was to identify the source of this scheme and stop it from further affecting the members and the organization financially. The Special Investigations Unit at SCAN was tasked with investigating these allegations that might have an adverse financial or compliance impact on members or the program. The team had to figure out the chances of one member being served by many pharmacies, dozens of members going to the same pharmacy outside California, every patient getting the same high quality, and several pharmacies sharing the same address.

The Colorado Hospital Association (CHA) was facing a significant challenge in the form of the opioid epidemic. Opioids, traditionally used to treat pain in the emergency department, were contributing to prescription abuse and serving as a gateway to illegal drugs. According to data from the Colorado Department of Health Care Policy and Finance, one Colorado resident died every 36 hours from overdose in 2015. From a data perspective, the situation was messy. The CHA needed to join emergency department data with claims base data to see what was happening across hospitals. Each question seemed to lead to another, creating a complex and challenging situation.

The team at Continuus Technologies identified a need for a search engine that could provide information about National Parks and Monuments based on a user's location, the features of the parks, and the expected weather conditions. Existing solutions, such as the National Park Service's 'Find a Park' feature, only provided state-level location information and did not offer accurate or updated weather forecasts. Google Maps' success varied depending on the quality of data in each zip code, which was inconsistent. The team sought to leverage their expertise as Alteryx Partners, data enthusiasts, and conservation advocates to create a solution that would empower others to preserve and admire the United States' natural resources.

Montgomery Transport, a transportation company based in North America, was facing challenges with their reporting process. The process was time-consuming, requiring three to four days of manual data entry. The company was looking for a solution that was easy to set up and effective at driving change quickly. They wanted a solution that could free up time for their team and publish to Tableau Server so that their executive team could get easy access to insights.

SEGA Games Co., Ltd. was facing a challenge with their promotional mailshots. The emails were sent to lists that had been collected over time, resulting in customers often receiving irrelevant content. This led to high unsubscribe rates and low hit rates. To address this, the team wanted to manage multiple datasets including gameplay data, customer histories, marketing and finance insights to improve analysis and reporting. They had implemented Amazon Web Services (AWS) to extract live data from game titles as they’re being played. However, they wanted to take this a step further by linking to other sales and gameplay data that was spread across numerous sources.

Brookson, a financial services company, was facing the challenge of automating the financial and tax advice being provided by their accountants. The goal was to provide real-time advice that is a capability beyond the reach of traditional accountants. The company recognized that they couldn’t teach their traditional developers accountancy, but knew that through Alteryx, they could get experienced accountants to execute advanced analytics.

Honda was focused on commercializing services that create new value through the visualization and analysis of a huge volume of location data. They were developing BtoB data analysis services based on motion data captured from Honda’s own car navigation system, Internavi. However, they faced issues with processing time series location data with a time history. The huge volume of data stored in the cloud data was not being fully coped with, not only with Excel but even with BI tools.

The University of Nottingham, one of the UK's largest universities, needed to forecast its student population and the related income each year to allocate departmental budgets. The planning and performance team was responsible for collecting and analysing up to nine million records of data on thousands of students across the globe to model expected student numbers and activity accurately. However, with 56 departments requiring deep levels of analytical granularity and five-year forecasts, calculations were complex. By 2015, the team desperately needed a more dynamic student planning model that would allow increased granularity and subsequently improve decision making, whilst working alongside Tableau’s data visualisation. The task would be to handle all reporting for student planning and forecasting as well as verifying data for HESA (Higher Education Statistics Agency), the body that collects quantitative data about higher education in the UK.

Birmingham City University is required to make mandatory annual returns to the OfS (Office for Students, previously HEFCE) to verify its government funding allocation. The Planning and Performance Department must pull together information from several internal systems and external sources to complete the aggregated funding return of student activity. Amassing and preparing the data from multiple sources is a significant, sizeable and complex challenge; with regulatory timeframes for the HESES return generally imposing a 7 working day turnaround from the census point of 1 December. Improving automation and underpinning processes became increasingly important both for securing efficiencies and for maintaining high levels of data integrity. It is essential that legitimate changes compared to prior years are clearly and accurately demonstrated, as this has the potential to affect the university’s core funding grant.

Symphony Care Network, a healthcare provider with 34 care facilities, was facing a significant challenge in tracking the exposure and treatment of COVID-19 among its patients and employees. The existing systems did not provide a consistent way to track this critical information, leading to inefficiencies and potential gaps in care and safety measures.

The Siemens Gas and Power Division launched a productivity offensive for power plant service in 2016. The objective was to analyze areas where unnecessary costs, such as excessively high material expenses, could be prevented. With several thousand various measures, more than 5,000 different data sets, and over 8,000 employees in the business unit, the investigations were complex and time-consuming. The analyses were nearly obsolete by the time the results were available. The first step was to switch to Tableau to improve the visualization. However, the actual problem with the time-consuming and complicated provision of data was still not solved.

SKOPOS, a technology company based in Europe, was seeking a solution to prepare, enrich, and model data for visualization in Tableau. The goal was to help its team visualize survey data in a more efficient and effective manner. The company was dealing with a large volume of data, over 2 million survey responses, and needed a way to analyze this data in near-real-time. The challenge was to find a solution that could handle the complexity and volume of the data, and deliver the desired results.

Takenaka Corporation, a major general contractor founded in 1610, has a wealth of architectural data spanning over 300 years. However, turning this vast amount of data into usable information for modern architectural design was a significant challenge. The data was stored in various formats and was difficult to manage and use effectively. The company wanted to use this data to expand the possibilities of architectural design and to integrate it with the thoughts and feelings of people today. The company was using Tableau, a Business Intelligence tool, to visualize this data, but it was not sufficient for their needs.

7-Eleven was facing a challenge in managing vendor data and gaining insights into their promotions. The process of requesting a vendor report or initiative was time-consuming, taking up to 100 hours. The company needed a solution that could be used by a business user on a daily basis without much technical support. They needed to get results quickly to share with external business associates and provide multiple capabilities at a marginal cost.

Ares Management, a leading global alternative investment manager, was facing challenges in automating their processes and breaking down silos between their teams. They were also struggling with providing better access to insights. One of their teams was spending two months to complete a process once a year, which was highly inefficient and time-consuming.