Travis Perkins, a British builders’ merchant and home improvement retailer, was facing a significant challenge due to the presence of many data silos within its operations. These data silos made it difficult for the company to quickly access a single truth, leading to inefficiencies and potential inaccuracies in decision-making. The company needed a solution that would allow both internal users and external suppliers to have fast access to the same information, thereby improving operational efficiency and accuracy.

AFAS Software, a fast-growing ERP software provider, was looking to extend the benefits of enterprise-ready Business Intelligence (BI) to the more than 740,000 users of the AFAS ERP suite. The company wanted to go beyond modernizing business practices and advance to innovation by letting customers see the whole story hidden in their data.

Calltech, a provider of computer telephony integration and media management solutions, was facing the challenge of providing its customers with the ability to report beyond traditional operational contact center management KPIs. They needed a solution that would allow their customers to drill down, analyze, and understand their data. Additionally, they wanted to retain their cutting-edge position in the market without diverting resources to build a solution that already exists in the market. They also wanted a solution that would be user-friendly and would be quickly adopted by their customers.

eCare, an IT service provider specializing in 'whole care' healthcare solutions, was looking to enhance its value proposition. The company wanted to deliver easy-to-use visual analytics to business users and provide a software-as-a-service solution that lets users access software from any device. Additionally, eCare aimed to take its solution beyond traditional healthcare technology, providing new ways of visualizing and analyzing daily and historical health data.

Moody’s Analytics, a global provider of financial intelligence and analytical tools, needed a way to enhance their existing capabilities in order to offer new insights to their customers. They required a solution that could handle vast volumes of data about borrowers for benchmarking and risk assessment. The challenge was to present this data in an intuitive and easily accessible format that could be explored to granular levels.

MTech Systems, a company operating in the live protein industry, was facing a growing demand from its customers for faster access to more robust reporting and the ability to interact with data in a visual format. The company was also looking to broaden its target audience within its current segments. Furthermore, the industry was experiencing an explosion of new data as equipment, house controllers, gauges, and more were coming online. This presented a challenge for MTech Systems' customers to benefit from and better manage this influx of data.

Tagetik, a leader in innovation, was looking to differentiate itself and deepen its competitive advantage in a crowded market. The company wanted to embed visualization, analysis, reporting and dashboards, and an associative in-memory analytics engine directly in its solution. The challenge was to integrate these features into their existing platform in a way that would provide their customers with visibility into all financial processes.

Unified Logic, a company specializing in IT asset management, security, and infrastructure solutions, faced the challenge of presenting their vast amount of data in a meaningful and flexible format. Their core product, Movere, integrates more than 1,000 data points and their largest single data set contains more than 50 million rows. The company needed a way to allow their customers to reshape their experience in a meaningful way using this data.

StoreNext, a leading research and analysis firm in the consumer goods market in Israel, was looking to improve its value proposition. The company wanted to launch a next-generation self-service Business Intelligence (BI) solution that would allow its clients to analyze millions of transactions to better understand market trends. Additionally, StoreNext's clients had been requesting mobile capabilities, which the company was keen to provide. Another challenge was the company's reliance on external consultants for the development of the solution, which they wanted to reduce.

CEGID Group, a provider of management software for organizations in multiple industries, was looking to enhance its software-as-a-service offering. The company wanted to provide its clients with a seamless experience that would allow them to easily collaborate and explore data through customized dashboards. However, the company faced challenges in achieving this goal without requiring special training for its clients.

Xn protel, a global provider of business-critical applications for the hotel and leisure sector, was looking to leverage and integrate key hotel subsystems into one synthesized dashboard. They wanted to transform their business intelligence tool into a true end-to-end solution, which would open access to a new global user base. The challenge was to provide significant cost savings and increased service levels to their customers.

Vancouver International Airport (YVR) is striving to become the preferred TransPacific hub for passengers traveling between Asia and the Americas. To achieve this, YVR needed near real-time data analytics to gain a clear understanding of how passengers, bags, and planes move through the airport. This data would enable YVR to optimize its minimum connection time and enhance the passenger experience.

Namaste Direct, a non-profit organization, was struggling with data management. They were dealing with mountains of paper records and had to manually transfer data into Excel spreadsheets for analysis. This process was time-consuming and prone to errors. When they received large requests with strict deadlines, such as pulling data on 50 clients’ businesses for a report due the next day, it was stressful and challenging. They needed a data analytics platform that could streamline their operations and provide clear, actionable data quickly and accurately.

The healthcare provider faces several challenges. They need to service a wide geographic area and reconcile financial constraints with growing demand. They also need to obtain real-time access to a single source of data, ensure adequate bed and staffing availability, combat bottlenecks and meet emergency demands, and view the status of all hospitals at a moment’s notice.

The biotechnology firm was facing challenges with data consolidation from disparate sources. They were relying on manual Excel-based processes which were inefficient and time-consuming. The firm needed a solution that could handle franchise performance, product launch, market share, patient evolution, competitive and financial data. They were also looking for a solution that could empower end users and provide education.

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.

The healthcare industry has been transformed by the advent of electronic health records (EHR), which provide accurate, up-to-date, and complete patient information. Epic, a leading EHR provider, has developed the Epic Caboodle Data Warehouse (CDW) for the storage and retrieval of large amounts of clinical data. However, healthcare organizations often struggle with accessing this data efficiently. Traditional ticketing systems for data queries can result in overlapping communications and lost time. IPC Global, a leading enterprise systems integrator of data, analytics, and cloud solutions, aimed to provide healthcare organizations with more efficient access to every record they have ever created and help them combine data from both inside and outside their organization for vital analysis.

AdventHealth, a healthcare organization, was looking for ways to integrate technology more deeply into the workflows of their frontline workers. They wanted to provide a tool that would help streamline workflows and increase the quality of work life for their clinical team. The challenge was to provide a tool that would be useful from an operational standpoint, providing near-real-time dashboards to give the nursing team and leadership the opportunity for action, not reaction. The goal was to develop a comprehensive tool for all levels of team members, from frontline nurses to the chief nursing officer, that could be used operationally to make actionable decisions to impact both patient outcomes and ensure good stewardship.

Asobanca, a nonprofit institution representing 15 of the 24 biggest private banks in Ecuador, faced a significant challenge in rebuilding people's trust in the banking system following the financial crisis of 1999. The crisis, which was a combination of bad politics, bad banking, and bad luck, resulted in many banks declaring bankruptcy and 64% of the population living below the poverty line. This has led to a lingering lack of confidence in the financial sector. Additionally, the way information on the financial system is collected and distributed in the country posed a significant obstacle. Many different institutions disperse the data, each using their own methodologies of data collecting and processing, making the data often incompatible and difficult to analyze. Furthermore, data access services offered by some companies are expensive and not user-friendly, discouraging many potential users.

Charter Communications, the owner of the Spectrum brand of telecommunications and media services, was facing a significant challenge. In a saturated mobile market, the company wanted to launch new products within a nine-month timeframe. However, its existing technology infrastructure was not capable of delivering the necessary data within this period. The company needed a solution that could rapidly onboard and standardize 200Tb of data from more than 60 sources, and prepare and publish this data to various analytical and production platforms.

Contra Costa Health Services, a safety net system for the residents of Contra Costa county, was struggling with data management. Despite having access to a large amount of data, the organization was unable to extract actionable insights from it. The data systems were limited and decision making often had to be gut-based due to lack of evidence. The culture around data awareness was also very different at the time. Data can tell uncomfortable stories, and those stories can ruffle some feathers if an organization has not made the data maturity journey. Things changed significantly in 2010 with the Affordable Care Act and its funding for electronic health records (EHRs). As a result, in 2012 they went from only using electronic systems primarily for billing and claims to using Epic, an enterprise wide EHR solution. With a consolidated system and a great platform, they suddenly had access to massive quantities of data. The EHR data in the data warehouse was supplemented by developing partnerships with social services, county jails, and other community organizations to share data while following prevailing privacy laws.

The Consumer division of BT aimed to have a BT product in every UK household. To achieve this, they needed to consolidate various BT brand data from different data siloes and data warehouses into a unified view. They also wanted to empower users to interact and explore the data with confidence and trust.

HAN University of Applied Sciences, located in Arnhem and Nijmegen, the Netherlands, wanted to improve the data literacy of its students. The university recognized the importance of equipping students with the ability to understand and exploit data, given the increasing data generation in modern businesses. However, the university faced challenges in providing students with access to data analytics software and a community of experts. They also wanted students to gain practical experience on tools and processes common in the corporate world. The university was looking for a solution that would be cost-effective, given the tight budgets universities often have to work within.

Financial Services organization Meilleurtaux identified an urgent need to deploy commercial and marketing applications for their franchise agencies. The agencies required access to in-depth analysis to make informed decisions that would drive the business. The challenge was to find a solution that could provide the necessary data and analytics to the agencies in a user-friendly and accessible manner.

The global medical devices, pharmaceutical and consumer packaged goods manufacturing company was previously collecting data off-hours and storing it in highly structured data warehouses. The reporting was generally at aggregate levels and done in silos. The structured reports were designed to show what happened by plant, by product, over time. This approach was not efficient and did not provide real-time insights into the manufacturing process.

Castrolanda, a Brazilian agricultural co-operative, is facing the challenge of transforming from a physical organization into a digital co-operative. The expansive business has generated a wealth of data that could potentially be leveraged by its members. However, the data is unstructured and difficult for members to access. Everything has to be done in person, as their data portal is too inefficient to provide solutions in a digital way. The vision of Castrolanda is to bring structure to the data, give all members self-service digital access and educate them on how to use Qlik to gain business insights.

The author works at Amazon Produce, a major importer and distributor of fruit, and also teaches business intelligence at universities. The challenge faced by both the company and the students is the need to become data-driven in a world where data skills are increasingly in demand. For Amazon Produce, the complexity of their supply chain, which involves over 50 growers across Latin America and major US retailers, made it difficult to track performance and tell a story about everything that happened along the supply chain. For the students, the challenge was to gain hands-on experience with real-world business intelligence tools and build a portfolio of data visualizations.

As the UK’s largest scheduled coach operator and urban bus provider outside of London, National Express faced several challenges related to business intelligence (BI) and data analytics. The company had to deal with manual reporting from various data siloes, which provided limited insights due to reports showing only one aspect of company performance. The reports also had limited flexibility and analytical capabilities, leading to a high 'event-to-action' latency. To overcome these challenges, the company decided to deliver BI as a service.

Lintech International, a chemical distribution company, was struggling with managing the distribution and sales expertise of more than 2,000 chemical products from over 20 suppliers. This was negatively impacting their productivity and performance. The process of preparing reports from their ERP and CRM systems was time-consuming, taking up to 8 business days per quarter. This delay in data processing and reporting was hindering their ability to make timely and informed decisions, leading to inefficiencies and potential loss of business opportunities.

Amadeus, a leader in SaaS solutions for the airline industry, generates large volumes of data across its various applications. The company faced the challenge of reconciling and analyzing all of this data to produce attractive KPIs. They needed a solution that could handle the large data volumes and provide valuable insights for their operations.