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Banco Bradesco, a leading financial institution, was facing challenges in meeting evolving customer expectations due to its legacy data warehouse. The existing system was too cumbersome to share customer data with other entities, with customer, transactional, and consent data scattered across disjointed systems. This lack of collaboration hindered proper data analysis and AI, creating obstacles to fully embrace open finance and the move to become a cloud-first bank. The bank's legacy on-premises infrastructure needed to improve to overcome the technical barriers of sharing 20+ terabytes of customer financial data with outside organizations. Rolling out new applications with over 1,000 siloed databases would take months, making deployment inefficient. Engineers struggled to complete projects, as they were inundated with IT operations work to maintain their infrastructure. Analysts needed help accessing and exploring data promptly, dependent on an overburdened engineering team to provide curated data and reports.

Barilla, the world's largest pasta producer, faced significant challenges due to unpredictable crop yields and rising raw material costs caused by climate change. These disruptions led to product shortages and quality issues, necessitating a more sustainable and resilient supply chain strategy. However, Barilla's legacy on-premises data warehouse was unable to scale their operations effectively, creating silos that hindered their ability to navigate these external threats. The company's supply chain and logistics needed to maintain high-quality standards while maximizing revenue in a low-margin business. As Barilla's distribution expanded to meet growing global demand, it became clear that they needed to modernize their data to enable analytics at scale. With over 1TB of data ingested daily, data analysts struggled to integrate and analyze the necessary data, leading to delays and inefficiencies. Additionally, Barilla's large European footprint required processing sensitive consumer data for GDPR compliance, necessitating a robust data governance plan.

Barracuda Networks, a global leader in security, application delivery, and data protection solutions, was faced with the challenge of handling sophisticated phishing emails. The company had built a powerful artificial intelligence engine that uses behavioral analysis to detect attacks and keep malicious actors at bay. However, the sophistication of attackers in creating malicious emails posed a significant challenge. The company needed to assess and identify malicious messages to protect their customers. Additionally, Barracuda Networks offered impersonation protection, a service that prevents malicious actors from disguising their messages as coming from an official source. However, these targeted phishing attacks required the attacker to have personal details about the recipient, making them harder to detect and block. Furthermore, Barracuda faced difficulties with feature engineering. They needed to utilize the right data and do feature engineering on top of that data, which included email text and statistical data. Before the Databricks integration, building features was more difficult with the labeled data spread over multiple months, particularly with the statistical features. Also, keeping track of the features when the data set grew in size was challenging.

Block, a global technology company, was facing challenges in managing a large volume of data crucial for graph-related use cases. This included handling graph databases, leveraging various machine learning tools, and optimizing performance for petabytes of data. Operational inefficiencies and scalability concerns arose due to the fragmented nature of data across diverse business units. The cumbersome data transfers between these systems, combined with the siloed nature of data governance policies, posed auditing and policy enforcement challenges. Block was also in need of a proper implementation and uniformity of data governance policies to ensure compliance with privacy laws like GDPR and CCPA for both customers and internal teams.

Burberry, a British luxury brand, faced a significant challenge in managing and annotating its thousands of marketing images. The company needed to classify these assets accurately to use them effectively in its marketing campaigns and drive the right action by the right audience. Burberry initially tried using an open-source tool for image annotation, but it had serious drawbacks. The company was looking for a solution that could improve the data for training its models quickly and easily. They wanted to produce labels for thousands of images and place them seamlessly into a model development pipeline for convenient reuse. The challenge was to find a solution that would integrate well with Burberry's existing Databricks implementation, a single, unified analytics platform for all its stakeholders.

ButcherBox, a young e-commerce company, operates on a monthly subscription-based model, delivering fresh, organic, and ethically sourced meat and seafood to its customers. However, the company faced significant challenges due to the complexity of its operations and the vast amount of data it had to manage. The data, coming from various sources such as email systems and the company's website, was siloed, preventing complete visibility into critical insights needed for strategic and marketing decisions. The data team struggled to deliver timely and accurate reports and insights. The legacy data warehouse environment was proving to be a hindrance to the company's agility and speed, making it difficult to keep up with the changing needs of their growing customer base, improve supply chain operations, and forecast demand.

CareSource, a nationally recognized healthcare organization, has been experiencing exponential growth over the past 30 years. This growth has led to an influx of new members, which the company's legacy data systems were unable to handle efficiently. The company had to resort to temporary solutions such as running jobs designed for monthly execution on a daily basis, which the systems were not designed to handle. This resulted in the expenditure of significant resources to maintain the systems. The company needed a modern data platform that could scale, perform efficiently, and be future-proof. The platform needed to be cloud-based and capable of serving as a single source of truth for all incoming data.

Carvana, an online used car retailer, developed its Next Generation Communication Platform (NGCP) to provide a seamless car shopping experience. However, the NGCP team faced several challenges related to scale, data quality, and high data warehouse costs. The team initially streamed its conversation and AI data into Google BigQuery, which limited how data engineers could partition and optimize query tables. Data quality was another challenge, with engineers needing to dedupe in the pipeline, but distinct calls on large data frames were slow and caused recomputation on the entire data set. The team also faced data availability challenges, with no process to automatically pick up experiment data as campaigns were configured and run. Maintenance and transparency were another challenge, as a single repo contained both the ETL and business logic. Finally, the data sets produced often contained too many files to be shipped to data warehouses via the Spark Connector, creating a data export bottleneck.

Cleanaway, Australia’s leading waste and recycling services provider, faced a significant challenge in managing data from its diverse operations. The company's operations, including waste collection, sorting, and logistics, involved different IT systems, leading to data being scattered across multiple, disjointed sources. This data sprawl was a major obstacle as the complexity and variability of Cleanaway’s services generated large volumes of operational and service data from various sources, including GPS and connected fleet systems, and structured and unstructured data from customer transactions, sales, marketing, and more. The company's ambition to become an efficient and profitable data-first business as part of its Blueprint 2030 objectives was hampered by these data silos, which impeded the sharing of actionable insights and resulted in unreliable insights due to inconsistent data quality.

Collective Health, a technology company revolutionizing health insurance, faced a significant challenge in managing and integrating data from various partners. The company's mission to simplify employer-led healthcare and improve health outcomes required a robust, flexible infrastructure that could handle vast amounts of data. However, the company's existing data integration architecture was not equipped to handle the evolving business requirements. The schema was constantly changing, and columns that previously contained data started to contain null values. Moreover, the company needed a solution that could ingest files incrementally without having to go through each file previously ingested. The challenge was to find a solution that could handle these complexities while ensuring data quality and scalability.

Condé Nast, a global media company that cultivates 37 of the world’s most influential and iconic brands, was planning its global expansion. However, the company realized that its data architecture was too complex to provide the scalability it needed. The company had stored its data in siloed systems, with five different data sources integrated with its then query engine, Presto. Data engineers ran ETL jobs and processes on Databricks Lakehouse and stored the data in Amazon S3. They also created tables in Databricks and pointed them to the storage layer in AWS S3. The data warehousing team used Informatica to build data models, stored the results in S3, and worked with data engineers to point that data set back toward Presto so that teams could access it in data queries. This complex and siloed data architecture was hindering the company's growth and expansion plans.

Dassault Systèmes, a 3DEXPERIENCE company, was faced with the challenge of addressing climate change, one of the most significant threats to our world. The company aimed to use solution-based design to build a more sustainable future. To achieve this, they partnered with globally renowned architects and thought leaders, Kengo Kuma and Associates. The challenge was to consider the use of existing pollution-neutralising materials in the production of their creation. The goal was not only to create a sustainable solution but also to stimulate dialogue within the design community about the potential solutions that emerge when design and technology converge.

The challenge was to launch EVEN, IHG's new wellness hotel concept, which was primarily targeted towards business travelers. The concept of a 'wellness hotel' was quite subjective and left consumers confused about what they were checking into. The task was not just about building awareness but creating a new category in the hospitality industry. The nebulous concept of wellness was not enough to attract customers, and there was a need to define the amenities of EVEN in a way that would resonate with potential guests.

MainStem, a B2B SaaS supply and purchasing platform for the cannabis industry, was faced with a significant challenge. The company's Chief Technology Officer, Garrett, was dealing with three crucial integration requests (Teams, Slack, and Quickbooks) simultaneously. However, his team was unable to prioritize these integrations as they were focused on developing core product features for their enterprise offering, Purchase Pro. Existing customers were frustrated due to the lack of MainStem notifications in their messaging apps, and potential enterprise clients required QuickBooks integration for decision-making. Previously, MainStem had built numerous integrations in-house, but these required significant engineering effort to build and maintain. The team would spend weeks understanding the API documentation for each third-party app, dealing with user authentication and token management, and maintaining the integrations due to changing vendor APIs. This approach had several drawbacks, including diverting engineering resources from their core product, impacting sales and customer success team's confidence in their integration roadmap, and increasing maintenance requirements.

Fidelity International (FIL), a global investment and retirement savings business, was in need of a technology partner to manage their global third-party supplier risk and performance management program. The challenge was to maintain a single inventory of all their third-party risk information, identify and segment critical and high-risk suppliers, and streamline the end-to-end third-party risk and performance management processes across the enterprise. The solution needed to provide advanced reporting capabilities and dashboard visualizations for a complete view of risk and performance, ensuring greater governance and standing up to regulatory scrutiny and good business practice. Furthermore, the solution had to be flexible, cost-effective, and able to scale and adapt to change quickly to support Fidelity International’s long-term requirements for success.

Culture Amp, an employee experience platform, was facing challenges due to its continuous growth. The company was at risk of falling behind and encountering circumstances that could cause misalignment within their priorities and processes. As a company working in the cultural space, they needed to stay ahead of evolving trends, especially during the shift to remote work and the onset of the 'great resignation'. The company also faced difficulties in aligning departments towards common goals as it scaled. The larger the organization grew, the more disparate the tasks became, leading to disagreements about priorities. Another challenge was the need to improve deal velocity, a crucial part of company growth. Culture Amp noticed that not all sales calls ended with clear next steps, slowing down their processes.

Gainsight, a platform that aids companies in driving growth through customer-led, product-led, and community-led strategies, was facing the challenge of keeping up with changing market trends. The company needed an intuitive and easy way to surface insights about their prospects and customers. As a large organization with nearly 1,400 global employees, Gainsight required a solution that could be easily adopted across all teams and provide immediate and significant impact. The CEO, Nick Mehta, was looking for a tool that could help him understand the authentic voice of Gainsight prospects and customers, and how market trends impact them and the overall business.

Before the implementation of Gong, Handshake’s forecast information was scattered across various systems, making it difficult to get a comprehensive view of the sales pipeline. Each opportunity had to be individually assessed, which was a time-consuming process. The lack of a unified system led to inefficiencies and inconsistencies in the sales process. The sales team was spending a significant amount of time on low-value tasks such as searching for data in multiple tools and maintaining pipeline hygiene. Poor pipeline hygiene was a common issue, with reps having to open dozens of opportunities, click through multiple fields within each opportunity, change a few bits of information, and save. This process had to be repeated for each opportunity, making it painstakingly slow and inefficient.

Highspot, a sales enablement software company, was faced with the challenge of implementing a new sales methodology. The company wanted to offer a series of trainings to help sales reps understand the messaging and how to use it with clarity and precision. The implementation required managers, sales reps, and marketing to be on the same page about goals and outcomes. They also wanted to monitor what was working and what wasn't throughout the process. The macro-economic environment was shifting, adding pressure on the sellers. Therefore, Highspot needed to make learning light and create a way for their sellers to quickly adapt to the changes.

Influitive, a pioneer in advocate marketing, was in search of a platform that could significantly impact their sales, growth, and customer retention. The company was struggling to find insights that could inform actions leading to substantial improvements. The absence of Gong, a platform they had previously used, left many sales representatives feeling as though they had lost their most productive tool. When Influitive switched to a competitor, they lost the comprehensive view of their sales cycle, from deal health to talk tracks, which had previously helped to streamline work across departments. The alternative solutions did not seem to be designed with the sales representative in mind, leading to a noticeable drop in productivity.

Isos Technology, a leading IT services and consulting company, was facing a significant challenge in managing its sales operations. The multitude of technology solutions available in the market was causing confusion and inefficiency. The company's Digital Sales Director, Lia Wood, was seeking a single, comprehensive tool that could streamline their efforts, allowing them to focus on their highest priorities. The challenge was to find a solution that could reduce the need for multitasking, thereby enabling the sales team to be more present and focused on their tasks. The ideal solution would also need to provide a platform for effective onboarding, coaching, and data-driven feedback.

Proposify, a proposal software company, was facing a significant challenge in managing their sales cycle. The information about deals was scattered across multiple platforms, including Salesforce, Gmail, and Chorus. This lack of a unified view led to difficulties in forecasting, resulting in unpredictable monthly numbers and poor revenue alignment. The team often had to rely on gut feelings rather than hard data, making their forecasts unreliable. Additionally, the company was using recording software Chorus to help managers coach reps’ calls, which required them to seek out information from multiple sources. This made it difficult to improve calls and kept the call and forecast coaching separate, leading to a lack of accountability and constant off-forecast situations.

Quotient Technology, a leading digital promotions and media technology company, was facing a challenge in understanding the unfiltered voice of its customers and anticipating their needs in a constantly changing market. The company needed a solution that would allow them to gain a more authentic and accurate understanding of their customers' sentiments, enabling them to deliver better outcomes. The challenge was not just about course-correcting after the fact, but about being able to point their services in the right direction from the start. The company was also looking for a way to drive visibility regarding revenue strategy and organizational decision-making.

SoftServe, a digital consulting company, was facing operational inefficiencies due to a lack of easily accessible data. The company, with teams based in Ukraine, was operating under challenging circumstances, making productivity a crucial factor. A significant issue was the lack of alignment across teams, leading to gaps between services. The company's intricate sales process was also a concern, as it required a more seamless approach. The absence of data made it impossible to justify the need for restructuring or to identify the areas that required immediate attention. Furthermore, the company was struggling to maintain productivity due to the lack of necessary information.

Sparrow, a San Francisco-based startup founded in 2018, was facing significant challenges in managing and optimizing their sales and marketing processes. The company, which specializes in employee leave management, was struggling with the lack of a system to record or analyze their conversations. This resulted in the team spending valuable time recapping and rescheduling meetings to ensure all members could attend. The company was also grappling with the challenge of keeping their sales team updated and trained, especially in a fast-paced startup environment where the product and business are constantly evolving. The traditional methods of running meetings, taking notes by hand, and scheduling follow-up meetings were proving to be inefficient and time-consuming.

Tackle.io, a zero-engineering platform that provides a go-to-market solution to help B2B software companies establish, operate, and scale sales through the cloud, was facing a significant challenge with forecasting. The company was spending over 10 hours per week on forecasting tasks, which involved going through spreadsheets, piecing together data, and having endless conversations with sales leaders and sales reps. This was not only time-consuming but also inefficient. The company's sales leaders were dedicating their one-on-ones to forecasting, taking away from valuable leadership and coaching time. This was starting to weigh on the company's Vice President of Sales, Jeramee Waldum, who was striving to build a sales organization that wasn’t of the super-high pressure mold.

Tinuiti, a leading advertising and public relations company, was facing a significant challenge with its manual sales process. The company had little to no analytics or data-backed insights to support its sales operations. The data they had was often insufficient and not the 'right' data that could drive their growth. The company was struggling to identify cross-selling opportunities and was in dire need of a solution that could help them grow at scale. The sales process was long and complex, and the company needed a way to capture, store, and ensure sales information was quickly and accurately searchable. The lack of an efficient system was hindering their growth and evolution.

Redo Sgr, a real estate company based in Italy, was faced with the challenge of integrating Environmental, Social, and Governance (ESG) criteria into its investments. The company decided to undertake the GRESB rating to measure and benchmark its sustainability performance. However, the challenge was to achieve comprehensive coverage of energy consumption in all the buildings they monitored. The company was also aiming to significantly improve its benchmark reports issued by the rating.

Blackmon-Farrell, a commercial electrical contractor based in Rochester, New York, was grappling with the inefficiencies of paper-based processes. Bidding on public sector contracts required extensive documentation, which was managed manually, leading to workflow challenges and wasted manpower. Closing out a project required tracking down the status of over 100 open purchase orders, a time-consuming and tedious process. Change orders also impacted the schedule, requiring site visits or sifting through different versions of a drawing to put together an estimate. Field teams used mobile devices to access, view, and annotate Bluebeam files in real time, but connectivity issues made the process slow. Some teams used personal hotspots, but often exceeded their data capacity within weeks, leading to throttled bandwidth and high costs. The company was spending at least $80 per month per user on wireless data costs. The need to print multiple copies of plans and manually scan large drawings added to the inefficiencies and costs.

Founded in 2015, Decibel Therapeutics is a clinical-stage biotechnology company that focuses on developing transformative treatments to restore and improve hearing and balance. As the company grew and went public in 2021, it became increasingly reliant on a global network of contract research organizations (CROs) to conduct comprehensive clinical trials. These CROs collected a variety of data, including visit times and dates, testing results, adverse event information, patient status, and more. The sheer volume of data collected necessitated a solution that could not only ensure the accurate intake of data from CROs but also apply rigorous governance over the data, consistent with Good Clinical Practices (GCP). Additionally, the solution needed to support the secure sharing of clinical trial data across external third parties.