Advocate’s old system had problems with speed and scalability. It could take multiple hours to produce an extract, often timing out during the process and failing. On top of this, it was very slow to refresh, was dated, and most importantly, could not handle their growing amounts of data.

Casumo employees were not able to create their own business reports without the assistance of the data team and lacked information about crucial departmental KPIs. Emanuele decided it was time to move beyond time-consuming manual reporting, creating a forward-thinking approach to company data with standardized reporting and a centralized BI system. This would allow company employees to successfully integrate their own data sources and develop easily understood business reports, complete with data drill-down and ad-hoc reporting. After discovering Sisense online, Emanuele decided to move forward with a free trial. He was immediately impressed with Sisense’s ability to quickly connect to its Amazon Redshift database and crunch data into the Elasticube. The performance was significant, allowing him to generate useful reports on the very first day. Sisense gave Emanuele an end-to-end solution for ETL and reporting. He found that with just one hour of introduction to Sisense for his users, they were able to build their own dashboards and start getting the insights that they needed to effectively do their job, with minimal support from his staff.

After a huge restructuring effort, FirstPort realized that its organizational decision making was in need of a serious overhaul. Monthly board meetings were led by senior department managers, all with conflicting agendas and data to match. At this point in time, no one could even say with any certainty the amount of properties FirstPort managed. According to Alex, “If you asked three people you’d get three different answers.” Alex recognized the opportunity to not only unify the organization’s decision making process, but lead the company into a golden era of insight. FirstPort was generating so much data from its day-to-day operations, customer queries, financial information, and new business opportunities that they were overwhelmed. They knew they could add value and make improvements for both the customers and company if they could just tap into the data. Alex and his team needed to drive improvements in data related reporting and decisions for customers and staff members, yet lacked the necessary tools and resources to do so, having only Excel and Powerpoint. To meet their objectives, they estimated that it would take up to one year of effort if they doubled the size of their existing BI team of five. Alex decided that the right direction for FirstPort was automating as much of the data cleansing and analysis as possible, and to focus the BI team’s talents on analysis rather than ETL. On top of this, Alex needed a vendor that could do all of this in a reasonable period of time - days or weeks, not months or years.

When CEO Andrew Vignuzzi joined Magellan Vacations, his priority was to enable everyone at the company to access, manipulate, and draw insights from their data quickly. The company needed a BI solution that could provide real-time feedback for agents on sales closings, destination performance, and other metrics. Additionally, the solution had to be user-friendly enough for non-technical users to create their own reports and drill down into the data. The dashboards needed to be agile and scalable without requiring major infrastructure upgrades. The personalized, phone-based service of Magellan Vacations made it difficult to track standard sales metrics like closing rates, commissions, and bookings by destination automatically. The company had already trialed a leading in-memory technology, but its performance was sub-par, requiring specialist IT resources and consultants to work with the tool's proprietary scripts. This tool did not meet their needs, prompting the search for a better solution.

Before implementing Sisense, alpharooms.com faced significant challenges in providing detailed and interactive reports and dashboards to various business functions. The existing tools, such as Excel and OLAP cubes, were not effective in building user-friendly dashboards or offering easy drill-down interfaces. Additionally, IT involvement was required for any modifications, making the process cumbersome and time-consuming. Lee Eckersley, Head of Business Analysis, had experience with other BI tools like Cognos, Hyperion, and Business Objects, but found them too expensive and resource-intensive for the company's needs. The team needed a more efficient and cost-effective solution to handle their data analytics and reporting requirements.

GOAL Academy, an online charter school, faced challenges in effectively utilizing data to keep students on track and align staff with key performance indicators (KPIs). The school relied on various data resources like Google Docs, Excel spreadsheets, and different servers, which made it difficult to create a consistent format accessible online. The institution needed a modern tool to better visualize and understand the data, and to merge multiple platforms into one place. The goal was to find a web-based tool capable of processing data from different sources to help teachers make quick decisions in the classrooms and improve student retention and graduation rates.

In addition to the custom software that Businessolver had developed internally, they were also using several off-the-shelf technologies such as inContact for their service center; Salesforce.com for sales team and Sage for the accounting department. There was no unified method to tie those disparate data sources together and get an overall picture of the customer interaction. Users would get various exported files from various other users and load them up into MS Excel and analyze in a single location. Due to this lack of uniformity to data access, team members were constantly providing different results to the same question. The problem was not the volume of data but rather the disparate sources of it. It was critical to Businessolver to find and acquire a tool that would allow them to connect all their data sources across the enterprise. That way they would be able to have full confidence that their results were accurate no matter who was collecting the information, and that data could drive decision making based on facts and not based on feelings. Sony Sung-Chu is the Director of Applied Data Science at Businessolver and it was his task to find and test potential solutions. With his years working as a Business and IT Analyst, he came at the question from a very technical perspective. Sony also brought in Sara Johnson, the lead BI analyst for Businessolver, whose background is in economics, math and Business Intelligence. Johnson brought in the first data warehouse at Businessolver and was to be tasked as the internal BI expert, responsible for training and maintenance.

When a food retailer launches a new item, many people are involved in the process: chefs, suppliers, procurement teams, taste testers, marketing, focus groups, legal teams, manufacturers, shipping companies, etc. Moreover, Gap Systems’ clients manage hundreds, even thousands, of product launches a year. That’s a lot of moving parts - including mountains of data that needs to be managed and interpreted to ensure a successful launch. Smartflow was intended to track these disparate items, so you know who is doing what at any particular time. Except, this wasn’t how customers were using the tool in reality. As a result, clients weren’t getting the value or insights they needed. They would say things like, “It seems our legal department is slowing us down, we need to do something about that,” when in fact, they couldn’t really show either way whether legal was the problem. It was all based on instinct or assumption, rather than the hard data they had at their fingertips. Evidently, choice wasn’t working. Customers needed high-end reporting embedded into the product to make Smartflow a success.

Integrous Marketing faced significant challenges in integrating data from multiple disconnected sources such as Adwords, Analytics, email marketing tools, and Salesforce. The process of manually gathering, cleaning, and joining datasets was labor-intensive and prone to errors. Additionally, generating visualizations from the data in Excel was time-consuming and often resulted in outdated and inaccurate information. The company needed a method to automate these steps and provide a better user experience, especially given the limitations in the types of reports and views that some tools provided.

Many companies today often have data that is so complex or distributed, it needs a dedicated team of specialists to clean and maintain it, and only then can a BI tool be useful. There’s a lot of work preparing complicated and dirty data, and many businesses need a simple way to prepare data that most BI tools on the market cannot provide. Mike saw that even after implementing a BI solution for customers. There was often such a steep learning curve, the customer would still be unable to build reports and dashboards independently. Mike’s customers typically come to him after they've failed with another BI solution. His company then takes on managing the client's internal data, some of which as been around for 10+ years, and is big, disparate, and dirty. His team would then wrangle the data together into a BI solution for the client. Mike saw that even after implementing a BI solution for customers, it often had such a steep learning curve, the customer would still be unable to build reports and dashboards independently. It was important that his customers could be self-sufficient, so he wanted to standardize on a tool that he knew would be a win for them.

BrightStar Care faced challenges in visualizing large volumes of data spread across multiple systems, including their home-grown application ABS, accounting software, help desk software, survey systems, and Microsoft Dynamics. They needed a solution to quickly answer business questions without rebuilding the entire pipeline for each new analysis. Additionally, they wanted to distribute their dashboard solution globally, allowing franchisees to access and visualize their own data easily. The complexity of the data and relationships between sources made it tedious to analyze, and they required a BI tool that offered self-service capabilities, agility for ad-hoc queries, visually attractive presentations, and a low cost of ownership.

Doron Gill, VP R&D at FairFly, needed to make day-to-day decisions based on a rapidly growing database. He wanted to combine this data with several other sources, including MixPanel and a CRM, without relying on R&D resources. After researching several BI tools, Doron realized he needed a tool that was easy to use for non-technical business managers. He was concerned that if R&D or IT had to manage data requests daily, it would not be sustainable. Doron and his colleague Ami Goldenberg were impressed by Sisense's ability to be used by business users without R&D involvement and its intuitive data visualizations.

Gentex, a leading supplier of personal protection and situational awareness systems, was struggling with an outdated ERP database that was over 30 years old and heavily customized. The company needed fast and accurate operation planning metrics such as projected revenue, opportunity forecasts, and expense reports. However, incorporating modern technical tools into their ERP environment for data analysis was limited and costly. The system had millions of records, and they needed a solution that could quickly process this data and deliver actionable intelligence.

When Ric Lumbard, Executive Director at ICN, stepped into his position, he realized that a central visual point for data did not exist. As a broadband carrier, ICN needed a visual system to be able to monitor the overall health and performance of the organization. Director Lumbard explained that state agencies tend to focus on monitoring the legal aspects of operations, but measuring the performance of operations is not always given the same attention. Director Lumbard was looking for a solution to raise the importance of performance awareness by providing visual cues and monitoring that allowed the staff to easily and quickly see a dashboard with important performance indicators. Another focus point for ICN was that the data to be analyzed was scattered across numerous sources–from a variety of databases to spreadsheets–in multiple servers and applications. The operations perspective needed a way to combine that data, maintain a single repository of truth, and visually analyze the data without sifting through dozens of pages of spreadsheets and columns.

The decision to evaluate BI solutions came in the wake of what could be defined as a “cultural revolution” taking place in JDC: from siloed data, with each stakeholder holding on to his or her own data and only sharing it with others on a “need to know” basis, to a corporate culture of complete transparency of information that aims to make data available to everyone, and challenge them to make good use of it. The data itself was being stored in a Cobalt character-based CRM system running on the IBM RS/6000 platform, as well as Excel spreadsheets. This data consisted of sales, operational, utilization, financial and other data. Prior to Sisense, reporting was done with Excel and Access. JDC has been looking for some sort of dashboard software for roughly two years but did not find any product that could suit their needs, until they ran into Sisense in a user group in which two Sisense customers had presented it. The VP of Parts and Business Systems downloaded the trial version right there at the convention, and within two days was already publishing dashboards.

Pantechnik International faced significant challenges in managing and utilizing their vast and scattered data sources. The company struggled with a 'black hole' of largely untapped client data, making it difficult to gain a holistic view of overall performance, cost-effectiveness, and service level agreements (SLAs) of their carriers. Senior management lacked visibility and control over these metrics, which was further compounded by the data preparation nightmare of the ETL process. The company evaluated various solutions, including Qlikview, but found the 'buy before you try' business model unappealing. They needed an embedded BI software with a powerful backend capable of handling thousands of large, scattered datasets.

Over the last 15 years, the National Healthcare Service (NHS) of the UK increased their spending from 70 billion British pounds to 150 billion British pounds. In order to improve their efficiency and cut costs, the NHS created dedicated internal organizations to measure performance of organizations against each other, and to publish and distribute the data in performance reports. The problem was, the healthcare data was very complex - big, scattered and siloed - limiting the reports to focus on one area of measurement or one organization per report, and were published as static PDF documents. Users were unable to compare to other organizations or integrate across different sets of data, giving them an isolated view of their performance. Data regarding each area, such as clinical performance, cost performance, and staff and patient surveys were reported in separate and heavy 50-page plus documents that required time and research to see a bigger picture across platform. That’s where Res Consortium came in with the goal of providing performance dashboards that showed the data across platform in an intuitive way. In the past Res Consortium was producing dashboards using Excel with protection keys to protect sensitive patient data, but started looking for a BI platform that could move the dashboards to a web-based environment as well as to more efficiently and quickly handle the amount of complex data typical in healthcare.

FCTG faced challenges in pulling data together for a simple and user-friendly report to track daily sales and performance across the company. It would take up to three hours each morning to create this report, which the sales team used to influence and plan their daily targets. There was a need to improve efficiency and minimize any lost opportunities, and thus, it was necessary to develop an end-to-end solution that would be able to replace manual reporting, and allow 80 business users to receive daily reports at the click of a button. Prior to Sisense, the nSight brand didn’t exist and Flight Centre’s finance team was responsible for generating all of the company’s reports. As a part of the finance team for three years, Graeme proposed the idea to implement a BI solution, as he noticed analytics were getting more and more difficult with the company’s rapid expansion. He looked at three different BI software companies hoping for a solution that could automate daily reporting in a cost-effective way, be easily managed by people who may have little to no technical knowledge, and also allow business users to flexibly manipulate the data to immediately answer questions they had. Sisense checked all three boxes.

Michael says data streams included CSV, Excel, or Salesforce along with donations over time, who gave how much, when they gave it, and in what fundraising program. What may have looked like a very straightforward, neat, and organized Excel document from a foundation, actually possessed a great deal of insight that could be derived from it if the data was manipulated strategically. Michael’s goal was to dig into what donations amount to loyalty, how contributions come in, renewal rate, weight of attrition, and much more. On top of this, because CESM is looking at time series data and is able to look at time analysis, like seasonality or cycles of giving, there were even more insights to be discovered. However, after many days of work, all Michael could say was, for example, 'in 2006, your renewal rate was 60%.' Looking at data that was static, he was unable to go further without putting a lot more effort into it. It was time to find a better solution, and that is where Sisense came in.

Blueline’s biggest problem was figuring out which budget allocations were connected to which sources of revenue. A single marketing campaign could bundle together various lines of business, making it hard to get a clear picture of the bottom line of promotional activities or to break down the revenue of product bundles by product and sub-product. The company lacked a way to combine data sources from different departments, leading to standalone reports that didn’t match up. This confusion resulted in inappropriate investments, reactive problem-solving, and missed business opportunities. As Blueline prepared to launch their mobile initiative, Nacer decided it was time to address the problem once and for all, anticipating high volumes of transactions that could cause enormous problems if not managed properly.

ES Originals faced significant issues with disparate and disconnected data, with nearly 1000 reports running against their ERP system. This led to logistical challenges, as reports were static and required new reports for any additional fields or selection criteria. The company needed a unified and standardized reporting system to streamline the process and reduce the number of reports. Additionally, salespeople had to bring hard copies of reports to client sites due to unreliable internet connections, and data from partners came in different formats, complicating the reporting process.

EEG had to structure the data to have the functionality and flexibility at an interface level so that they could easily deploy it to any event type and use consistent tools to report on the data. That is where the problem arose: though the data was being collected, the data created data dumps that were cumbersome to understand and not structured to produce easy or accurate data analysis. After Adam sifted through the data dumps of a number of their clients, he realized that some data just couldn’t be connected in a traditional reporting environment - creating gaps of what they could report. After talking to a longtime client, he found that many of their clients were forced to manually pull data and reports together - and were spending a significant amount of time doing it. Adam attempted to solve the problem by doing data analysis for his clients internally and sending out the reports. But, for Adam to do that internally, he had to pull the data out of Salesforce, cobble it together, create reports and charts in Excel and then email them out. Every report would have taken weeks at least, and the clients wanted to see this data frequently and quickly, so it wasn’t feasible.

As the company grew, Online Commerce Group’s data become so large that, without a new generation Big Data Analytics solution, management couldn’t receive quality reports. The fast growth of the company meant that Data Manager Paul Auen was unable to run reports with large enough data sets to provide any real value to the business end. “Originally, we could do reports manually, but as the data sets got larger, the reports took longer and impacted the transactional database,” Auen recalled. “We were constrained between keeping the servers running or making it available for reports.” Online Commerce Group chose a popular business analytics tool, but it was too complex; Auen’s group was unable to run reports at the speed and frequency needed for the business. Quickly, the team abandoned and turned to Sisense. The company needed a solution that could: 1. Quickly analyze large data sets coming from multiple sources. 2. Provide drag-and-drop modeling and dashboard creation for business users. 3. Automatically generate reports and publish them to the company intranet. 4. Require a minimal capital investment and learning curve for use.

Plastic Jungle’s business success is predicated by its ability to move faster than the competition. When the company brought in a new CFO in 2012, he aimed to deploy a data solution that would match the company culture. Speed, accuracy and agility were the key tenants for the company data approach. “We wanted to make sure we didn’t paint ourselves into corner by taking a traditional approach to data warehousing.” That meant a solution that could grow to massive amounts of data, and allow regular business users to work with data quickly without requiring a huge investment that would leave them beholden to the product.\n\nPlastic Jungle's BI requirements included the ability to:\n• Manage and sustain the entire operations aspect of Plastic Jungle’s data warehouse with little or no operating support from the engineering and IT staff\n• Allow business users to create any ad-hoc reports they required\n• Provide the abstraction layer between the schema and the metrics that the business sought\n• Refresh in close to real-time – a minimum of once per day, and ideally every couple of hours\n• Not incur a significant capital outlay

FTA’s member companies needed reliable data on producers to avoid human rights abuses and unsanitary conditions. The manual system for auditing and reporting data was inefficient, making it difficult to provide timely and accurate reports. Members had no way to independently access data, requiring internal resources to manually extract information from various sources. This lack of visibility and efficiency was a significant challenge for FTA.