Our client, a retail gas and electricity provider, operates a call center to facilitate customer requests and to offer complementary services, such as equipment maintenance.

Over 60% of the world’s global seaborne trade is shipped using intermodal freight containers, and the ports that manage them serve as central points for supply chains – over 90% of global trade is conducted through ports.

Great visualizations can make data come alive, leading to better insights and decisions. Data consumers of every kind rely on dashboards to perform their work, but they have a common complaint, slow loading times.

Palette Insight provides actionable intelligence about your Tableau deployment to help you maximize the benefits of Tableau Server.

Large enterprises acquiring companies often face challenges integrating their financial systems. Over the last several decades, our client has acquired dozens of businesses, each with its own ERP system and data warehouse solution.

Our client, a global manufacturer in the power generation industry, faced challenges with an aging reporting environment based on multiple Oracle ODS systems and reporting straight from source databases.

At the heart of data driven organizations lies the concept of data democratization: making data more accessible to everyone and making it easier to share, discuss, and act upon. Data visualization tools like Tableau help companies view, understand and leverage their data to make better decisions about their business.

As humans, we think and communicate in narratives. Numbers and visualizations help, but taken on their own, they often don’t tell the full story. A good dashboard may be useful for showing trends and conveying metrics, but it’s words that resonate with decision-makers and provide them with important context and situational awareness

Magnetic resonance imaging (MRI) artifacts, distortions or false signals that affect image quality, may adversely affect diagnostic quality, resulting in potential diagnostic errors and the need for costly and time consuming repeat examinations that may delay timely treatment. Detecting these artifacts with convolutional neural networks can save costs and improve outcomes.

Cardiac Resynchronization Therapy (CRT) can be a life-saving therapeutic option. However, the intervention itself has considerable risks, carries significant expense and its benefits to heart failure patients are limited to a small group of suitable patients, making patient selection critical. The right algorithm can determine patient selection criteria to identify patients most likely to benefit from CRT and least likely to suffer pre-operative or post-operative complications.

With Palette Trust Tableau Server administrators can communicate outage notifications, including direct communications and automated outage notifications directly on Tableau Server. Palette Trust automatically polls Tableau Server for internal process statuses and creates notifications based on predefined rules. No more automated messages sent through distribution lists to interrupt and be ignored.

We design and implement data lakes to analyze data in distinct ways, gain insights and create value out of the data your organization generates and imports. Our standard BI Data lake solution implemented on Microsoft Azure platform is based on Lambda Architecture providing flexibility to process either structured data coming from traditional SQL databases or semi/non-structured data ingested from IoT devices, logs, documents.

In large Tableau deployments, accounting for and maintaining licenses can be challenging for various reasons. However, our custom application produces a consistent and reliable database of users who currently holding a Tableau License Key.

Hundreds of companies — Fortune 10 through startups — rely on Tableau and Starschema to see, understand, and use their data to drive business results. Our Tableau solutions are engineered to bridge the gap between the out-ofthe-box Tableau capabilities and the needs of our Fortune 500 clients. These solutions are cost effective, and can rapidly and easily be implemented in the enterprise environment.

Producing high-value, high-volume pharmaceuticals on a 24/7 operational schedule means that breakdowns are time-consuming, interrupt production and are often extremely costly. Fortunately, data scientists and manufacturing specialists can examine production lines to determine what data can be used to predict future failures and how to best collect it.

When large organizations merge or divest, then new entity has business transformation thrust upon it. Our client, a power generation manufacturer, divested from a larger organization to become a brand-new company. With the looming deadline of a cut-over from the existing data platform, the client engaged Starschema to validate and test the existing technology stack and determine the best way to move forward.

Our client, a Fortune 100 company spanning multiple industries, operates a Tableau environment with thousands of users. To ensure optimum performance and provide great user experience, the client needed to gain a deep understanding of how their Tableau Server resources were being utilized.

Machine Learning models can be so complex that they seem like a magical black box with inputs and outputs, but little understanding of how the outputs are derived. In this white paper, we’ll explain the concept of interpretability and several methods to address the problems posed by black box models.

With Tableau’s Disaster Recovery method, large deployments can take 10+ hours to backup and same to restore. Even if you back up daily like you should, if disaster strikes you’ll lose a full day of productivity, and a full day of data. Palette Rescue ensures that your users are never interrupted by a server crash.

From recommender systems on streaming services to personal assistants like Siri or Alexa, ML is nearly everywhere today. This white paper demystifies Machine Learning for non-technical business stakeholders to better collaborate in, and derive more value from, data science initiatives.