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Learn how to design and implement a complex solution that automatically identifies anomalies in organizational data, provides relevant context and communicates it all in an easy-to-consume form to augment analysts' work.
This white paper goes beyond cloud providers' documentation to introduce best practices that will help your organization ensure a comprehensive security solution for a cloud environment at optimal long-term cost.
Geolocation data provides invaluable insights into the habits and preferences of users, customers and audiences. This white paper helps understand the fundamental opportunities and challenges inherent in using location data for business-critical processes in any industry.
For businesses seeking to grow their competitive advantage, the challenge today is clear: build more and better digital products while relying less on large teams and deep technical expertise. This white paper looks at why and how you should think about data platform modernization to achieve speed at scale with fewer resources.
Forward-thinking organizations see investing in a Tableau license as just the start. They realize that customizing your Tableau deployment to your unique use cases is the key to making the most of the platform, and one way to do this is to streamline the communication and write-back processes to optimize workflows.
AI is transforming healthcare, unlocking unprecedented opportunities for enabling easier discovery of deeper insights that drive innovation – but the available technologies can very greatly in their maturity and domain-specific applicability. This white paper introduces five proven, future-resilient solutions to challenges that healthcare providers face today.
Topic modeling enables the analysis of text-based data to leverage insights that are difficult to extract and understand to help you optimize costs, improve operations and drive innovation. Read this white paper to understand the fundamentals of topic modeling and learn how to get started implementing it.
Cloud opens up a wealth of opportunities and can drastically reduce operational costs in the long-term — especially if you know where to look. This white paper introduces the most common strategies for ensuring that you get the most value from your move to the cloud.
Using ML to effectively target the right customer at the right time with the right information can make a big difference in how effective your campaign is. This short white paper discusses some of the approaches and demonstrates how one company achieved a 6x uplift in conversions by apply ML to customer targeting.
For many businesses, demand planning is essential. Profitability, cash flow, and customer satisfaction and retention all hinge on getting this right. This white paper will introduce latent matrix factorization to model demand curves and discuss how it can be used to achieve these outcomes.
Healthcare Information Technology (HIT) is an indispensable part of managing and delivering healthcare services but patient data handling is highly regulated, presenting a challenge to practitioners. Learn how Starschema HealthLake can ensure compliance with the U.S. Health Insurance Portability and Accountability Act (HIPAA) while streamlining analytics.
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.
Opening the Black Box - Learn how to think about AI and thrive in data-driven cultures of today and tomorrow
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,
Eszter Windhager-Pokol, Starschema head of data science, explains the concept of interpretability and several methods to address the problems posed by black box models.
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. A recent (2018) report on the manufacturing industry saw 31% of manufacturing CEOs expecting artificial intelligence and machine learning to contribute to a reduction in operating costs. Learn how predictive maintenance helps make this reality.