All Research Sponsored By:Dataiku
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Artificial Intelligence in Insurance: High-Value Use Cases
The growth of data science is driven by a variety of factors, including risk modeling. This white paper explores up-and-coming use cases for data science and machine learning in the insurance space, challenges traditional insurance companies face in implementing these use cases, and trends in how successful companies execute. Download a copy today.
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The AI Impact Survey Insights from More than 400 Data Professionals
Many data professionals have strong opinions about the ways in which AI will impact their industries, companies, and roles—but not all these opinions align with reality. Read this white paper to learn how data professionals expect AI to change their industry, as well as how to integrate these predictions into your business strategy.
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A Framework for Choosing the Right Use Cases
As hype around data science, machine learning, and AI continues to grow, more and more organizations are feeling the pressure to modernize their business.
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The State of the Market
In order to go in-depth on what exactly data science and machinelearning (ML) tools or platforms are, it's important to take a step back and understand where we are in the larger story of AI, ML, and data science in the context of businesses.
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Vendor Landscape for Data Science and Machine Learning Platforms
The number of data science platforms available has explosively gown along with the market. While that means that there is a remarkable number of data science platforms available, not all of these were created equal. Read this Gartner Magic Quadrant to learn which vendors are most likely to provide you with quality solutions.
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Follow 4 Data Science Best Practices to Achieve Project Success
Data science and machine learning initiatives (DSML) have exploded in popularity, yet many of these projects have surprising poor results despite continued investment. Read this Gartner report to learn the best practices that will help your data science program see sustained success and provide your organization with real insights.
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Trends in Enterprise Data Architecture and Model Deployment
To stay on the edge of business innovation, companies are investing in cloud and AI technology, among other innovations. But how prevalent are these trends? And do they produce real results? Read this analyst report what data architecture and model deployment trends are happening right now, and where companies plan to focus their data efforts next.
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The Data ROI Toolkit: How to Determine the Value of Your Data Initiatives
This white paper by Dataiku gauges your company’s ultimate ROI—balancing pros like time saved and reduced data expenditure against cons like workflow disruption and the cost of additional training. Download it to see ways that your company can make sure to improve your ROI and derive true value from your data.
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2020: What's Next for the Data-Driven Enterprise
Read this analyst report to learn the 6 AI trends to watch for in 2020 and beyond to make sure your organization is not left behind, as well as key factors that will evolve the role of the data scientist.
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Defining a Successful AI Project: how can organizations prioritize the right projects?
Leveraging a centralized data platform might be the secret to staying ahead of the technological curve. Access this white paper to read the 5 Ws and an H AI prioritization check list, learn how to avoid false starts on AI projects that are ill-defined, and achieve an environment of success.
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How to scale up AI competencies within organizations in the energy and utility industries.
Resource and utility companies that hope to remain competitive should be aggressively pursuing the next technological frontier. Access this white paper to learn the 3 immediate steps that companies looking to advance in the race to AI can take as well as some of the highest-value AI use cases to date.
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Innovative data strategies for smarter predictions
By leveraging a collaborative and flexible AI-based tool, Europcar was able to build a predictive web app as well as dashboards that forecasted market activity at a very granular level. Access this case study to learn more about the technology Europcar used and the positive impact the solution had.
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Machine Learning Applications for Banking Fraud Detection
AI-based systems can augment regulatory alert systems and improve analysts’ workflow by reducing noise without discarding results. Access this paper to view the 3 types of anomalies to look out for, understand examples of how banks use fraud and anomaly detection, and learn how to build a basic, machine learning-based fraud detection system.
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Fraud Detection in Healthcare: a step-by-step guide to incorporating machine learning
There are many AI-based use cases that span the healthcare industry, all with the goal of improving patient care. Access this white paper to learn the 3 basic types of anomalies that may be detected and to learn how to confront the challenges of fraud and anomaly detection with 4 AI and ML-based approaches.
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Data Architecture Basics: an Illustrated Guide for Non-Technical Readers
Don't assume that only CIOs or data architects should understand data structure, it's a skill that every member of an organization should be familiar with if true data democratization is the goal. Read this white paper for data architecture basics that can integrate any team member into the mission for data-driven decision-making.
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Data Science Operationalization
Read this white paper to find common ground between data science and IT teams for the benefit of your data and analytics projects as a whole by ensuring consistent packaging and deployment of models.
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How and Why IoT is Shifting Enterprise AI Strategy
Businesses will not be able to yield the full benefits of IoT integration without a better structure for their data and analytics—and this means mastering AI and ML too. Read this white paper to learn how to enable true innovation through data and IoT.
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Self-Service Analytics at GE Aviation: So Much More than BI
In the case of GE Aviation, they were able to boast innovative new products and huge efficiency boosts by implementing a self-service analytics solution—ensuring that all business efforts could be quantified at scale. Read this case study to learn how.
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Data Science, Machine Learning, AI Platforms: How & Why?
Ultimately, it's about saving time and getting organizations into the AI game sooner rather than later—read this white paper to learn more about data science and ML platforms and how they allow for more productive data initiatives.
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How to reach data maturity and become a data driven organization
CDOs can drive data strategy, support machine learning analysis, and generate business value with data. Read this white paper (including insights from over 50 CDOs worldwide) to learn how to create an organizational path to data leader success.
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Enabling AI Services Through Operationalization
Read this white paper to learn why operationalization and self-service analytics are key to a successful and pervasive data-driven business model.
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How To: Address Churn with Predictive Analytics
Churn is when a company loses a customer - and mostly every business will have to deal with this sooner than later, because it has the power to plateau growth. Read this white paper to learn how to use predictive analytics to predict and prevent customer loss.
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Executing Data Privacy-Compliant Data Projects
Dataiku has compiled a data privacy guidebook to keep companies regulation compliant while planning data storage or analytics initiatives by pitting myth vs. reality. Read it here.
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The Importance of AutoML for Augmented Analytics
Read this white paper to learn about the potential of augmented analytics & enterprise AI and the shifting role of the Data Scientist.
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Machine Learning Basics: An Illustrated Guide
This easy-to-read, entry-level e-book explains all the basics of machine learning, without the technical lingo that bogs it down. Read on for more information.