The Ultimate Guide to Data Visualization

“The Ultimate Guide to Data Visualization” eBook by Inzata, discusses how data visualization is all about communication. With clear, easy to read charts and visuals, the information can be effectively read and understood. This guide discusses the different types of visualizations, the appropriate time to use each one, and how to design visuals that will […]

Machine learning for all: the democratizing of a technology

In this short eBook, you’ll discover automated machine learning using H2O.ai. H2O.ai has dedicated itself to democratizing all aspects of AI, including machine
learning. H2O Driverless AI is a machine learning solution that automates AI for nontechnical
users. So-called “AutoML” solutions like H2O Driverless AI are rising in popularity for enterprises across a wide range of industries. With it, users can build robust, fast, and accurate machine learning solutions. It also includes visualization and interpretability features that explain the data modeling results in plain English, fostering further adoption and trust in AI.

Overcoming Obstacles to Machine Learning Adoption

This is a new Business Impact Brief from 451 Research sponsored by H2O.ai – “Overcoming Obstacles to Machine Learning Adoption.” After many fits and starts, the era of enterprise machine learning has finally arrived. According to 451 Research’s Voice of the Enterprise, AI and Machine Learning survey, 20% of enterprises have already deployed the technology and a further 33% plan to do so within one year.

Chief Data Officer Survey and Research Results

Exasol released the findings of a survey of nearly 1,000 IT directors in the US, UK and Germany about their organization’s use of data and the role of Chief Data Officers (CDO) in their organizations. The survey found – among other things – that 72% of businesses worry that their inability to generate insights through the analysis of data will have a negative impact on financial performance.

AI in the Enterprise: Trends & Insights on Vendor Selection and Implementation

A new report was released by our friend over at Leverton, a data extraction startup recently acquired by MRI Solutions, titled “AI in the Enterprise: Trends & Insights on Vendor Selection and Implementation.” The report lends insight into the experiences and preferences of “leaders,” “lookers,” and “laggards” (defined below) when it comes to AI deployment.

Diffbot State of Data Science, Engineering & AI Report – 2019

Diffbot, the AI startup with more knowledge than Google, released a new report on the state of the data science industry. The company developed the report using the Diffbot Knowledge Graph, an AI-curated, structured database of all of the public information on the web. Key findings include: IBM is leading in workforce size across all […]

Future of Data Talent Report

Correlation One released its Future of Data Talent Report, which helps organizations: Define a framework to identify the most important data workflows and roles. Establish a standard assessment methodology for accurately and efficiently evaluate data skills when hiring.

Darwin Efficacy Report: Accelerating Data Science at Scale by Automation

Darwin, a machine learning platform, accelerates data science at scale by automating the building and deployment of models. It provides a productive environment that empowers data scientist with a broad spectrum of experience to quickly prototype use cases and develop, tune, and implement machine learning applications in less time. Download the latest white paper from SparkCognition that compares how Darwin performs against other platforms in the market on the same datasets.

Alternative Data for Investment Management

From hedge fund managers to mutual funds and even private equity managers, alternative data has the power to improve valuation of securities and boost the clarity of the investment process.  Techniques like natural language processing and machine learning allow organizations to better capitalize on alternative data. These technologies enable processing of large, heterogenous, and unstructured sets at an extremely fast rate. A new report from SparkCognition explores the challenges for alternative data adoption, how to overcome them, and explores the potential of automation.

Accelerating SQL and BI Analytics — Extending Analytical BI with a GPU Database

Organizations worldwide are facing the challenge of effectively analyzing their exponentially growing data stores. Download the new white paper from SQream DB that explores the features that make GPU databases ideal for BI and incorporates real-world use-cases from actual customer implementations. It also explains how you can turn your existing BI pipeline into a more capable, next-generation big data analytics system using powerful GPU technology.