In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs. To address this, a next-gen cloud data lake architecture has emerged that brings together the best attributes of the data warehouse and the data lake.

This guide identifies the biggest challenges for associations moving their training online and provides practical solutions so that you can hit the ground running. Download now to keep your members engaged and growing even in times of COVID-19.

Data Robot

Capitalizing on the incredible potential of AI means having a coherent AI strategy that you can operationalize within your existing processes. But it’s not always easy for organizations to do. In our 10 Keys to AI Success in 2021 eBook, we draw from the engaging conversations we’ve had with guests on our More Intelligent Tomorrow podcast series to show how organizations are overcoming hurdles and realizing the enormous rewards that AI can bring to any organization.

Data Robot

Many organizations are dipping their toes into machine learning and artificial intelligence (AI). However, for most organizations embarking on this transformational journey, the results remain to be seen. And for those who are already underway, scaling their results across their organizations is completely uncharted waters. Machine Learning Operations (MLOps) allows organizations to alleviate many of the issues on the path to AI with ROI by providing a technological backbone for managing the mac

Data Robot

You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. But rapid change, vendor churn, hype and jargon make it increasingly difficult to choose an AI vendor. This report explores why it is so challenging to choose an AI vendor and what you should consider as you seek a partner in AI.

Data Robot

While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? Renowned author and professor Tom Davenport conducted an in-depth study (sponsored by DataRobot) on how organizations have become AI-driven using automated machine learning. In this white paper, Davenport explains the rise of automated machine learning, its benefits, and success stories from businesses that are already using it to reali

As more businesses embrace online channel communications, the opportunity to unlock audio data increases. Regardless of whether you are evaluating Automatic Speech Recognition (ASR) solutions to get more value out of your call center data, build the next game-changing voice feature, or are just looking to save a lot of money on speech transcription, Deepgram is the platform to get you there.

There is a fundamental difference between 1st generation, 2nd generation, and modern-day Automatic Speech Recognition (ASR) solutions that use 100% deep learning technology. Get the information you need to ensure your evaluation experience is efficient and yields the data you need to make your purchasing decision. In this solution brief, you will learn: The differences between 1st generation, 2nd generation, and modern-day ASR solutions.

Until recently, the only way to accurately produce real-time audio transcription has been to employ voice writers to convert audio to text using dictation software and clean up the transcript before producing the final output. Today, many companies are deploying automatic speech recognition in place of voice writers. Learn about the key steps you can implement to advance your transcription pipeline.

Datadog

In this eBook, find out about the benefits and complexities of migrating workloads to AWS, and dive into services that AWS offers for containers and serverless computing. Find out the key performance metrics for each service to track in order to ensure workloads are operating efficiently. Lastly, learn how a monitoring solution like Datadog can easily track every stage of a migration to AWS as well as the performance of each of your AWS services side-by-side.

Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data. In this paper, we explore the top considerations for building a cloud data lake including architectural principles, when to use cloud data lake engines and how to empower non-technical

Cloud data lake engines aspire to deliver performance and efficiency breakthroughs that make the data lake a viable new home for many mainstream BI workloads. This guide describes how to evaluate cloud data lake engine offerings based on their ability to deliver on their promise of improving performance, data accessibility, and operational efficiency as compared with earlier methods of querying the data lake.

Datadog

In this eBook, Danny Miles, CTO of Dollar Shave Club, reveals an efficient framework for thinking about and prioritizing the performance metrics that matter most to him, providing a blueprint for fellow e-commerce CTOs to follow as they evaluate their own business.

Download this whitepaper to learn what contextual analytics is, how BI platforms like Yellowfin revolutionize the way users discover insights from their data with native contextual analytics, and how it adds value to your software solution by elevating the user experience. This whitepaper will help you understand: What contextual analytics can do to elevate the value of your application.

This whitepaper discusses how automated business monitoring solutions like Yellowfin Signals revolutionize the way users discover critical and relevant insights from their data. Download to learn: 5 business benefits of automated data discovery with ABM. The evolution of dashboards to automated business monitoring. How automated business monitoring separates insights from noise.

This report is designed to help readers select an embedded analytics product. It provides 12 criteria to consider when evaluating embedded capabilities. It also comes with a companion spreadsheet that enables users to score and compare products along these 12 dimensions and others they may add.

Datadog

In this eBook from Datadog, Orderbird CTO Frank Schlesinger tells the story of the company’s journey from 99.9% uptime to 99.99% uptime. He explains why this seemingly small improvement is actually a major leap and describes the five key steps to get there.

Selecting a graph database is an important decision that can shape the success of your organization. This guide is intended to assist your buying decision with side-by-side comparisons of graph databases from Amazon, DataStax, Neo4j, and TigerGraph.