Tag: Hadoop

Feed: Teradata Blog. In the past I’ve heard some criticisms around Teradata’s founding “vision” -- criticisms that have been bolstered by the misperception that Teradata has admitted that its original vision of a “single store of business data” is no longer correct. Allow me to clear a few things up… Teradata started with the vision of “bring data together” so users could ask “any question of any data at any time.” At our heart we started as an analytic software company. We revolutionized a new paradigm of MPP software that was able to scale to (at the time) unfathomable amounts ... Read More

Feed: Actian. Author: Lewis Carr. And why is it better than a Data Lake or an Analytics Hub? In the opening installment of this blog series—Data Lakes, Data Warehouses and Data Hubs: Do we need another choice?  I explore why simply migrating these on-prem data integration, management, and analytics platforms to the Cloud does not fully address modern data analytics needs. In comparing these three platforms, it becomes clear that while all of them meet certain critical needs, none of them meet the needs of business end-users without significant support from IT. What we in fact need is a platform ... Read More

Feed: Big Data Made Simple. Author: Philip Piletic. The modern digital marketing industry simply couldn’t exist without the aggregation of huge amounts of data. That being said, the role that data plays in marketing has changed dramatically in the last few years. Some computer scientists are suggesting that many organizations that currently collect customer information will soon be unable to process the sheer amount of data they’re working with.Unfortunately, that means some companies have been reduced to guessing as opposed to actually using their data in a wise fashion. This, combined with the recent announcement that major marketing firms are ... Read More

Feed: Alation. Author: Venky Ganti, Ph.D.. Venky Ganti, Ph.D. December 22, 2015 — With the year coming to a close, many look back at the headlines that made major waves in technology and big data – from Spark to Hadoop to trends in data science – the list could go on and on. Looking in the rear-view mirror not only affords reflection, but can also show us what’s plausible for the year ahead. Considering what we’ve seen this year in industry trends and patterns, we have compiled some predictions for 2016 from our co-founders at Alation. Venky Ganti, CTO & Co-Founder: ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Alaa Mahjoub. Data and Analytics Platform is a sub platform of the Enterprise Digital Business Technology Platform. It contains information management and analytical capabilities. Introduction Building the digital business technology platform is a core aspect of enterprise endeavours to support its digital business transformation and therefore gain a sustainable competitive advantage. The digital business technology platform includes 5 building blocks: the information systems platform, the customer experience platform, the internet of things (IoT) platform, the ecosystem platform, and the data and analytics (D&A) platform. The D&A platform is located at the ... Read More

Feed: Planet MySQL; Author: Ronald Bradford; I learned this week that 30+ years of Relational Database Management System (RDBMS) experience still does not prepare yourself for the disappointment of working with organizations that use a RDBMS; MySQL specifically; have a released production product, have dozens to hundreds of developers, team leaders and architects, but do not know the importance of, nor use transactions. If I was to ask this when interviewing somebody that would work with a database and the response was it is not important, or not used these days it would be a hard fail. To use a ... Read More

Feed: Actian. Author: Lewis Carr. There’s a long-standing debate, dating back to the early days of Hadoop, about what kind of data repository is best for a given data analytics use case. A Data Lake? A Data Hub? A Data Warehouse? Despite Hadoop’s fall from grace, the debate not only persists but grows more complicated. Today’s cloud-based repositories, including AWS S3, Microsoft Azure ADLS, and Google Cloud Store, look very much like Data Lakes in the Cloud. Similarly, cloud-based offerings like Snowflake look very much like Enterprise Data Warehouses but in the cloud. Granted, for an apples-to-apples comparison for Data ... Read More

Feed: AWS Big Data Blog. Given the scalability of Amazon QuickSight to hundreds and thousands of users, a common use case is to monitor QuickSight group and user activities, analyze the utilization of dashboards, and identify usage patterns of an individual user and dashboard. With timely access to interactive usage metrics, business intelligence (BI) administrators and data team leads can efficiently plan for stakeholder engagement and dashboard improvements. For example, you can remove inactive authors to reduce license cost, as well as analyze dashboard popularity to understand user acceptance and stickiness. This post demonstrates how to build an administrative console ... Read More

Feed: Radar. Author: . Here are some of the most significant themes we see as we look toward 2021. Some of these are emerging topics and others are developments on existing concepts, but all of them will inform our thinking in the coming year. MLOps FTW MLOps attempts to bridge the gap between Machine Learning (ML) applications and the CI/CD pipelines that have become standard practice. ML presents a problem for CI/CD for several reasons. The data that powers ML applications is as important as code, making version control difficult; outputs are probabilistic rather than deterministic, making testing difficult; training ... Read More

Feed: Neo4j Graph Database Platform. Author: Enzo. Editor’s Note: This presentation was given by Dr. Jim Webber at GraphTour Boston in 2019.Full PresentationIf there’s any area of computer science that’s prone to nonsense today, it’s artificial intelligence. I’m going to walk you through some no-nonsense definitions of AI-cronyms, share my history with graphs and intelligent applications, and take a little peek into the future of graph AI.A Bluffer’s Guide to AI-cronymsArtificial intelligence (AI) is the property of a system that appears intelligent to its users. Machine learning (ML) is a branch of artificial intelligence that analyzes historical data to guide ... Read More