This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
Ahead of the third Chief Data & Analytics Officer (CDAO) Singapore conference, we caught up with Melecio Valerio Jr, Head, Data Strategy and Governance at FWD Life Insurance to discuss the key strategies for managing massive volumes of data, the cornerstones for building a data driven enterprise as well as how to best roll out an enterprise-wide data management program.
by Jen Underwood. So many buzzwords, so much confusion. Automated analytics, artificial intelligence (AI)-driven BI, and automated machine learning (AutoML), aren’t these terms describing the exact same thing? NO. Although these technologies may. Read More.
Introduction We are currently in the midst of a global fitness revolution. Most of the people I know are geeking out over the latest. The post How I Built Animated Plots in R to Analyze my Fitness Data (and you can too!) appeared first on Analytics Vidhya.
The O’Reilly Data Show Podcast: Neelesh Salian on data lineage, data governance, and evolving data platforms. In this episode of the Data Show , I spoke with Neelesh Salian , software engineer at Stitch Fix , a company that combines machine learning and human expertise to personalize shopping. As companies integrate machine learning into their products and systems, there are important foundational technologies that come into play.
AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.
A few years ago, I generated a list of places to receive data science training. That list has become a bit stale. So, I have updated the list, adding some new opportunities, keeping many of the previous ones, and removing the obsolete ones. Here are 30 training opportunities that I encourage you to explore: The Booz Allen Field Guide to Data Science NVIDIA Deep Learning Institute Metis Data Science Training Leada’s online analytics labs Data Science Training by General Assembly Learn Data Scienc
In today’s business world, competition is fierce across all industries and sectors, which means that to survive and thrive, working with measurable online data analysis and performance metrics is essential. Studies suggest that by 2020, customer experience (CX) will be the main brand differentiator (according to a research conducted by the customer experience consultant company Walker), surpassing factors such as price and product in terms of importance to today’s digitally native consumers.
Introduction I was intrigued going through this amazing article on building a multi-label image classification model last week. The data scientist in me started. The post Predicting Movie Genres using NLP – An Awesome Introduction to Multi-Label Classification appeared first on Analytics Vidhya.
Introduction I was intrigued going through this amazing article on building a multi-label image classification model last week. The data scientist in me started. The post Predicting Movie Genres using NLP – An Awesome Introduction to Multi-Label Classification appeared first on Analytics Vidhya.
Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Can you tell me a bit more about your role at Protegrity? I am head of Products here, which comprises of R&D, Product Management and Global Customer support.
Resolving the volatility problem will unlock the groundwork needed for blockchain-based global payment systems. For cryptocurrency enthusiasts, the long game of blockchain ecosystems is to create open platforms controlled by no single authority, inviting open participation from anyone. This, of course, is in an effort to move forward the culture of open source, from static code branches sitting in source trees to living and evolving useful systems ready for live interaction, still egalitarian an
Though the Agile Methodology is used heavily in software development domains, it has since spread into different sectors. With Agile comes a growing emphasis on equipping the development team, e.g. your software developers, content writers, engineers, designers, etc, with the information, tools, and direction they need to produce a tangible output within a fixed period of time, that is, sprints of typically 2 weeks.
Introduction How do computer vision techniques work in an industry setting? How does an organization use data engineering to scale up its operations? These. The post DataHack Radio #22: Exploring Computer Vision and Data Engineering with Dat Tran appeared first on Analytics Vidhya.
Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage
When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m
Data privacy laws around the world are changing and the new laws have teeth. They recognize the rights of consumers to own and control their own data. And they hold enterprises unequivocally accountable for protecting personal data, thus creating a huge burden of compliance. Are you responsible for data innovations or data decisions at your company?
. When you’re presenting data analytics or any technical information to a non-technical audience, it can be difficult. You have to think about the components of a good presentation in general, but also how to simplify complex subjects and information and make them resonate with your target audience. If you’re someone who understands data analytics well or is highly technical, it can be especially challenging to know how to make your presentation work for the needs of an audience which is differ
In organizations that operate without a data warehouse or separate analytical database for reporting, the only source of the latest and up-to-date data may be in the live production database. When querying a production database, optimization is key. An inefficient query may pose a burden on the production database’s resources, and cause slow performance or loss of service for other users if the query contains errors.
While it is not one of the popular programming languages for data science, The Go Programming Language (aka Golang) has surfaced for me a few times in the past few years as an option for data science. I decided to do some searching and find some conclusions about whether golang is a good choice for data science. Popularity of Go and Data Science. As the following figure from Google Trends demonstrates, golang and data science became trendy topics at about the same time and grew at a similar rate
The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.
Big data is playing a massive role in the formation of new technologies. New developments in data science have contributed to the release of a number of popular Android apps on the market. To the average Android user, big data is an invisible factor. However, it is the foundation of almost every app on their phone. It is important to evaluate its significance.
For decades now, the professional world has put a great deal of energy into discussing the gulf that exists between business and IT teams within organizations. They speak different languages, it’s been said, and work toward different goals. Technology plans don’t seem to account for the reality of the business, and business plans don’t account for the capabilities of the technology.
Microsoft Azure has an abundance of data science capabilities (and non-data science capabilities). It can be challenging to keep up with the latest updates/releases. Luckily, Azure has a page to let you know exactly what has changed. You just need to know where to find it, and the following video will help you find that page. Also, if you are still interested in earning a Microsoft Data Science Certification , join the Study Group.
GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.
At Dorchester Collection of ultra-luxury hotels, we use big data and analytics to help us improve our guest o?erings and marketing. Our tool, Metis, analyzes data from online reviews and social media to uncover problems and opportunities. But, as the Dorchester Collection’s director of global guest experience and innovation, I’ve discovered that often the data can only tell you where there’s a problem, not why it exists, or how to ?
Influencers are rapidly transforming the digital marketing landscape. Nearly two out of five plan to increase their influencer marketing budgets substantially in the coming year. Only 7% of respondents in a recent poll spent less than $10,000 on influencer marketing. However, many brands are still struggling to cultivate their ideal influencer marketing strategy.
At Teradata, we think a lot about our customers in the cloud, and continue on our promise to deliver choice and flexibility by adding new as-a-service options for Teradata Vantage.
ZoomInfo customers aren’t just selling — they’re winning. Revenue teams using our Go-To-Market Intelligence platform grew pipeline by 32%, increased deal sizes by 40%, and booked 55% more meetings. Download this report to see what 11,000+ customers say about our Go-To-Market Intelligence platform and how it impacts their bottom line. The data speaks for itself!
Analysts are eager to dive into new challenges, but you've only got part of the picture if you don't have all the information necessary to understand new industries and technologies. That's why we assembled a set of free resources for analysts to activate their data science and machine learning expertise.
Manufacturing is a more powerful and essential part of our industries and economies than ever. But setting these vital enterprises up for maximum success and unrivaled innovation takes information — and that means gathering data. If you represent a manufacturing concern and you’re wondering about the benefits of capturing and analyzing operational data , you’ve come to the right place.
Evolving from departmental, small-group AI projects to an enterprise data science platform can put your business on a path to significant competitive advantage. Those who don’t seize the opportunity risk falling behind the curve. But some might not be sure how to begin. If you’re interested in learning how to get going, our publication, A business guide to modern predictive analytics, is great place to start.
To thoroughly, accurately, and clearly inform, we must identify the intended signal and then boost it while eliminating as much noise as possible. This certainly applies to data visualization, which unfortunately lends itself to a great deal of noise if we’re not careful and skilled. The signal in a stream of content is the intended message, the information we want people to understand.
Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.
We’re happy to announce the new V4 release of our popular DataRobot tools for Alteryx. We’ve taken the feedback from hundreds of customers and partners to incorporate even more robust functionality into the connectors.
Many people believe that digital media is rapidly replacing traditional forms of branding. They believe that advances in big data have made business cards, brochures and direct mail marketing obsolete. Nothing could be further from the truth. We previously published an article on the state of direct mail marketing. We showed that marketers are actually using big data to improve the performance of their direct mail marketing campaigns.
It's well-established that customer retention is much less expensive than customer acquisition. Therefore, preventing churn is a priority for nearly every company. A vital part of a viable strategy for preventing churn is the effective use of data. Let’s look at the role predictive analytics can play in that strategy.
Deep and rich search results are paramount for thorough and accurate analysis across enterprise information systems. In this article you will read why and how SPARQL queries make for a better search and are of immense help when it comes to accessing all the independently designed and maintained datasets across an organization (and outside it) in an integrated way.
Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?
We organize all of the trending information in your field so you don't have to. Join 42,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content