Smart Data Collective
JULY 25, 2019
Not long ago, big data was one of the most talked about tech trends , as was artificial intelligence (AI). But, in case people need a reminder of how fast technology evolves , they only need to consider something newer — big data AI. It combines elements of both technologies. AI allows computers to perform cognitive functions, much like the human brain.
DataRobot Blog
JULY 9, 2019
by Jen Underwood. To retain market leadership in the algorithm economy, enterprises require new ways to maximize the value of data and AI with citizen data scientists. Don’t think citizen data science is. Read More.
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Dataiku
JULY 4, 2019
It's hard to know where to start once you’ve decided that yes, you want to dive into the fascinating world of data and AI. Just looking at all the technologies you have to understand and all the tools you’re supposed to master is enough to make your dizzy.
BA Learnings
JULY 18, 2019
I tend to describe the agile approach as a way of working; A targeted way of working that allows us to make changes, respond to customers’ needs and manage uncertainty with minimal delays, and without needing to wade through “red tape”. Agile manifesto encourages: - Customer collaboration over contract negotiation - Individuals and interactions over processes and tools - Responding to change over following a plan - Working software over full documentation This does not however imply that the agi
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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?
Jet Global
JULY 2, 2019
The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive. What was at first a data stream has morphed into a data river as enterprise businesses are harvesting reams of data from every conceivable input across every conc
Peter James Thomas
JULY 24, 2019
I was asked the question appearing in the title of this short article recently and penned a reply, which I thought merited sharing with a wider audience. Here is an expanded version of what I wrote: Let’s start by considering some related questions: Why are so many businesses still doing a bad job of controlling their costs in 2019? Why are so many businesses still doing a bad job of integrating their acquisitions in 2019?
Data Leaders Brief brings together the best content for data, strategy, and BI professionals from the widest variety of industry thought leaders.
Analytics Vidhya
JULY 31, 2019
Overview Managing the various stakeholders in a data science project is a must-have aspect for a leader Delivering an end-to-end data science project is. The post A Data Science Leader’s Guide to Managing Stakeholders appeared first on Analytics Vidhya.
datapine
JULY 17, 2019
Experts predict that by 2025, around 175 Zettabytes of data will be generated annually, according to research from Seagate. Moreover, within just five years, the number of smart connected devices in the world will amount to more than 22 billion – all of which will produce colossal sets of collectible, curatable, and analyzable data, claimed IoT Analytics in their industry report.
Smart Data Collective
JULY 30, 2019
In an earlier age, perhaps as little as a decade ago, businesses had to rely on intuition and educated guesses to guide their spending. The situation was famously captured by John Wanamaker, who said, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.” Today, data is everywhere. Phones track our locations and our social media usage.
Teradata
JULY 9, 2019
Integrated data and analytics has a proven track record of helping organize operations, enhance customer experience and improve revenue and market growth.
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Jet Global
JULY 11, 2019
With major advances being made in artificial intelligence and machine learning, businesses are investing heavily in advanced analytics to get ahead of the competition and increase their bottom line. One of those areas is called predictive analytics, where companies extract information from existing data to determine buying patterns and forecast future trends.
Corinium
JULY 7, 2019
Drawing on over 30 years of experience, we caught up with our international keynote, Cary Correia, Chief Commercial Data Scientist, GE USA to share some golden nuggets on how to truly achieve a data-driven culture and become an intelligent enterprise. See how Cary’s teams worked towards a data driven culture, the use of proactive and reactive analytics, and facilitating the most significant steps to move from strategy to execution.
Analytics Vidhya
JULY 21, 2019
Overview Mask R-CNN is a state-of-the-art framework for Image Segmentation tasks We will learn how Mask R-CNN works in a step-by-step manner We will. The post Computer Vision Tutorial: Implementing Mask R-CNN for Image Segmentation (with Python Code) appeared first on Analytics Vidhya.
datapine
JULY 11, 2019
The rise of innovative, interactive, data-driven dashboard tools has made creating effective dashboards – like the one featured above – swift, simple, and accessible to today’s forward-thinking businesses. In the digital age, there’s little need for a department of IT technicians, plus a qualified graphic designer, to create a dazzling data dashboard.
Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com
Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.
David Menninger's Analyst Perspectives
JULY 26, 2019
Alteryx Inspire 2019, this year's user conference for Alteryx, drew around 4500 customers, partners, and prospects to Nashville’s Gaylord Opryland Resort & Convention Center in Tennessee last month. The strong attendance was a reflection of the strong growth Alteryx has experienced over the last year; roughly 50% growth year-over-year. This year's conference focused on Alteryx's evolution from data preparation to AI and machine learning, and both were front and center.
Rocket-Powered Data Science
JULY 7, 2019
Career Relevance. Definitions of terminology frequently seen and used in discussions of emerging digital technologies. (NOTE: This page is a WIP = Work In Progress.). AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data).
O'Reilly on Data
JULY 18, 2019
The O’Reilly Data Show Podcast: Roger Chen on the fair value and decentralized governance of data. In this episode of the Data Show , I spoke with Roger Chen, co-founder and CEO of Computable Labs , a startup focused on building tools for the creation of data networks and data exchanges. Chen has also served as co-chair of O'Reilly's Artificial Intelligence Conference since its inception in 2016.
KDnuggets
JULY 29, 2019
Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.
Speaker: Jay Allardyce, Deepak Vittal, and Terrence Sheflin
As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.
Analytics Vidhya
JULY 10, 2019
Overview Presenting 21 open source tools for Machine Learning you might not have come across Each open-source tool here adds a different aspect to. The post 21 Must-Know Open Source Tools for Machine Learning you Probably Aren’t Using (but should!) appeared first on Analytics Vidhya.
datapine
JULY 3, 2019
In a hyper-connected digital world driven by data, there has never been a better time for businesses to gather meaningful insights on their target prospects, in addition to measuring ongoing levels of commercial growth and performance. The modern consumer, or digital native, craves a significant level of value from the brands in which they’re looking to invest – and as such, to gain consumer loyalty, businesses must reach out and talk to their customers on a personal level.
David Menninger's Analyst Perspectives
JULY 23, 2019
Summit 2019, Information Builders' annual user conference, drew about 1000 attendees this year, including customers, partners and prospects all working with Information Builders' technologies. Under new leadership, Summit 2019 showcased the direction Information Builders is moving in the next couple of years.
Domino Data Lab
JULY 9, 2019
Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way.
Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network
In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.
erwin
JULY 12, 2019
In light of recent, high-profile data breaches, it’s past-time we re-examined strategic data governance and its role in managing regulatory requirements. News broke earlier this week of British Airways being fined 183 million pounds – or $228 million – by the U.K. for alleged violations of the European Union’s General Data Protection Regulation (GDPR).
KDnuggets
JULY 26, 2019
Different neural network architectures excel in different tasks. This particular article focuses on crafting convolutional neural networks in Python using TensorFlow and Keras.
Analytics Vidhya
JULY 4, 2019
Overview Check out our pick of the top 24 Python libraries for data science We’ve divided these libraries into various data science functions, such. The post Don’t Miss out on these 24 Amazing Python Libraries for Data Science appeared first on Analytics Vidhya.
datapine
JULY 31, 2019
In a data-driven age, modern organizations need access to advanced data analytics solutions to help them improve the business in a wealth of key areas—Salesforce is one of those solutions. One of the world’s most popular cloud-based customer relationship management (CRM) platforms, the software is designed to help companies across sectors plan and optimize their sales processes.
Speaker: Christophe Louvion, Chief Product & Technology Officer of NRC Health and Tony Karrer, CTO at Aggregage
Christophe Louvion, Chief Product & Technology Officer of NRC Health, is here to take us through how he guided his company's recent experience of getting from concept to launch and sales of products within 90 days. In this exclusive webinar, Christophe will cover key aspects of his journey, including: LLM Development & Quick Wins 🤖 Understand how LLMs differ from traditional software, identifying opportunities for rapid development and deployment.
Smart Data Collective
JULY 9, 2019
Business success begins and ends with customer experience. According to recent studies, 90 percent of buyers would gladly spend more for a better customer experience. That’s exactly why understanding what an improved experience means for customers is so important. Companies have been able to perform more in-depth customer analysis—above and beyond social media commentary and feedback surveys—with the development and proliferation of analytics.
Domino Data Lab
JULY 10, 2019
Joshua Poduska provides a distilled overview of Ludwig including when to use Ludwig’s command-line syntax and when to use its Python API. Introduction. New tools are constantly being added to the deep learning ecosystem. It can be fun and informative to look for trends in the type of tools being created. For example, there have been multiple promising tools created recently that have Python APIs, are built on top of TensorFlow or PyTorch , and encapsulate deep learning best practices to allow d
MLWhiz
JULY 29, 2019
Data Science is the study of algorithms. I grapple through with many algorithms on a day to day basis so I thought of listing some of the most common and most used algorithms one will end up using in this new DS Algorithm series. This post is about some of the most common sampling techniques one can use while working with data. Simple Random Sampling Say you want to select a subset of a population in which each member of the subset has an equal probability of being chosen.
KDnuggets
JULY 24, 2019
Recently, researchers from the Google Brain team published a paper proposing a new method called Concept Activation Vectors (CAVs) that takes a new angle to the interpretability of deep learning models.
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