datapine

MAY 2, 2019

Modern dashboard software makes it simpler than ever to merge and visualize data in a way that’s as inspiring as it is accessible. But while doing so is easy, a great dashboard still requires a certain amount of strategic planning and design thinking. Knowing who your audience is will help you to determine what data you need. Knowing what story you want to tell (analyzing the data) tells you which data visualization type to use.

Visualization 173

Visualization Dashboards Sales KPI 173

Corinium

MAY 19, 2019

Ahead of the third Chief Data & Analytics Officer Singapore conference, we caught up with Murari Mohan, Assistant Vice President, Partnership Analytics, Business and Data Science,, NTUC Link to talk about moving from reactive analytics to proactive analytics, the cultural hurdles to be addressed in order to drive intelligent data strategies as well as the most significant steps to be taken to move from strategy to execution.

Analytics 150

Analytics Data Strategy Data Science Strategy 150

Analytics Vidhya

MAY 12, 2019

Introduction Data scientists spend close to 70% (if not more) of their time cleaning, massaging and preparing data. That’s no secret – multiple surveys. The post A Beginner’s Guide to Tidyverse – The Most Powerful Collection of R Packages for Data Science appeared first on Analytics Vidhya.

Data Science 307

Data Science Analytics Visualization 307

O'Reilly on Data

MAY 23, 2019

The O’Reilly Data Show Podcast: Jike Chong on the many exciting opportunities for data professionals in the U.S. and China. In this episode of the Data Show , I spoke with Jike Chong , chief data scientist at Acorns , a startup focused on building tools for micro-investing. Chong has extensive experience using analytics and machine learning in financial services, and he has experience building data science teams in the U.S. and in China.

Machine Learning 232

Machine Learning Data Science Management Analytics 232

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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?

Business Intelligence

David Menninger's Analyst Perspectives

MAY 20, 2019

The emerging internet of things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any appropriately designed device can generate and transmit data about its operations, which can facilitate monitoring and a range of automatic functions.

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Internet of Things IoT Analytics Optimization 208

ScienceSoft

MAY 10, 2019

Explore five different types of artificial intelligence (AI) – analytic, interactive, text, visual and functional – and get inspired by real-life business examples of AI in action.

Visualization 110

Visualization Interactive Analytics 110

Corinium

MAY 27, 2019

With the rise of new data streams, the ability to access more data and derive insights from it more quickly is critical. By 2023, worldwide revenue for big data solutions will reach $260 billion.* Download our new 3 Benefits of a Self-Adapting Data Warehouse ebook to learn how analytics leaders leverage technology shorten time to value for their data.

Data Warehouse 150

Data Warehouse Machine Learning Big Data Optimization 150

Analytics Vidhya

MAY 19, 2019

This article was submitted as part of Analytics Vidhya’s Internship Challenge. Introduction I’m an avid YouTube user. The sheer amount of content I can. The post Data Science Project: Scraping YouTube Data using Python and Selenium to Classify Videos appeared first on Analytics Vidhya.

Data Science 303

Data Science Analytics Machine Learning Data Collection 303

O'Reilly on Data

MAY 9, 2019

The O’Reilly Data Show Podcast: Jeff Jonas on the evolution of entity resolution technologies. In this episode of the Data Show , I spoke with Jeff Jonas , CEO, founder and chief scientist of Senzing , a startup focused on making real-time entity resolution technologies broadly accessible. He was previously a fellow and chief scientist of context computing at IBM.

Marketing 202

Marketing Technology 202

David Menninger's Analyst Perspectives

MAY 1, 2019

About 10 years ago, social media tools like Facebook, Twitter and LinkedIn introduced a wave of collaborative analytics and BI capabilities. We saw chat streams associated with specific analyses that users could like or endorse. The number of contributions a user made to the community was part of his or her profile so others could accordingly weigh the importance of the input.

Analytics 191

Analytics Business Intelligence Technology 191

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Data-driven

Domino Data Lab

MAY 15, 2019

This Domino Data Science Field Note covers Pete Skomoroch ’s recent Strata London talk. It focuses on his ML product management insights and lessons learned. If you are interested in hearing more practical insights on ML or AI product management, then consider attending Pete’s upcoming session at Rev. Machine Learning Projects are Hard: Shifting from a Deterministic Process to a Probabilistic One.

Machine Learning 111

Machine Learning Management Experimentation Uncertainty 111

datapine

MAY 28, 2019

BI projects aren’t just for the big fishes in the sea anymore; the technology has developed rapidly, the software has become more accessible while business intelligence and analytics projects implemented in various industries regularly, no matter the shape and size, small businesses or large enterprises. With the help of online data analysis tools , these kinds of projects have become easy to manage and agile in performance.

Business Intelligence 317

Business Intelligence KPI Dashboards Reporting 317

Corinium

MAY 27, 2019

Industry 4.0…. it is just a buzz word thrown about? What does it actually mean? And how does it have an impact? We went straight to the source and asked the founding father and driving force behind the Industry 4.0 workgroup- Henrik von Scheel. What exactly is the Fourth Industrial Revolution?

IT 150

IT 150

Analytics Vidhya

MAY 2, 2019

Introduction What is one of the most important and core concepts of statistics that enables us to do predictive modeling, and yet it often. The post Statistics 101: Introduction to the Central Limit Theorem (with implementation in R) appeared first on Analytics Vidhya.

Statistics 300

Statistics Predictive Modeling Modeling Analytics 300

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.

Marketing

O'Reilly on Data

MAY 1, 2019

Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Continue reading Sustaining machine learning in the enterprise.

Machine Learning 203

Machine Learning Enterprise 203

David Menninger's Analyst Perspectives

MAY 13, 2019

Organizations now must store, process and use data of significantly greater volume and variety than in the past. These factors plus the velocity of data today — the unrelentingly rapid rate at which it is generated, both in enterprise systems and on the internet — add to the challenge of getting the data into a form that can be used for business tasks.

Business Analytics 180

Business Analytics Big Data Analytics Enterprise 180

Smart Data Collective

MAY 20, 2019

We’re well past the point of realization that big data and advanced analytics solutions are valuable — just about everyone knows this by now. In fact, there’s no escaping the increasing reliance on such technologies. Big data alone has become a modern staple of nearly every industry from retail to manufacturing, and for good reason. IDC predicts that if our digital universe or total data content were represented by tablets, then by 2020 they would stretch all the way to the moon over six times.

Analytics 111

Analytics Machine Learning Business Intelligence Big Data 111

datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips. According to Better Buys, 85% of business leaders feel that using big data to their advantage will significantly improve the way they run their companies – and they’re not wrong.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

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.

Business Intelligence

Corinium

MAY 26, 2019

Ahead of the Chief Customer Officer New Zealand conference, we caught up with Phillipa Cameron, Chief Customer Officer at Stuff NZ to discuss the biggest challenges she faces in her role, and how to tackle them, how she has encouraged Stuff NZ to be more collaborative as well as how a shift to be more customer focused has impacted the organisation.

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150

Analytics Vidhya

MAY 7, 2019

Introduction I love descriptive statistics. Visualizing data and analyzing trends is one of the most exciting aspects of any data science project. But what. The post Extracting and Analyzing 1000 Basketball Games using Pandas and Chartify appeared first on Analytics Vidhya.

Statistics 296

Statistics Visualization Data Science Analytics 296

O'Reilly on Data

MAY 1, 2019

Watch highlights from expert talks covering machine learning, predictive analytics, data regulation, and more. People from across the data world are coming together in London for the Strata Data Conference. Below you'll find links to highlights from the event. Making the future. James Burke asks if we can use data and predictive analytics to take the guesswork out of prediction.

Advertising 192

Advertising Machine Learning Predictive Analytics Data-driven 192

David Menninger's Analyst Perspectives

MAY 6, 2019

I am happy to share some insights gleaned from our latest Value Index research, which provides our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Collaborative Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. Drawing on our benchmark research and expertise, we apply a structured research methodology built on evaluation categories that are designed to reflect t

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Analytics Business Intelligence ROI Software 167

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.

Data-driven

Data Science 101

MAY 20, 2019

I took and passed the exam during the beta period. These are my memories of the topics on the exam. You can get this information as the Microsoft Azure Data Scientist Checklist. General Overview. Below is the basic structure of the DP-100: Designing and Implementing a Data Science Solution on Azure. Passing the exam will qualify you for the Azure Data Scientist Associate certification.

Data Science 111

Data Science Machine Learning Deep Learning Testing 111

datapine

MAY 29, 2019

Effective decision-making processes in business are dependent upon high-quality information. That’s a fact in today’s competitive business environment that requires agile access to a data storage warehouse , organized in a manner that will improve business performance, deliver fast, accurate, and relevant data insights. BI architecture has emerged to meet those requirements, with data warehousing as the backbone of these processes.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

Corinium

MAY 22, 2019

Over it's lifetime Facebook has become possibly the biggest B2C/B2B marketing channel available to marketers. The platform is a mass generator of big customer data that holds immense potential value for making smarter marketing decisions.

Marketing 150

Marketing B2B Data Science IT 150

Analytics Vidhya

MAY 5, 2019

Introduction “How did your neural network produce this result?” This question has sent many data scientists into a tizzy. It’s easy to explain how. The post A Guide to Understanding Convolutional Neural Networks (CNNs) using Visualization appeared first on Analytics Vidhya.

Visualization 296

Visualization Analytics Deep Learning IT 296

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.

Sales

O'Reilly on Data

MAY 2, 2019

Sandra Wachter argues that a right to reasonable inferences could protect against new forms of discrimination. Continue reading Privacy, identity, and autonomy in the age of big data and AI.

Big Data 134

Big Data 134

David Menninger's Analyst Perspectives

MAY 3, 2019

Domopalooza 2019 marked the first annual user conference after Domo went public, but the energy, excitement and new feature announcements have not slowed. With thousands in attendance and growing fast, this year's conference focused on five key areas: digitization, real time connectivity, driving insight based actions, applying AI & machine learning, and building applications.

IoT 160

IoT Machine Learning Data Integration Business Intelligence 160

Smart Data Collective

MAY 2, 2019

Large companies around the world are investing in big data. Big data has been especially important for optimizing their marketing campaigns. However, a number of small businesses are getting in on the action too. Local marketing agencies have discovered that SEO is more dependent on big data than ever. They are developing more data driven solutions to offer better search marketing strategies.

Big Data 111

Big Data Optimization Modeling Deep Learning 111

datapine

MAY 21, 2019

“BI is about providing the right data at the right time to the right people so that they can take the right decisions” – Nic Smith. Data analytics isn’t just for the Big Guys anymore; it’s accessible to ventures, organizations, and businesses of all shapes, sizes, and sectors. The power of data analytics and business intelligence is universal.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

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Visualization