Corinium

MAY 15, 2019

64% of C-level exes said that AI and machine learning would improve customer and agent experience.

Machine Learning 150

Machine Learning 150

Analytics Vidhya

MAY 14, 2019

Introduction We have worked on plenty of drag-and-drop tools in our business intelligence (BI) journey. But none has come close to matching the Swiss. The post 10 Useful Data Analysis Expressions (DAX) Functions for Power BI Beginners appeared first on Analytics Vidhya.

Business Intelligence 290

Business Intelligence Analytics Visualization 290

Dataiku

MAY 13, 2019

It's no secret that introducing data science, machine learning, automation, and (eventually) AI into the world of marketing will be a critical factor to success. Yet it also means a fair bit of change not only at the tactical and organizational levels, but also at a personal level with the skills marketers will need to have to execute. But it doesn't mean all marketers need to become data scientists overnight - instead, the answer is collaboration.

Marketing 104

Marketing Machine Learning Data Science IT 104

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

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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.

Optimization

datapine

MAY 14, 2019

“Big data is at the foundation of all the megatrends that are happening.” – Chris Lynch, big data expert. We live in a world saturated with data. At present, around 2.7 Zettabytes of data are floating around in our digital universe, just waiting to be analyzed and explored, according to AnalyticsWeek. By gaining the ability to understand, quantify, and leverage the power of online data analysis to your advantage, you will gain a wealth of invaluable insights that will help your business flourish

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

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

Corinium

MAY 14, 2019

I spent 7 years working for one of the biggest commercial conference companies. It was led by an extremely astute CEO who actually started the business under Jack Welch and then broke away with it. So when he offered business advice it was time to listen, absorb and use.

IT 150

IT 150

datapine

MAY 16, 2019

The restaurant industry is one of the most competitive sectors on the planet. Not only do we as a species need to eat and drink to survive; communal dining is an experience that people have cherished for centuries. And as we love to dine out whenever we can, there is a great deal of demand for restaurants in villages, towns, and cities across the planet.

Analytics 163

Analytics Predictive Analytics Advertising Dashboards 163

Analytics Vidhya

MAY 15, 2019

Introduction “You can’t prove a hypothesis; you can only improve or disprove it.” – Christopher Monckton Every day we find ourselves testing new ideas, The post Statistics for Data Science: Introduction to t-test and its Different Types (with Implementation in R) appeared first on Analytics Vidhya.

Statistics 280

Statistics Testing Data Science IT 280

DataRobot

MAY 15, 2019

Art is subjective and everyone has their own opinion about it. When I saw the expressionist painting Blue Poles , by Jackson Pollock, I was reminded of the famous quote by Rudyard Kipling, “It’s clever, but is it Art?” Pollock’s piece looks like paint messily spilled onto a drop sheet protecting the floor. The debate of what constitutes art has a long history that will probably never be settled, there is no definitive definition of art.

IT 107

IT 107

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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

Smart Data Collective

MAY 15, 2019

Big data has created both positive and negative impacts on digital technology. On the one hand, big data technology has made it easier for companies to serve their customers. On the other hand, big data has created a number of security risks that they need to be aware of, especially with brands leveraging Hadoop technology. Big data has created a number of security risks for Bluetooth users.

Big Data 93

Big Data Risk Measurement Data mining 93

IBM Big Data Hub

MAY 15, 2019

Streams v5.0 for IBM Cloud Private for Data (ICP for Data) provides a real-time engine within our data platform. The platform simplifies bringing artificial intelligence (AI) into your enterprise processes.

Enterprise 88

Enterprise 88

erwin

MAY 16, 2019

The only thing that’s constant for most organizations is change. Today there’s an unprecedented, rapid rate of change across all industry sectors, even those that have been historically slow to innovate like healthcare and financial services. In the past, managing ideation to the delivery of innovation was either not done or was relegated within organizational silos, creating a disconnect across the business.

Enterprise 87

Enterprise Cost-Benefit Management Technology 87

Insight

MAY 16, 2019

Computer vision is a rapidly growing field in the technology and computer science world. It is a high-level, multifaceted field that allows machines to iteratively learn and understand complex representations from images and videos to automate human visual tasks. More recently, companies like Amazon opened a cashier-less grocery store that uses computer vision and deep learning to automatically detect which items are taken off the shelf.

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

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📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

Data-driven

Smart Data Collective

MAY 15, 2019

Big data has opened a number of doors for marketers. One of the most overlooked benefits of big data is that it allows marketers to translate documents from one language to another. Memsource shows that big data is revolutionizing translation solutions , primarily due to the advent of more sophisticated cloud language platforms and machine learning capabilities.

Big Data 92

Big Data Marketing Machine Learning Advertising 92

IBM Big Data Hub

MAY 16, 2019

Companies are entering “chapter two” of their digital transformation. The next chapter is all about moving from experimentation to true transformation. It’s about gaining speed and scale. We are helping businesses activate data as a strategic asset, with desire to maximize the impact of AI as core to the business strategy.

Experimentation 83

Experimentation Data Science Digital Transformation Modeling 83

Dataiku

MAY 17, 2019

Hype around AI means that more and more, businesses are dedicating huge sums of money to assembling large data teams and setting them loose, hoping they produce results on their own. Often, they are disappointed; so how can organizations thoughtfully build not just data teams, but productive ones?

Data Strategy 81

Data Strategy Enterprise Strategy 81

Sisense

MAY 12, 2019

Today, most companies can say that they have integrated some DevOps collaboration between their development and operations teams. They are breaking down the silos, communicating better, and making the company more efficient as a result. But is that really true? Is your DevOps movement doing what it was set out to do? DevOps first came about in 2007-2008 to fix problems in the software industry and bring with it continuous improvement and greater efficiencies.

Analytics 79

Analytics Dashboards KPI Measurement 79

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

Smart Data Collective

MAY 14, 2019

In the early days of software development , projects were developed sequentially in a series of steps which was called “The Waterfall Model.” It was called the waterfall because once you got past a step, you couldn’t climb back up. Here is a typical waterfall model for software development : Requirements. Design. Implementation. Verification. Maintenance.

IT 90

IT Testing Software Modeling 90

Ontotext

MAY 17, 2019

Modern medicine and the Pharmaceutical industry have made tremendous breakthroughs over the past few centuries. From the discovery of penicillin to gene editing, Life Sciences and Pharma have helped treat and prevent many life-threatening diseases. At the same time, human ingenuity has always sought to not only save lives but also improve the standard of living for the growing global population.

Slice and Dice 76

Slice and Dice Unstructured Data Dashboards Optimization 76

Jet Global

MAY 16, 2019

Jet Basics is a free reporting tool available with Microsoft Dynamics. Offered as an extension included with Dynamics NAV since 2011 and Dynamics GP since 2016, Jet Basics gives users a simple way to create basic reports and business queries inside of Excel. While it’s a great way to get your feet wet with integrating Dynamics NAV or GP reporting directly in Excel, and become familiar with Jet Global products, it’s imperative to understand that Jet Basics is still designed to be an introductory

Reporting 76

Reporting Data Warehouse Dashboards Operational Reporting 76

Teradata

MAY 14, 2019

Cheryl Wiebe explains why AI for industrial use cases is a more complicated road than it appears.

IT 103

IT 103

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Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

Reporting

Smart Data Collective

MAY 11, 2019

. Artificial intelligence is redefining the nature of customer service. According to one analysis by Maruri Tech Labs, 85% of all customer service communications will be handled by an AI system by the end of next year. This is even true in call centers, which are surprisingly being disrupted by AI technology. Although artificial intelligence is going to be extremely important in the future of customer service, it is still too early to determine the degree to which it will be utilized.

Management 74

Management Big Data Interactive Predictive Analytics 74

DataRobot

MAY 14, 2019

DataRobot was honored to be named the 2019 Global Technology Partner of the Year by Qlik at their annual customer and partner event, Qonnections 2019. The awards ceremony recognizes the Qlik partner community for excellence in several different categories, both on a global scale and within regions, and celebrates outstanding achievement and innovation for joint customer success.

Technology 73

Technology 73

Jet Global

MAY 15, 2019

Microsoft Dynamics 365 Finance & Operations (D365FO) is a cloud-based business management solution built from the robust architecture of Dynamics AX. While some functionality has stayed the same, other areas, like reporting and analytics, have changed quite drastically and many people are unfamiliar with the new hurdles they face. In this Webinar, we will be covering several topics that impact self-service reporting, data access, and data consolidation in D365FO , including SSRS reporting, d

Finance 75

Finance Reporting Analytics Strategy 75

IBM Big Data Hub

MAY 16, 2019

A few competitors are trying to sow doubt about IBM’s commitment to IBM TM1 and IBM Planning Analytics – which is powered by IBM TM1 – as well as the product’s future, and the implications of the latest upgrade. Let me set the record straight—IBM Planning Analytics isn’t going anywhere.

Analytics 72

Analytics 72

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

Perceptual Edge

MAY 16, 2019

After a few months of waiting, my new book The Data Loom: Weaving Understanding by Thinking Critically and Scientifically with Data is now available. By clicking on the image below, you can order it for immediate delivery from Amazon. Data, in and of itself, is not valuable. It only becomes valuable when we make sense of it. Unfortunately, most of us who are responsible for making sense of data have never been trained in two of the job’s most essentially thinking skillsets: critical thinking and

IT 69

IT 69

Smarten

MAY 17, 2019

When it comes to using Predictive Analytics and a self-serve augmented analytics environment, businesses often want to sell the management team on these tools by suggesting real-world use cases that reflect the needs of the organization and illustrate how advanced analytics can help business users and the organization at large with accurate, efficient insight into the planning and forecasting process, and the ability to identify trends and patterns, understand target custom buying behavior, pred

Predictive Analytics 66

Predictive Analytics Forecasting Analytics Predictive Modeling 66

Domino Data Lab

MAY 15, 2019

Our last release, Domino 3.3 saw the addition of two major capabilities: Datasets and Experiment Manager. “Datasets”, a high-performance, revisioned data store offers data scientists the flexibility they need to make use of large data resources when developing models. And “Experiment Manager” acts as a data scientist’s “modern lab notebook” for tracking, organizing, and finding everything tested over the course of their research.

Testing 65

Testing Management Modeling Data Science 65

IBM Big Data Hub

MAY 16, 2019

Learn more about Brittany Bogle in our new series profiling the technical experts helping clients reach their AI and machine learning goals. Her path to data science elite status is what makes her a valuable and unique practitioner for IBM clients.

Data Science 69

Data Science Machine Learning 69

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