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 295

Business Intelligence Analytics Visualization 295

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

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

Management

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

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 156

Business Analytics Big Data Analytics Enterprise 156

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

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 277

Statistics Testing Data Science IT 277

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 98

Enterprise 98

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

Analytics

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 92

Big Data Risk Measurement Data mining 92

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

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

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 91

Experimentation Data Science Digital Transformation Modeling 91

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Visualization

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 91

Big Data Marketing Machine Learning Advertising 91

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

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

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

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Experimentation

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 89

IT Testing Software Modeling 89

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

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

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 73

Analytics 73

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Management

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 73

Management Big Data Interactive Predictive Analytics 73

Sisense

MAY 16, 2019

Oh, wonderful Ireland! The Emerald Isle, famed for her lush green land, her stunning rugged, dramatic western coast and her beautiful, historic, cities. A country celebrated for her lyrical heart that has been hailed by generations of some of the finest poets, playwrights, novelists, and songwriters. The home of James Joyce, Samuel Beckett, George Bernard Shaw; of Jonathan Swift, Oscar Wilde and W.B.Yeats.

Uncertainty 73

Uncertainty Reporting Dashboards Sales 73

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

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 71

Data Science Machine Learning 71

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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

Analytics

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

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 65

Predictive Analytics Forecasting Analytics Predictive Modeling 65

bridgei2i

MAY 14, 2019

BANGALORE, May 14, 2019. BRIDGEi2i is pleased to host Alex Smola – VP & Distinguished Scientist at AWS for an informative and hands-on learning session on Computer Vision GluconCV & D2L.ai on 18th May 2019 at the BRIDGEi2i auditorium. AWS is a cloud computing service that enables enterprises to build sophisticated applications with improved flexibility, scalability and reliability.

Contextual Data 63

Contextual Data Deep Learning Data Processing Consulting 63

Smart Data Collective

MAY 15, 2019

Big data is having a profound effect on the privacy debate. The problem is that people only look at it from one perspective. They see big data as a looming threat to their privacy. This is an issue that Tech Republic brought to our attention a couple of years ago in their post Big data privacy is a bigger issue than you think. The post showed that big data is raising a number of concerns about privacy rights.

Big Data 60

Big Data Predictive Analytics Machine Learning Technology 60

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

Manufacturing