datapine

MARCH 25, 2019

In our data-rich age, understanding how to analyze and extract true meaning from the digital insights available to our business is one of the primary drivers of success. Despite the colossal volume of data we create every day, a mere 0.5% is actually analyzed and used for data discovery , improvement, and intelligence. While that may not seem like much, considering the amount of digital information we have at our fingertips, half a percent still accounts for a huge amount of data.

Key Performance Indicator 217

Key Performance Indicator Statistics Visualization Big Data 217

TDAN

MARCH 19, 2019

From time to time, TDAN.com polishes off oldie but goodie content. A regular columnist required time to address personal issues, so we are substituting one of my past columns in its place. I hope you have as good a time reading it as I had writing it back in October of 2017. While I was […].

IT 45

IT Data Strategy Data Governance Business Intelligence 45

Rocket-Powered Data Science

MARCH 19, 2019

Diversity in data is one of the three defining characteristics of big data — high data variety — along with high data volume and high velocity. We discussed the power and value of high-variety data in a previous article: “ The Five Important D’s of Big Data Variety ” We won’t repeat those lessons here, but we focus specifically on the bias-busting power of high-variety data, which was actually the last of the five D’s mentioned in the earlier article: Decrease

Big Data 192

Big Data Statistics Manufacturing Data Science 192

TDAN

MARCH 19, 2019

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way. Which concepts will be forgotten in five years and which […].

Management 84

Management Data Lake Data Warehouse Analytics 84

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

Sisense

MARCH 31, 2019

Business intelligence implementation can seem like a daunting task at the outset. There are so many moving parts, needs, and requirements that finding the right starting point may feel like a shot in the dark. However, one of the most important aspects of running a successful business intelligence project is finding the right starting point. Clear starting points can help you launch new projects faster and acclimate to your platform’s tools.

Dashboards 75

Dashboards Business Intelligence ROI Testing 75

Andrew White

MARCH 28, 2019

It’s all the rage- we need to be ‘data driven’. Unfortunately important ideas and advice are often dumbed-down or simplified to singular messages for ease of consumption and this can lead to yet more problems. To be data driven is a great example. What is such a thing? Conceptually to be data driven sounds like a situation whereby a decision ought to have its roots founded in data.

Data-driven 79

Data-driven Statistics Testing Metrics 79

datapine

MARCH 20, 2019

“Vision without action is merely a dream. Action without vision just passes the time. Vision with action can change the world.” – Joel A. Barker. Financial analysis and reporting are one of the bedrocks of modern business. While you may already know that financial reporting is important (mainly because it’s a legal requirement in most countries), you may not understand its untapped power and potential.

Reporting 248

Reporting Finance Snapshot Dashboards 248

Analytics Vidhya

MARCH 31, 2019

Introduction What’s the first thing you do when you’re attempting to cross the road? We typically look left and right, take stock of the. The post Computer Vision Tutorial: A Step-by-Step Introduction to Image Segmentation Techniques (Part 1) appeared first on Analytics Vidhya.

Analytics 307

Analytics Deep Learning 307

David Menninger's Analyst Perspectives

MARCH 1, 2019

I am happy to offer some insights on SAP drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Analytics 203

Analytics IT Business Intelligence ROI 203

Rocket-Powered Data Science

MARCH 19, 2019

We hear a lot of hype that says organizations should be “ Data – first ”, or “AI- first , or “ Data – driven ”, or “ Technology – driven ”. A better prescription for business success is for our organization to be analytics – driven and thus analytics-first , while being data -informed and technology -empowered. Analytics are the products, the outcomes, and the ROI of our Big Data , Data Science, AI, and Machine Learning investments!

Analytics 193

Analytics Metrics Data-driven ROI 193

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Strategy

Corinium

MARCH 27, 2019

Investment managers are expected to spend more than $1.6 billion on alternative data sets in 2020. The sheer volume of data produced will necessitate a change in how businesses acquire, process, and use it. Identifying and acquiring data sets is only the beginning of an investment firm’s data strategy. The key will be the ability to integrate a broad range of custom data sets, to share them flexibly, and to extract key insights in time.

Data Analytics 150

Data Analytics Analytics Data Strategy Strategy 150

O'Reilly on Data

MARCH 7, 2019

NLP systems in health care are hard—they require broad general and medical knowledge, must handle a large variety of inputs, and need to understand context. We’re in an exciting decade for natural language processing (NLP). Computers will get as good as humans in complex tasks like reading comprehension, language translation, and creative writing.

Deep Learning 227

Deep Learning Testing Machine Learning Modeling 227

datapine

MARCH 15, 2019

At present, 53% of businesses are in the process of adopting big data analytics as part of their core business strategy – and it’s no coincidence. To win on today’s information-rich digital battlefield, turning insight into action is a must, and online data analysis tools are the very vessel for doing so. The world’s inherent rise in digital transformation coupled with today’s consumers’ appetite for the World Wide Web (and all entities either connected to it or surrounding it), there has

Technology 143

Technology Cost-Benefit KPI Dashboards 143

Analytics Vidhya

MARCH 21, 2019

Introduction Do you often work with reports in Excel? Or regularly build dashboards and visualizations in Tableau or Power BI? If you answered yes. The post Infographic: 11 Steps to Transition into Data Science (for Reporting / MIS / BI Professionals) appeared first on Analytics Vidhya.

Data Science 308

Data Science Reporting Dashboards Visualization 308

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

Testing

David Menninger's Analyst Perspectives

MARCH 25, 2019

Analytics and business intelligence (BI) play an instrumental role in enabling an organization’s business units and IT to utilize its data in both tactical and strategic ways to perform optimally. To accomplish this, organizations must not only access the data, generate and apply insights from analytics, and communicate the results, they also must ensure that the analytics are presented in a way that leads to action.

Analytics 184

Analytics Business Intelligence Optimization IT 184

Rocket-Powered Data Science

MARCH 19, 2019

We often think of analytics on large scales, particularly in the context of large data sets (“Big Data”). However, there is a growing analytics sector that is focused on the smallest scale. That is the scale of digital sensors — driving us into the new era of sensor analytics. Small scale ( i.e., micro scale) is nothing new in the digital realm.

Big Data 186

Big Data Analytics Machine Learning Internet of Things 186

DataRobot

MARCH 29, 2019

AI has tremendous potential for benefiting humanity in every area of how we live and work. While most people realize this fact, their hopes for AI also come with a note of caution. A recent survey reported that 77% of Americans expressed that AI would have a “very positive” or “mostly positive” impact on how people work and live in the next 10 years.

Reporting 106

Reporting Management Technology 106

O'Reilly on Data

MARCH 27, 2019

Watch highlights from expert talks covering AI, machine learning, data analytics, and more. People from across the data world are coming together in San Francisco for the Strata Data Conference. Below you'll find links to highlights from the event. The journey to the data-driven enterprise from the edge to AI. Amy O'Connor explains how Cloudera applies an "edge to AI" approach to collect, process, and analyze data.

Uncertainty 207

Uncertainty Forecasting Data-driven Machine Learning 207

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IT

datapine

MARCH 22, 2019

“There’s a certain way of creating a service, hospitality, and experience that perpetuates people feeling like they matter.” – Julie Rice, entrepreneur, and investor. Today’s tech-savvy customers are driven by experiences. Now more than ever, consumers look for trust, honesty, transparency, value, and an exemplary level of customer experience (CX) from brands they’re willing to invest in.

Metrics 134

Metrics Dashboards Measurement Interactive 134

Analytics Vidhya

MARCH 13, 2019

Introduction I have been a programmer since before I can remember. I enjoy writing codes from scratch – this helps me understand that topic. The post 5 Amazing Deep Learning Frameworks Every Data Scientist Must Know! (with Illustrated Infographic) appeared first on Analytics Vidhya.

Deep Learning 308

Deep Learning Analytics 308

David Menninger's Analyst Perspectives

MARCH 20, 2019

I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Mobile Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Business Intelligence 145

Business Intelligence Analytics ROI Software 145

Data Science 101

MARCH 16, 2019

Recently updated, is the March 2019 Machine Learning Study Path. It contains links and resources to learn Tensorflow and Scikit-Learn. If you are interested in details on the study path and how to best use the resources. There is a livestream on Facebook, Sunday March 17 on the Math for Data Science Facebook page.

Machine Learning 105

Machine Learning Data Science IT 105

Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO

The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.

Customer Analytics

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. Data can be stored as-is, without first structuring it, and different types of analytics can be run on it, from dashboards and visualizations to big data processing, real-time analytics, and machine learning to improve decision making. The power of the data lake lies in the fact that it often is a cost-effective way to store data.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

O'Reilly on Data

MARCH 14, 2019

The O’Reilly Data Show Podcast: Kartik Hosanagar on the growing power and sophistication of algorithms. In this episode of the Data Show , I spoke with Kartik Hosanagar , professor of technology and digital business, and professor of marketing at The Wharton School of the University of Pennsylvania. Hosanagar is also the author of a newly released book, A Human’s Guide to Machine Intelligence , an interesting tour through the recent evolution of AI applications that draws from his extensive expe

Marketing 185

Marketing Technology 185

datapine

MARCH 27, 2019

“Get closer than ever to your customers. So close that you tell them what they need well before they realize it themselves.” – Steve Jobs. We’re living in the midst of the age of information, a time when online data analysis can determine the direction and cement the success of a business or a startup that decides to dig deeper into consumer behavior insights.

Management 129

Management Data-driven Dashboards Visualization 129

Analytics Vidhya

MARCH 27, 2019

Introduction Q-learning became a household name in data science when DeepMind came up with an algorithm that reached superhuman levels on ATARI games. It’s. The post Nuts and Bolts of Reinforcement Learning: Introduction to Temporal Difference (TD) Learning appeared first on Analytics Vidhya.

Data Science 302

Data Science Analytics IT 302

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Analytics

David Menninger's Analyst Perspectives

MARCH 18, 2019

For analytics to be effective, they need to be available to line-of-business personnel as needed in their normal course of conducting business, which today means providing rich mobile access to analytics through phones and tablets to support a mobile workforce seeking to conduct business in any location at any time. Workers today expect these mobile capabilities, which means organizations must make choices to provide analytics and BI platforms that can deliver them.

Business Intelligence 145

Business Intelligence Analytics Technology 145

IBM Big Data Hub

MARCH 26, 2019

IBM announced Informix V14.10 at Think 2019, revealing a host of new capabilities to clients and partners in attendance. Now, after beta testing with more than 25 customers and partners, it is available to the public.

Enterprise 100

Enterprise Data Processing Testing IT 100

Corinium

MARCH 28, 2019

Zendesk :

150

150

O'Reilly on Data

MARCH 28, 2019

Lauren Kunze discusses lessons learned from an analysis of interactions between humans and chatbots. Continue reading Chatting with machines: Strange things 60 billion bot logs say about human nature.

Interactive 131

Interactive 131

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

Data-driven