datapine

SEPTEMBER 11, 2019

Digital data, by its very nature, paints a clear, concise, and panoramic picture of a number of vital areas of business performance, offering a window of insight that often leads to creating an enhanced business intelligence strategy and, ultimately, an ongoing commercial success. Business intelligence steps up into this process by creating a comprehensive perspective of data, enabling teams to generate actionable insights on their own.

Business Intelligence 161

Business Intelligence Analytics Sales Dashboards 161

KDnuggets

SEPTEMBER 12, 2019

There is no such thing as a free lunch in life or data science. Here, we'll explore some science philosophy and discuss the No Free Lunch theorems to find out what they mean for the field of data science.

Data Science 123

Data Science Optimization Machine Learning 123

Analytics Vidhya

SEPTEMBER 10, 2019

Overview Sampling is a popular statistical concept – learn how it works in this article We will also talk about eight different types of. The post A Data Scientist’s Guide to 8 Types of Sampling Techniques appeared first on Analytics Vidhya.

Statistics 307

Statistics Analytics IT 307

Corinium

SEPTEMBER 10, 2019

Tell us about your experience in working with the data analytics community at Cloudera? Why do you like working in this space?

Data Analytics 150

Data Analytics Analytics 150

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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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

O'Reilly on Data

SEPTEMBER 12, 2019

The O’Reilly Data Show Podcast: Michael Mahoney on developing a practical theory for deep learning. In this episode of the Data Show , I speak with Michael Mahoney , a member of RISELab , the International Computer Science Institute , and the Department of Statistics at UC Berkeley. A physicist by training, Mahoney has been at the forefront of many important problems in large-scale data analysis.

Deep Learning 29

Deep Learning Statistics Data Processing Optimization 29

KDnuggets

SEPTEMBER 13, 2019

While ensembling techniques are notoriously hard to set up, operate, and explain, with the latest modeling, explainability and monitoring tools, they can produce more accurate and stable predictions. And better predictions can be better for business.

Modeling 123

Modeling Machine Learning 123

Corinium

SEPTEMBER 9, 2019

Tell us about your experience in working with the data analytics community at Outlier? Why do you like working in this space? From the very beginning of Outlier, I have really enjoyed collaborating with others in the data analytics community. Data.

Data Analytics 150

Data Analytics Analytics 150

David Menninger's Analyst Perspectives

SEPTEMBER 13, 2019

The Oracle Analytics Summit 2019 was the inaugural user event for Oracle Analytics customers, and they also broadcast the video for thousands of others. You can watch the keynote at [link]. Executives talked about some big organizational changes, including Bruno Aziza joining last year to lead the analytics organization. This event marked a transition and "a new beginning" for the Oracle Analytics portfolio, as the company announced three new analytics products.

Broadcasting 113

Broadcasting Analytics Big Data Data Science 113

KDnuggets

SEPTEMBER 12, 2019

It is important to distinguish prediction and classification. In many decision-making contexts, classification represents a premature decision, because classification combines prediction and decision making and usurps the decision maker in specifying costs of wrong decisions.

IT 123

IT Machine Learning Data Science 123

Analytics Vidhya

SEPTEMBER 11, 2019

Overview A data-science-driven product consists of multiple aspects every leader needs to be aware of Machine learning algorithms are one part of a whole. The post 4 Key Aspects of a Data Science Project Every Data Scientist and Leader Should Know appeared first on Analytics Vidhya.

Data Science 282

Data Science Machine Learning Data-driven Analytics 282

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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

DataCamp

SEPTEMBER 12, 2019

You can become a data scientist at any age if you’re willing to put in the work.

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CIO Business Intelligence

SEPTEMBER 12, 2019

Business intelligence (BI) and analytics platforms have long been a staple for business, but thanks to the rise of self-service BI tools, responsibility for analytics has shifted from IT to business analysts, with support from data scientists and database administrators.

Analytics 106

Analytics Business Intelligence IT 106

KDnuggets

SEPTEMBER 11, 2019

As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.

Machine Learning 123

Machine Learning Marketing Modeling 123

Analytics Vidhya

SEPTEMBER 9, 2019

Overview Here’s a unique data science challenge we don’t come across often – a marketing analytics hackathon! We bring you the top 3 inspiring. The post WNS Analytics Wizard 2019: Top 3 Winners’ Solutions from our Biggest Data Science Hackathon appeared first on Analytics Vidhya.

Data Science 268

Data Science Analytics Marketing Analytics Marketing 268

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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

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. Strata attracts the leading names in the fields of data management, data engineering, analytics, ML, and artificial intelligence (AI).

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

erwin

SEPTEMBER 12, 2019

Strong internal business process modeling and management helps data-driven organizations compete and lead. In short, an internal business process is a documented account of how things should be done to maximize efficiency and achieve a particular goal. In the book “Exponential Organizations” by Salim Ismail, Michael S. Malone and Yuri van Geest , the authors, examine how every company is or will evolve into an information-based entity in which costs fall to nearly zero, abundance replaces scarci

Modeling 101

Modeling Cost-Benefit Data-driven Data Governance 101

KDnuggets

SEPTEMBER 10, 2019

In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.

Data Science 123

Data Science 123

Ontotext

SEPTEMBER 9, 2019

My great grandparents were married for more than sixty years. They had a telepathy that comes from living together that long. They could finish each other’s sentences or anticipate when one wanted a coffee or lunch. An exchange could go like this. ‘Remember those figs?’ Grandma said. ‘You’re talking about that holiday to France in ’76 and it wasn’t figs, it was apples.’.

Metadata 99

Metadata Consulting Reporting Technology 99

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

Teradata

SEPTEMBER 11, 2019

AI & Deep Learning allow organizations to maximize player performance while minimizing player risk through better insights from performance and wellness data.

Deep Learning 98

Deep Learning Risk 98

Smart Data Collective

SEPTEMBER 13, 2019

As industry buzzwords, “Big Data” is one of those phrases that has become seemingly ubiquitous. Everyone wants to be using big data to better their operation. The maintenance department is no exception to this trend. Accordingly, maintenance teams are beginning to embrace the use of big data and analytics to improve performance. In emphasizing the use of “big data”, maintenance can establish predictive maintenance programs, which reduce downtime and save on maintenance costs.

Big Data 92

Big Data Manufacturing Cost-Benefit Optimization 92

KDnuggets

SEPTEMBER 10, 2019

How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a competitive advantage by knowing both frameworks.

Machine Learning 123

Machine Learning 123

Perceptual Edge

SEPTEMBER 11, 2019

[Note: To make it easy for you to read this article offline and to share it with others, I’ve made a PDF version available as well.]. Almost all data visualizations are multivariate (i.e., they display more than one variable), but there are practical limits to the number of variables that a single graph can display. These limits vary depending on the approach that’s used.

Visualization 88

Visualization Sales Software Data Processing 88

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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

IBM Big Data Hub

SEPTEMBER 9, 2019

Artificial intelligence and machine learning (ML) have become very popular recently due to their ability to both optimize processes and provide the deep insights that push enterprises and industries forward.

Management 82

Management Machine Learning Optimization Enterprise 82

Smart Data Collective

SEPTEMBER 13, 2019

Big Data is among one of the most impressive tech advancements that have hit the marketing world in recent memory. While it has been tossed around as a buzzword in certain circles, Big Data is so much more than just a phrase. For a definition , Oracle recommends Gartner’s 2001 description of Big Data, which describes it as data containing a greater variety, getting to the source in increasing volume and at ever-higher velocity.

Big Data 86

Big Data Marketing Advertising Data Collection 86

KDnuggets

SEPTEMBER 9, 2019

This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.

Data Science 123

Data Science 123

Srividya Sridharan

SEPTEMBER 10, 2019

Summer’s lease hath all too short a date. It always seems to pass by in the blink of an eye, and this year was no exception. Though I am excited for cooler temperatures and the prismatic colors of New England in the fall, I am sorry to see summer come to an end. The end […].

Data Analytics 81

Data Analytics Analytics B2B IT 81

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

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

Sisense

SEPTEMBER 12, 2019

Blog. We’ve been talking a lot recently about companies needing to use their data in order to stay in business in the future. We’ve even gone as far as saying that every company is a data company , whether they know it or not. And every business – regardless of the industry, product, or service – should have a data analytics tool driving their business.

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

Smart Data Collective

SEPTEMBER 13, 2019

Gone are the days when storage of information can only be done with the traditional remote servers which are located in a secluded location. Today, the in-thing is cloud data storage where information and data are stored electronically online. With this approach, you can store unlimited data online (in the cloud) and access it anywhere. Several essays and many articles have been written on storage clouds and benefits of the cloud , but this piece puts forward five of the biggest benefits that yo

Big Data 80

Big Data Cost-Benefit Risk IT 80

KDnuggets

SEPTEMBER 9, 2019

In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

Machine Learning 123

Machine Learning Modeling 123

Timo Elliott

SEPTEMBER 13, 2019

A quick 13-minute presentation from last year’s Mentes Brillantes in Madrid, talking about the digital enterprise revolution, using real-world examples of artificial intelligence, blockchain, and analytics, and talking about the importance of creativity and new business models. I was speaking slowly to try and make it easy to follow (I was the only presenter who didn’t do it in Spanish).

Technology 79

Technology Enterprise Modeling Analytics 79

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