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February 2016 Blog Posts (93)

Two Sides of "Big?" Data

The ongoing pursuit of data solutions occupies mindshare of consumers, vendors and service providers alike as they invest considerable amount of time, costs and efforts. The past attempts to concur data have resulted in solutions that combined databases, applications and tools with limited success. We are still struggling with a few unresolved, persistent legacy challenges such as - 

Data everywhere

Today, every enterprise has huge data…

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Added by Suhas Marathe on February 23, 2016 at 9:48am — No Comments

Big Data: 17 Predictions Everyone Should Read

This article was written by Bernard Marr. 

Almost everyone can agree that big data has taken the business world by storm, but what’s next?  Will data continue to grow?  What technologies will develop around it? Or will big data become a relic as quickly as the next trend — cognitive technology? fast data? — appears on the horizon.   

Let’s look at some…

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Added by Emmanuelle Rieuf on February 23, 2016 at 8:00am — No Comments

The Shift from Real-Time to Right Time Marketing – How to Drive Real-Time Connections with Today’s Consumers

The definition of real-time marketing is evolving. The buzz around Big Data and the…

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Added by Larisa Bedgood on February 23, 2016 at 6:00am — No Comments

Using machine learning to generate music

Apart from…

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Added by Banjog on February 23, 2016 at 1:30am — No Comments

5 Ways to Realize the Potential of the Industrial Internet

How does a company break into the huge potential marketplace that is the Industrial Internet? Spending on the Industrial Internet—the convergence of industrial machines, data, and the Internet (one aspect of the Internet of Things)—was $20 billion in 2012. Analysts are forecasting that number will reach $514 billion by 2020, creating nearly $1.3 trillion in value. MIT Sloan Management Review recently published a case study of one company that…

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Added by Deb Gallagher on February 22, 2016 at 12:54pm — No Comments

New Architecture for the Analytic Ecosystem

Great article by Mike Ferguson. Articles about the big data, AI, data science or IoT ecosystems are always popular. Many have been posted here (see screenshot below):

Sometimes, the keyword…

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Added by L.V. on February 22, 2016 at 11:30am — No Comments

12 Emerging Trends in Data Analytics

Data Science Central shared its predictions for 2016. More predictions can be found here. In this article, we share Scott Mongeau's predictions. The full version of this (long) article can be found…

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Added by L.V. on February 22, 2016 at 11:00am — 2 Comments

Boom of Data Analyzing Software Makes Big Data More Accessible

You cannot argue that the marketing landscape has changed drastically over the years - gone are the days of throwing different strategies on the wall to see which one would stick. Instead, companies today are equipped with enough information about their customers and tactics thanks to the big data boom of recent years. In…

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Added by Nate Vickery on February 22, 2016 at 1:30am — No Comments

Mobile Data Traffic Market is expected to reach USD 628.1 billion in 2016

With the growth in the market penetration of smart phones, the number of mobile phone users is likely to increase. The popularity of social media is also expected to increase and 14 more applications will see growth in the mobile data traffic market.

Mobile traffic data was estimated at 3.9 trillion megabytes in 2011 and it is expected to reach 39.9 trillion megabytes in 2016, whereas mobile data revenue was estimated at USD 326.1 billion in 2011 and is expected to reach USD 628.1…

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Added by Ankit Jain on February 21, 2016 at 9:42pm — No Comments

Tutorial – Getting Started with GraphLab For Machine Learning in Python

This article was written by Sunil Ray. Sunil is a Business Analytics and Intelligence professional with deep experience in the Indian Insurance industry. 

Introduction

GraphLab came as an unexpected breakthrough on my learning plan. After all, ‘ Good Things Happen When You Expect Them Least To Happen’. It all started with the end of Black Friday Data Hack. Out of 1200 participants, we got our winners and their…

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Added by Emmanuelle Rieuf on February 20, 2016 at 3:30pm — No Comments

11 Important Model Evaluation Techniques Everyone Should Know

Model evaluation metrics are used to assess goodness of fit between model and data, to compare different models, in the context of model selection, and to predict how predictions (associated with a specific model and data set) are expected to be accurate. 

Confidence Interval. Confidence intervals are used to assess how reliable a statistical…

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Added by L.V. on February 20, 2016 at 10:00am — 2 Comments

Data Center Infrastructure Management Market led to Wider Spread thanks to Incorporation of DCIM Solutions in IT Industry

Data center infrastructure management (DCIM) solutions are the most effective way to reduce data center operating costs. DCIM solutions provide significant value to IT organizations that are concerned about the energy consumption and improvement in operational efficiency in their data centers. DCIM is a combination of IT and facilities management that helps enable faultless monitoring of all systems in IT and facility infrastructure.

DCIM Emerges as a Strategic Tool for…

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Added by Ankit Jain on February 19, 2016 at 4:00am — No Comments

Cloud Machine Learning APIs

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Added by Megter on February 19, 2016 at 2:30am — 1 Comment

Credit Analytics and its Application in Businesses

Credit analytics is a way to arrive at creditworthiness of a business or an organization i.e. the ability of the Business or organization to meet its financial obligations. In technical terms, the crux of credit risk analysis lies in identifying the appropriate level of default risk associated with investment in a particular entity.…

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Added by Tanmay Bhandari on February 19, 2016 at 1:19am — No Comments

Choosing features for random forests algorithm

There are many ways to choose features with given data, and it is always a challenge to pick up the ones with which a particular algorithm will work better. Here I will consider data from monitoring performance of physical exercises with wearable accelerometers, for example, wrist bands.

The data for this project come from this source: http://groupware.les.inf.puc-rio.br/har.

In this project, researchers used data from…

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Added by Maiia Bakhova on February 18, 2016 at 11:00am — 5 Comments

Beware: Employers Mine Your Personal Data to Predict Health

Watch out folks - there is a new breed of health analytics firms sprouting like weeds - mining "big data" about you and making broad and bold predictions about your state of health to make workplace decisions.

 …

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Added by Michael Walker on February 18, 2016 at 12:34am — No Comments

Speech (Interaction) Analytics : Realize the Essential Points and Leave the Rest as Surplus

As worldwide establishments continue to look for ways to make big data actionable, solutions such as speech analytics are well placed to help customers and balance the need of revealing new revenue opportunities, reducing costs and optimizing the customer experience.…

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Added by Anuj Tripathi on February 18, 2016 at 12:00am — No Comments

Predictive Analytics: The Command to Forecast Who will Connect, Purchase, Gain or Drain

Whether you love it or hate it, predictive analytics has already helped elect presidents, discover new energy sources, score consumer credit, assess health risks, detect fraud and target prospective buyers. 

Predictive analytics is business intelligence technology that produces a predictive…

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Added by Anuj Tripathi on February 18, 2016 at 12:00am — No Comments

Big Data – Before you jump in make sure you are planning appropriately

For a few years now Big Data has drawn the attention of many firms and CIOs. The rewards are major –new business insights, new customer segments, speed (faster time-to-answer, faster time-to-decision, and faster speed-to-market) to driving operational cost efficiencies and even corporate strategies. 

In the past few months I have been connecting with senior managers who want to start their Big Data efforts this year. You will need to take the necessary time to focus on some upfront…

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Added by John P. Stevens on February 17, 2016 at 12:21pm — No Comments

Weekly Digest, February 22

Starred articles are new additions or updated content, posted between Thursday and Sunday. The weekly digest has six sections: (1) Featured Resources and Technical Contributions, (2) Featured Articles and Case Studies, (3) From our Sponsors, (4) News, Events, Books, Training, Forum Questions, (5) Picture of the Week, and (6) Syndicated Content.

The full version is always published Monday.…

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Added by Vincent Granville on February 17, 2016 at 10:30am — No Comments

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