BIG DATA AND ANALYTICS
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Rescooped by Neeraj Kumar Singal from LinkedIn Marketing Strategy
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5 Tips to Make Your LinkedIn Profile Irresistible

5 Tips to Make Your LinkedIn Profile Irresistible | BIG DATA AND ANALYTICS | Scoop.it
Are you looking to make your LinkedIn profile more attractive to recruiters?   1. Keywords in your profile Search engine optimization is a key element of your LinkedIn profile.

Via Steve Cassady, Renee Fortin, Noland Hoshino
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Rim Riahi's curator insight, August 25, 2013 2:40 AM

Are you looking to make your LinkedIn profile more attractive to recruiters?   1. Keywords in your profile Search engine optimization is a key element of your LinkedIn profile.

Ali Anani's curator insight, September 4, 2013 12:18 AM

LinkedIn is for professionals and so why not have a professional profile?

Scooped by Neeraj Kumar Singal
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[Free eBook] Big Data, Analytics And The Future Of Marketing And Sales - McKinsey

[Free eBook] Big Data, Analytics And The Future Of Marketing And Sales - McKinsey | BIG DATA AND ANALYTICS | Scoop.it

We’ve recently published a multimedia eBook Big Data, Analytics, and the Future of Marketing & Sales that attempts to answer that question. Organizations today face overwhelming amounts of data, organizational complexity, rapidly changing customer behaviors, and increased competitive pressures.   New technologies as well as rapidly proliferating channels and platforms have created a massively complex environment. At the same time, the explosion in data and digital technologies has opened up an unprecedented array of insights into customer needs and behaviors.

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Sachin More's curator insight, January 27, 2015 6:26 AM

hi

Zeyu Wu's curator insight, May 6, 2015 9:52 PM

We need to read it.

Igor Martini's curator insight, February 10, 11:34 AM

teste

Rescooped by Neeraj Kumar Singal from Big Data & Digital Marketing
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How Your Company Can Utilize Big Data Analytics

How Your Company Can Utilize Big Data Analytics | BIG DATA AND ANALYTICS | Scoop.it

A by-product of the Information Age is a myriad of unstructured data created by companies aptly termed by data managers as “big data.”


Via Luca Naso
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Luca Naso's curator insight, August 2, 2013 12:11 PM

If Big Data is a gold mine, one should try to identify the veins of gold and start extracting.

Here are some suggestion about where these gold veins could be:

1. Social Media Data

2. Publicly Available Internet Data

3. Network Packet Data

4. Archived Documents

Rescooped by Neeraj Kumar Singal from The MarTech Digest
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Metrics and Analytics: 4 questions every marketer should ask their data analysts | MarketingExperiments | #TheMarketingAutomationAlert

Metrics and Analytics: 4 questions every marketer should ask their data analysts | MarketingExperiments | #TheMarketingAutomationAlert | BIG DATA AND ANALYTICS | Scoop.it
Marketers understand the value of using metrics to gain customer insights, but often have a limited background in data analysis. This can have a profound impact on the accuracy of information used to make important decisions.

 

Digest...

 

There’s no need to turn a marketer into a data analyst or vice versa, but instead, let’s cover some very important ground first before any testing begins.

 

Question #1. How are we using quality assurance to mitigate risk?  It stands to reason you want to address data accuracy and appropriate metric interpretation before you begin testing.

And quality assurance (QA) is a key step in doing that.

 

Question #2. How will results vary? Would you want to make a multimillion-dollar decision knowing there is a good chance you could be off by a fairly large margin?

Probably not, and this is why understanding how variance between your metrics platform and the true value is important.

 

Question #3. Do we know how the metrics we use are calculated on our platform?   Misinterpretation of metrics is epidemic in online testing – and it’s often preventable.

I say this because the accuracy of interpreting information is generally driven by an understanding of it.

 

Question #4. How can we avoid placing too much faith in one calculated metric?   

I often talk to people who use average time on page as a measure of engagement and they put far too much faith in it. The problem with this is from a theoretical standpoint, any average is highly susceptible to outside forces because an extreme outlier will skew the average value.


Via marketingIO
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marketingIO's curator insight, August 2, 2013 12:25 PM

Big Data is a waste of time if you don't have the resources to exploit the data. Whether it's marketing scientists, stat pros, ops, etc., you need the resources in place to exploit the hidden value found in the data. Take a look at the questions above: are there folks on staff right now who understand those questions and have the answers?


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Rescooped by Neeraj Kumar Singal from Designing service
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Designing design thinking driven operations

Designing design thinking driven operations | BIG DATA AND ANALYTICS | Scoop.it

 

 

Customer experience, customer service, design thinking, service design, service management

 

Mail me: fjg.zimny@serve4impact.com

 

 

 

Follow me on twitter: @FredZimny

 

Connect with me on linkedin http://www.linkedin.com/in/fredzimny

 

 

Even more good stuff at http://serve4impact.com 




Via Fred Zimny
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Sneaky's comment, June 25, 2015 10:42 AM
super article
Rescooped by Neeraj Kumar Singal from IT Books Free Share
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Real-Time Big Data Analytics: Emerging Architecture - Free eBook Share

Real-Time Big Data Analytics: Emerging Architecture - Free eBook Share | BIG DATA AND ANALYTICS | Scoop.it
eBook Free Download: Real-Time Big Data Analytics: Emerging Architecture | PDF, EPUB | ISBN: B00DO33RSW | 2013-06-24 | English | PutLocker

Via Fox eBook
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Fox eBook's curator insight, July 23, 2013 2:19 PM

Five or six years ago, analysts working with big datasets made queries and got the results back overnight. The data world was revolutionized a few years ago when Hadoop and other tools made it possible to get

the results from queries in minutes. But the revolution continues. Analysts now demand sub-second, near real-time query results. Fortunately, we have the tools to deliver them. This report examines tools and technologies that are driving real-time big data analytics.

Table of Contents

1. Introduction
2. How Fast Is Fast?
3. How Real Is Real Time?
4. The RTBDA Stack
5. The Five Phases of Real Time
6. How Big Is Big?
7. Part of a Larger Trend

rajesh's curator insight, January 14, 2014 12:27 AM

i need to read the book

Rescooped by Neeraj Kumar Singal from Data Nerd's Corner
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Getting down to business on big data analytics

Getting down to business on big data analytics | BIG DATA AND ANALYTICS | Scoop.it
With the right big data analytics tools and effective strategies for managing them, companies can gain real business value and competitive advantages from their caches of big data.

Via Carla Gentry CSPO
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Carla Gentry CSPO's curator insight, July 23, 2013 11:22 AM

This handbook provides strategic insight and practical advice on some of the key facets of managing successful big data analytics programs. It will also point to real-world examples of big data analytics in action. 

Rescooped by Neeraj Kumar Singal from Conversion Optimisation
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51 Tips To Succeed With Web Analytics | Analytics & Optimization

51 Tips To Succeed With Web Analytics | Analytics & Optimization | BIG DATA AND ANALYTICS | Scoop.it
This article provides 51 tips to help professionals implement Google Analytics, configure the tool, use it to analyze online behavior and optimize websites. Sit down and relax, here we go!

Via Haberich
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