Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    big data analytics in transporation
    Turning Data Into Decisions: How Analytics Improves Transportation Strategy
    3 Min Read
    sales and data analytics
    How Data Analytics Improves Lead Management and Sales Results
    9 Min Read
    data analytics and truck accident claims
    How Data Analytics Reduces Truck Accidents and Speeds Up Claims
    7 Min Read
    predictive analytics for interior designers
    Interior Designers Boost Profits with Predictive Analytics
    8 Min Read
    image fx (67)
    Improving LinkedIn Ad Strategies with Data Analytics
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Harvesting Data: What Is the Mood in the World?
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Big Data > Data Mining > Harvesting Data: What Is the Mood in the World?
Data Mining

Harvesting Data: What Is the Mood in the World?

Erica Driver
Erica Driver
4 Min Read
SHARE

Every day, we create 2.5 quintillion bytes of data.* This data comes from everywhere—from posts to social media sites, digital pictures and videos posted online, and cell phone GPS signals, to name a few. The amount of data in our world has been exploding. Analyzing large data sets, so called “big data,” becomes a key basis of competition and innovation. The question is: How are we going to harvest all this data? Traditional BI is too clumsy to get the job done. Why?

Every day, we create 2.5 quintillion bytes of data.* This data comes from everywhere—from posts to social media sites, digital pictures and videos posted online, and cell phone GPS signals, to name a few. The amount of data in our world has been exploding. Analyzing large data sets, so called “big data,” becomes a key basis of competition and innovation. The question is: How are we going to harvest all this data? Traditional BI is too clumsy to get the job done. Why? Big data is time sensitive; there isn’t enough time for business users and developers to spend months documenting and coding the analysis requirements. Also, big data has a lot of variety; it comes from both structured and unstructured data sources.

QlikView is the perfect fit for analyzing big data. To prove my point, I created a QlikView application analyzing human feelings all over the world. Everyday millions of blog posts are written. People blog about technology, politics, health, etc. and they talk about their feelings.  I wondered if I could scan all of these blogs and analyze human feelings all around the world.

I found an API (We Feel Fine), which has been harvesting information about human feelings from a large number of logs since 2005. Every few minutes, the system searches the world’s newly posted blog entries for occurrences of the phrases “I feel” and “I am feeling” and stores 15,000 to 20,000 new emotions per day. I used the API to extract the data (in QlikView, developers can define web files as data source). Then I started asking questions and exploring this unstructured data.

Do women feel fat more often than men? Does rainy weather affect how we feel? What are the happiest cities in the world?  Do Europeans feel sad more often than Americans? You can download my application from QlikCommunity, to ask your own questions and formulate your own insights about the human condition.

 

World Mood.png

 

QlikView provides developers with a complete set of tools for managing data extraction and transformation, all offered in one comprehensive product. It can extract data from both structured and unstructured data sources and automatically creates associations in the data. Because QlikView operates entirely in memory, it does not require data to be stored in specific, aggregated formats. Once the data is loaded, users can start exploring the data right away, creating charts and answering questions with zero wait time. These are some of the features that make QlikView the perfect fit to discover big data. By the way, how am I feeling? I am feeling like Qliking!  

 

* McKinsey Global Institute – Big data: The next frontier for innovation, competition, and productivity

Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

AI role in medical industry
The Role Of AI In Transforming Medical Manufacturing
Artificial Intelligence Exclusive
b2b sales
Unseen Barriers: Identifying Bottlenecks In B2B Sales
Business Rules Exclusive Infographic
data intelligence in healthcare
How Data Is Powering Real-Time Intelligence in Health Systems
Big Data Exclusive
intersection of data
The Intersection of Data and Empathy in Modern Support Careers
Big Data Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

History of BI Month

1 Min Read
Image
Data Mining

Apache Spark Use Cases

6 Min Read

Is there anything new in Predictive Analytics?

5 Min Read

Headup uses a proprietary semantic engine that cross references…

1 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai is improving the safety of cars
From Bolts to Bots: How AI Is Fortifying the Automotive Industry
Artificial Intelligence
AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?