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
    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 and remote work
    Data Helps Speech-Language Pathologists Deliver Better Results
    6 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: Harnessing the Power of Big Data, Machine Learning, & Predictive Analytics
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Analytics > Predictive Analytics > Harnessing the Power of Big Data, Machine Learning, & Predictive Analytics
Big DataPredictive Analytics

Harnessing the Power of Big Data, Machine Learning, & Predictive Analytics

Subhankar Bhattacharjee
Subhankar Bhattacharjee
6 Min Read
Predictive Analytics
SHARE

Any sufficiently advanced technology is indistinguishable from magic.” – Arthur C. Clarke

The concept of Big Data is here to stay. Furthermore, as technology advances and computing power and computing speed increases, data analysts will be able to improve on the type, caliber, and quality of the statistical information that is derived from the raw data.

Contents
Machine learning and Predictive AnalyticsThe neural network pattern recognition model:Final words

In other words, data scientists can extract, transform, load (ETL) and analyse large volumes of data from scanned documents, voice recordings, social media, website statistics, as well as telematics.

Machine learning and Predictive Analytics

As described above, the data that is undergone the ETL process and is loaded into a data warehouse can be used for a variety of functions. One of the more popular applications is to build a predictive analysis model or a neural network that will answer questions about the future. These issues or questions depend on the industry that is utilising the neural network to provide the predictive analysis.

Before we look at a practical example of how a neural network is used to provide forecast information based on existing data, let’s define what the terms “machine learning”, “predictive analytics”, and “neural networks” are:

More Read

data ethics
Essential Data Ethics and Privacy Practices for Social Media Marketers
Data Mining Poll: Online Privacy
It’s Just a Little More Disk Space
Bigger Data, Better Intelligence for Government
How BI and Data Analytics Gurus Used Twitter in February

Machine learning

Reema Bhatia defines machine learning as the “ability for computer programs to analyse big data, extract information automatically, and learn from it.” Massive amounts of data are being generated faster than ever before. Consequently, data can no longer be analysed manually. Hence, machine learning has taken over the role of analysing the vast amounts of data that are generated on a daily basis.

Predictive analytics

Predictive analytics is the “practice of extracting information from existing data sets… to determine patterns and predict future outcomes and trends.” It is important to note that the aim of predictive analytics does not state what will happen in the future. It predicts or forecasts what might occur with an “acceptable level of reliability, and includes what-if scenarios and risk assessment.”

Neural networks

In simple terms, a neural network or artificial neural network is “a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs.”

It is a type of deep learning technology that, when utilised in the in the corporate world, tends to focus on solving complex predictive analyses problems using pattern recognition methodologies. Neural network models are also used weather prediction, facial recognition, oil exploration data analysis, and text-to-speech transcriptions.
It should be noted at this juncture, that for a neural network pattern recognition model to predict or forecast future trends as accurately as possible, substantial amounts of data are needed to train the model.

The neural network pattern recognition model:

As mentioned above, an artificial neural network is similar to the human brain in that it is constructed from a collection of nodes (called neurons) with links or synapses connecting them.

Furthermore, a neural network is organised into three layers: the input layer, a number hidden or inner layers, and the output layer. The hidden layers are necessary to make sense of complex input data. In essence, the more complicated the input data, the greater the number of inner layers that are needed to understand the data and produce valuable output.

The number of nodes in each hidden layer is also dependent on the complexity of the data. Each node is in actual fact a weighting which determines the strength of the input in relation to the output. In order to calculate the output based on the node’s weighting factor, all input variables need to consist of numerical data. Text or categorical data cannot be used.

Due to the complex nature of the neural network’s calculations, we won’t go into detail here. All we need to understand is that part of building the model is to test it using known output to determine whether it produces the correct results or not.

Once the model has been built, the next step is to train the model using existing data. Once the model has been trained, the final step is to run it using live data and allow it to predict or forecast future trends using pattern recognition as its base.

Final words

As the quotation mentioned above by Arthur C. Clark states, a successfully built artificial neural network produces magical results that go a long way towards providing possible solutions to the questions that are asked of it.

TAGGED:big datamachine learningpredictive analytics
Share This Article
Facebook Pinterest LinkedIn
Share
BySubhankar Bhattacharjee
Content Writer
Follow:
Subhankar Bhattacharjee is a small business writer who helps brands promote their products and services. Through his writing on Biggerstalk.com, he delivers well-researched, high-quality content that supports brands in building their presence and connecting with their target audience. His growing reputation as a thoughtful and effective writer is making a significant impact in the business community.

Follow us on Facebook

Latest News

sales and data analytics
How Data Analytics Improves Lead Management and Sales Results
Analytics Big Data Exclusive
ai in marketing
How AI and Smart Platforms Improve Email Marketing
Artificial Intelligence Exclusive Marketing
AI Document Verification for Legal Firms: Importance & Top Tools
AI Document Verification for Legal Firms: Importance & Top Tools
Artificial Intelligence Exclusive
AI supply chain
AI Tools Are Strengthening Global Supply Chains
Artificial Intelligence Exclusive

Stay Connected

1.2kFollowersLike
33.7kFollowersFollow
222FollowersPin

You Might also Like

conversation intelligence software
Machine Learning

Machine Learning Aids Marketing With Conversation Intelligence Software

7 Min Read
machine learning in businesses
ExclusiveMachine Learning

Machine Learning And RUM Are A Pivoting Point For Online Business

5 Min Read

More Data, More Problems? Not for Thomson Reuters

4 Min Read

PAW: New Challenges for Developing Predictive Analytics Solutions

7 Min Read

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

giveaway chatbots
How To Get An Award Winning Giveaway Bot
Big Data Chatbots Exclusive
ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots

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?