What is Analytics? Learn about data analytics

Analytics, can be described as an art, a process or methodology. It all starts from data collection. It involves discovering and identifying meaningful patterns in the gathered data. This analysis is further communicated with an intent of getting better business insights. Thus, it empowers decision makers with facts, past trends and current state of their business.

Learn Analytics Digital
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Any analytics hugely relies on the ‘data gathering‘.

Data, like any other entity will have noise and impurities in the form unnecessary or wrongly formatted information.

Hence, it is critical to make sure that the first step is taken right!

It also relies on computer programming, reporting and operations research in order to quantify and gain meaningful insight from the collected data.

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Watch this short,crisp short video to get an introduction to Data analysis:

Phases of Data Analysis

 
  • Data Gathering (and collation)
  • Data Processing
  • Reporting – Pattern formation
  • Behavioral analysis (or scoring)
  • Insight generation.
  • Improvise what is necessary
 

Below is the self-explanatory diagram different phases.

Analytics phases

Analytics types or stages

 
  1. Descriptive – Describes ‘what happened’?
  2. Diagnostic – Helps to do a sort of postmortem analysis i.e., answers ‘Why’?
  3. Predictive – Estimates what is most likely to happen?
  4. Prescriptive – Provides suggestions, and solutions to solve existing problems.
 

Data Integration in analytics

Integrating data from various sources gives the ability to get a holistic view of your marketing/operations. It also makes sure that all the channels/mediums are in ‘sync’ for future communications.

A self-explanatory diagram of process of data integration is shown below:

Analytics data integration process

All these mediums or channel are a part of Digital marketing activities. Refer this link to get basic idea of what is digital marketing. You can then discover how analytics makes sense!

The areas of analytical application

These days, institutions and organizations are trying to get data analysis married to their existing process irrespective of their business streams. However, below are most widely used applications as of today.

 
  • Web-analytics
  • Business-analytics
  • Fraud analysis
  • Risk analysis
  • Advertisement and marketing effort analysis
  • Enterprise decision management
  • Market optimization
 

The more a business is equipped with data, the lesser it has to depend on guesses and intuitions.

From analytics, one can easily find answers to questions like:

 
  • What happened?
  • How or Why did it happen?
  • What’s happening now?
  • What is most likely to happen next?
  • What do customers like or dislike?
 

What’s the future of Analytics?

  • It is still in  ‘infancy’ – Baby phase! 🙂
Analytics is baby
  • We have only achieved about 20% of full data’s analytical potential.
Analytics is just 20%
  • Data analysis is either present or entering in to every field in the world.
    • IT Services, Production, HR, Healthcare, Hotel, Transportation, Education, Airlines etc.
Analytics in other fields
  • Artificial intelligence, Deeper machine learning, More accurate outcome prediction
Analytics in Artificial intelligence

What will be our focus at Digilitica?

 
  • We will begin with pure Web/Digital data analysis coupled with concept and practical walk through of tag manager implementation and generating user-behavior-reports from the websites.
Focus on Digital analytics
 
  • Focus on learning free Google Tag Manager and Google analytics tool in simplest possible way.
    • Learn about various Dimensions, Metrics and reports
    • Learn how to decipher a report, how to learn from any analytical report?
Focus on Google tools
 
  • Slowly move on to Social Media Marketing, Email Marketing, SEO, AdWords etc.,  and learn about ‘advanced’ levels of data analysis in the coming days.
Focus on Analytics Reporting
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