Analytics can be described as an art, a process or a methodology. It all starts from data collection. Analytics 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.
Any analytics hugely relies on the ‘data gathering‘. In fact, it’s not wrong to say that analytics “entirely” depends on gathered data.
However, Data, like any other entity will have noise and impurities in the form unnecessary or wrongly gathered information.
Hence, it is critical to make sure that the first step is taken right!
Analytics also relies on computer programming, reporting and operations research to quantify and gain meaningful insight from the collected data.
Watch my short, crisp short video to get an introduction to Data analysis:
Different Phases of Data Analysis
Below is the self-explanatory diagram different phases.
- Data Gathering (and collation)
- Data Processing
- Reporting – Pattern formation
- Behavioral analysis (or scoring)
- Insight generation.
- Improvise what is necessary
Analytics types or stages
- Descriptive: It describes ‘what happened’?
- Diagnostic: It helps to do a sort of postmortem analysis i.e., answers ‘Why’?
- Predictive: It estimates what is most likely to happen?
- Prescriptive: It 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:
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 analytics 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.
- Fraud analysis
- Risk analysis
- Financial 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?