Importance of Data Analytics

Data Analytics, Data Scientists, Business Analytics?

Few days back when I published my first blog on "Internet of Humans", one of my friend told me to start writing my experience and whatever I know about Data Analytics so that it could be of some help for the people who actually want to learn "Data Analytics" but do not have a proper guidance on how to start with. So here I am starting to share my experience in the industry so far.

Before going into anything related to analytics tools or techniques being used in the data analytics industry, I would like you guys to first understand the meaning and importance of the word "Data Analytics" or "Data Scientists" or "Business Analysts".

So lets start with "What and Why" of Data Analysis

Data analysis is nothing but a process of converting data into some meaningful structure with goals of discovering useful information, suggesting conclusions and supporting decision making. As per me Data analysis is important to business will be an understatement. In fact, no business today can survive without analyzing available data. For more clarity lets visualize the following situations :

• A leading professional social networking company wants to understand how the different channels(email campaigns, ads on the website, etc) which they are using to promote the launch of the new mobile application is contributing to the activation of the new application by users
• A pharma company conducted a survey amongst the physicians for the launch of a new drug and wants to understand whether their product is better than the existing drug in the market or not or how many of the physicians will be likely to prescribe the new drug to the patients.
• A leading mobile manufacturer recently announced the release date and specification for the new phone which they are launching. They want to understand how the people all over the world are reacting to the product, they want to understand the sentiments of the people regarding the new phone.

These situations are indicative enough to conclude that data analysis is the lifeline of any business in today's world. Whether one wants to arrive at some marketing decision or fine-tune new product launch strategy, data analysis is the key to all the problems.

Merely analyzing data isn't sufficient from the point of view of making decision. How does one interpret from the analyzed data is more important. So in my views, data analysis is not a decision making system, but decision supporting system.

Now lets move on to the role of "Data Scientist" or "Business Analyst" in this...

I have seen many people getting confused with the these two terms, people think that these two terms are same but these are completely two different roles. A data scientist / data analyst and a business analyst is two different roles with two different skill sets. I have been working as both, as a data scientist as well as business analyst so know the clear difference between these two roles. 

Business Analyst :

A business analyst does research and extract valuable information from structured and unstructured sources to explain historical, current and future business performance, determine the best analytical models and approaches to present and explain solutions to business users

Data Analyst/Data Scientist :

A data scientist or analyst designs, develops and deploys algorithms through statistical programming that supports business decision making tools, manage large amount of data, create visualizations to aid in understanding. The role of Data Analyst and Data Scientist can again be differentiated but will not go into that now.

So this is all for now, will take this further with me adding new topics to it as we move on. 

Note : I am going to keep my posts short to eliminate the chance of boredom or over flow :)

Big Data and Internet of Humans

Internet of Things Humans

Introduction Big data, analytics, algorithms, the “Internet of Humans” is one of the hottest technology in the field of Data Analytics. Sensor technology is so advance these days that we can monitor almost everything in real-time. Real-time monitoring enables real time data gathering, real-time data analysis and therefore real-time decision making. Monitoring various vital signs of the patients or even normal people in real time can give us dramatic results and can help us in saving billions of dollars which are being spend today in healthcare industries.

Human sensors can create vast streams of big data throughout our lives, particularly when we consider matching health related activity with human DNA. General sensors include those connected to mobile phones while consumer applications generally focus on health and fitness apps, as recently launched by Apple and Google. On the other end of the spectrum, there are very sophisticated sensor devices that capture clinical data.

In this digital economy, in near future every human being will get connected with some sensors or gadgets which will keep collecting their health related data (vital signs) and the next step for us would be to start analyzing those data and help healthcare professionals in making better decisions related to their patients and even more. Remote monitoring with real-time data can spot patterns or areas of concern, allowing healthcare professionals to intervene much quicker than if there was a reporting delay. Predictive analytics also allow physicians to compare real-time patient data from monitoring devices to medical baselines, helping them predict which patients are likely to develop complications and need further intervention.

To be continued...