Big Data and Data Analytics

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Big Data is gaining a lot of popularity and importance lately and why shouldn’t it. As a data lover, I can say there is nothing more valuable these days than data.

But What is Big Data ?

Data helps in building not only a virtual assistant and a humanoid but many more. Yeah, I know these two applications are enough for most of you people to fall in love with it but trust me it can do more. Data also helps businesses to grow and earn more. Large scale businesses like Amazon, Google, IBM, Apple, Samsung and many more are using the power of data to grow their business and reach more customers. 

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How is it generated ?

These days everyone uses google. Whether to find the directions to your new office or to search newly opened cafes to try out, we uses google one way or another. Every click we perform on our devices is recorded and stored in some database. With google providing so many applications on a single smartphone device and with billions of smartphones in the world, there is tremendously huge amount of data generated every second with every single finger touching the screen and even that’s not all. Whenever anyone searches any product online or watches video on YouTube or tweets or posts pictures on social media, all these activities are stored in a database somewhere and used to provide recommendations, personalized customer interactions and to predict future requirements of the customer.

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Almost every IOT device contributes a lot in generating big data but most common big data sources are social media, e-commerce websites, streaming services like netflix, YouTube and prime video and cloud applications. For those of you who is unfamiliar with the term “IOT”, I will be publishing another blog covering all about IOT but for further understanding of this blog, every smart device which uses internet is known as IOT device which stands for “Internet Of Things”.

Who uses it?

Data helps in building not only a virtual assistant and a humanoid but many more. Yeah, I know these two applications are enough for most of you people to fall in love with it but trust me it can do more. Data also helps businesses to grow and earn more. Large scale businesses like Amazon, Google, IBM, Apple, Samsung and many more are using the power of data to grow their business and reach more customers. 

How to use it ?

As I said, Data is “helping” to achieve impossible. Data cannot do things on its own. Where none of this would be possible without data, there is an important part for special kind of people. Even with all these potential powers, data in its first form is ugly and useless. That’s where data analyst comes into picture.

Remember when I said that big data is a data in huge amount. Well there’s more to the definition. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with traditional data-processing application software.

Wait! That’s too much of information to fetch.

Let’s break it down.

What is analyze? Why does it need to be analyzed?

Coz its ugly and useless but still in huge amount. You can easily find the required information from 10 lines of data. But as number of lines increases, difficulty to fetch information from it also increases. What if there are 100,000 lines of data? You see, up to some limit even relational databases can help you but when it starts getting out of that limit, things start falling apart. With the help of advanced techniques and tools, you an easily analyze the big data. You must analyze because in such huge data, information is sometimes hidden in some kind of pattern which you have to identify.

Who is Data analyst?

Data analyst are the ones who performs all the heavy lifting mostly with the help of a programming language or a data analysis tool and sometimes even both. Most of the data analyst have an IT background or a mathematical background. A skilled data analyst is the one who has a detailed knowledge of a programming language (most commonly Python or R), a non-relational database system, an ability to analyze, model and interpret data along with a strong problem-solving skill.

The common duties of a data analyst include but not limited to conducting full life-cycle analysis to include requirements, activities and design, reporting analysis and monitor performance and quality control plans to identify improvements.

The scope of big data is beyond this blog and how much of potential it has is pretty much clear by now. I will be covering the application and pathway on how to acquire all the skills necessary to become a successful data analyst.

Enjoy your day.

Stay tuned.