Hello friends,
Sorry for the late post. I was busy in completing a significant milestone in my life. So let me start, as I promised, we will see some facts about Big Data. Today's world can be best described as "we are drowning in data but are starving for information". The data from web, social media sites, sensors, logs etc. is so large so that we cannot handle it by traditional data processing methods. Trillions of status updates are posted to Facebook daily. We see large data, but have we thought of how to store it. It's high time to think of such data storage techniques. Here comes the importance of big data. Let me go back to my good old school days.
Too much of theory for the day. We can look at the tools and techniques used in Big Data Analytics in the next post. So just wait and see. Catch you all soon..
Sorry for the late post. I was busy in completing a significant milestone in my life. So let me start, as I promised, we will see some facts about Big Data. Today's world can be best described as "we are drowning in data but are starving for information". The data from web, social media sites, sensors, logs etc. is so large so that we cannot handle it by traditional data processing methods. Trillions of status updates are posted to Facebook daily. We see large data, but have we thought of how to store it. It's high time to think of such data storage techniques. Here comes the importance of big data. Let me go back to my good old school days.
What is Big Data?
According to Wikipedia: Big data is a term used to describe large and complex data sets that cannot be handles by other traditional data processing applications. It also includes capture, storage, search, analysis and visualization of the data.Why Big Data?
Organisations can gain significant advantages by managing data effectively. Some of them include:- Better decision making: With the speed of data processing techniques like hadoop and applying in memory analytics we could combine data from multiple sources which would yield better decision making.
- More business opportunities: We can mine the data and can find the customer needs and their satisfaction. This in turn can help us to develop the products that the customers want.
- Cost reduction: Majority of the data processing techniques are open source. This reduces the cost of analysis of large data sets.
How is Big data?
Big Data can be best described by its characteristics. They are:- Volume: It describes the quantity of the data
- Velocity: It is the speed at which the data is generated
- Variety: It is the nature of the data
- Veracity: It describes the quality of the data
- Variability: The inconsistency in the data set is described by variability
When is Big Data?
The data stored in traditional databases cannot be regarded as big data. When we are dealing with terabytes and petabytes of information coming from diverse sources within short span of time, then it can be regarded as big data. In other words it can also be described as those data that satisfies the 5V's of big data or the characteristics of big data.Too much of theory for the day. We can look at the tools and techniques used in Big Data Analytics in the next post. So just wait and see. Catch you all soon..
No Dream is too High!
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