 Welcome to the session on what is big data analytics. In this video we will be learning what exactly big data analytics is ok and what it is not. Let us move ahead. The learning outcomes of this session are at the end of this session you will be able to differentiate what exactly this big data analytics is and what it is not and you can classify the big data analytics. The transformation of data into actionable insights usually what happens that till now we have operated on the data we have manipulated the data but getting the knowledge from the data getting the information from the data which is converted as the actionable insight for the decision making that is very important ok. So let us see that how we can do that basically what happens raw data is collected classified and organized ok at the beginning because raw data is directly cannot be used for the actionable sites then what we are doing we are associating the metadata ok to that data which is converting into the meaningful information means whatever the data is there after collecting classifying in organizing we are associating the metadata to it and then we are getting the meaningful information from that one. Then aggregation and summarization we are doing and why this aggregation and summarization is required it is required for analysis ok after getting the information we are we are doing that for the analysis and then whatever this accumulation of the information is there it is totally building the knowledge and once we get the knowledge and it will help to go for the actionable insights and that is used for finally the decision making ok. So that is what a transformation of data is converted into actionable insights. Let us see pictorially so what it is specifying here that data is there then information then knowledge and then actionable insights and how we are reaching towards this one we are starting with collection of the data then we are organizing the data then summarizing that data then analyzing the data synthesizing the data that is getting the meaning of the information from that data then finally whenever the actionable insights we are getting then we are going for the decision making. Now what exactly big data analytics is basically we call it as it is a process for examining the big data based on the some unearthed trends ok unknown relations uncover patterns which are not there till now in the data ok and that from that we are getting the useful information that too with the faster and better decisions ok. So it is helping us to get the faster and the better decisions. Now for this one analysis we have to do and this analysis is beginning with analyzing the all available data what exactly now the available data is let us go one by one. So these are few examples of available data one might be the websites data then the billing data which is the point of sale data and ERP data entrepreneurship resource planning data then it is a customer relationship management data RFID data social media data whatever ok all these are the available data so the data may be available in any other format. So let us move ahead with what exactly big data is saying or big data analytics is saying. So this big data analytics is talking about all these things what are these one you just see one by one that is big data analytics is totally the technology enabled analytics ok we are using more tools and technologies for getting the insights from the data richer deeper insights into customers partner and the business ok whatever the insights it is giving that is deeper insights it is providing richer insights it is providing which is according to the satisfaction of the customer or of anybody who is there in the organization. It is talking about moving the code into data so whatever the code is there that we are converting into a data that is we call we are calling it as a analytics it we are it is providing the competitive advantage here because most of the organizations are taking the business decisions based on this big data analytics only ok their historical data is there or whatever the current data the that is generated even through internal or external sources all that one is analyzed and then some decision making process will go on based on this data and this big data analytics is providing the collaboration of IT with the business users and basically the data scientist why because infrastructure collaboration and even the end users or organizers the business users ok and it is a totally combination of IT with the business users and as well as a data scientist what a data scientist is doing data scientist is actually analyzing the data ok and whatever the insights and all that is there the professionalism comes under this data scientist now another thing in big data analytics is what working with the data ok which is having more that is huge amount of volume and variety is there which is beyond the normal storage and the processing ok whatever the data is there the volume of that data and the variety of that data till now is beyond the storage capacity and beyond the processing thing. So, this even if the huge amount of data is processing then also the processing should be fast ok that is done by this big data analytics and it will take the time sensitive decision because time based decisions are there timely decisions we have to take according to that so big data analytics will do that one so obviously that will provide a better and faster decisions for the real time applications also. So, big data analytics is basically talking about all this one now let us see what it is not ok what big data analytics is not what it is not the this is all the things big data analytics is not only about volume ok only large or huge amount of volume of the data is not handling here there is variety there is velocity ok there is validity more these are there ok. So, it is not only talking about volume it is not just an technology just now we have seen that it is a combination of infrastructure business users data scientist and everything. So, it is not a simple technology it is not just replacing the normal rdbms into the big data analytics part not like that ok it is not even replacing data warehouse because data warehouse simply is for storing a large amount of data we are using ok, but the operations and all that that depends upon the manipulation of the data here in this one it is providing the insights ok big data analytics is providing the insights here. Then it is not only used by huge online companies like Google or Amazon anybody can use it ok only you cannot say that the big companies the are are using it not like that ok and the next one is one size fit on the traditional rdbms ok it is not you cannot see that after the traditional rdbms this is built not like that ok. So, big data analytics is a part of technology it is a combination of technology and users and the data scientist and all. Now why this sudden hype around big data analytics is happening ok why everyone is saying nowadays big data analytics because data is growing at a compound annual rate of 40 percent or more now it is nearly reached 45 zeta bytes by 2020 if we are talking about and cost per gigabyte is hugely dropped ok cost of the data is hugely dropped the user friendly analytics tools there are n number of user friendly analytics tools in the market today. So, that is what the the sudden hype has come for the big data analytics we can say. Let us imagine what exactly 45 zeta bytes of data means you can see here this table is showing the conversion of all the units of the data into the possible amount and few examples are provided here. So, just if we are talking about zeta bytes then zeta bytes is nothing but 1000 exabytes and what this combination is it is nothing but as much information as there are grains of sand on all the world's beaches you can just imagine what kind of volume of data is this zeta byte is ok simply. So, this is about and just try to answer few questions here that what is big volume of data and what is big variety of data you can pause the video see what big volume of data is data which is growing from bits to bytes bytes to petabytes to exabytes and zeta bytes and more that we call it as large volume of data and variety of data variety of data deals with a kind of data range of data the data types the structures of the data from where the sources of the data various sources of the data is there from where the data is coming. Let us move ahead what big data entails big data is providing start with more data produced ok if more data is produced then more storage is there of the data and if more data is stored we can analyze more data and as most of the data or more data is analyzing automatically it is providing the better prediction and if it is providing better prediction then the growth of the analysis is again there which is steadily growing ok every time. So, again this cycle repeats again the data is produced more again the data is storing again the data is analyzed and then again the better finer product predictions are provided. So, this is all about this video these are my references thank you.