The next phase of demand for IT professional will come from Big Data. It is a high paying job and the demand is huge. So this is a great news for IT professional.
Making money from Big Data is a challenge. Here Data analytics come handy. Data analytics can be of different background which include data science, data mining, web analytics or even statistics. IT professional have to work in tandem with Data Analyst in order to get something meaningful from the huge quantity of data. One of the major complain of Data Analysts is that they don't get enough support from their IT team. This is a major deterrent in their work. Other major problem Data Analyst face is the quality of Data given to them. They are poorly documented and they have to spend huge amount of time in reformatting those data. IT professional must understand the need of Data Analyst and must prepare data according to their need so that they can use their time in analysing the data instead of reformatting it.
What Data Analysts need..
Data analyst need all common type of data group together so that they can come with some conclusion. Like transaction happening in a retail shop must contain data for whole day so that they can come out with a conclusion what customer are buying, how much they are willing to pay and what the shop must have to attract more customer.
Raw Data must be complete with full details.
All data are important. Previous data always comes as a handy for getting a conclusion. So no data should be deleted and maximum data should be put in use. The more the data the better the conclusion.
Data should be fed to Analysts on time.
In order to come on a particular conclusion is a time consuming activity. So Data analysts must be supplied raw data well in advance not at last moment.
Analysts need lot of space to store the data.
Analysts always want to save data that can come handy in future. They don't want to destroy valuable data due to lack of space.
Current data which is complete, correct and consistent should be supplied to analysts.
Data analysts must spend all there time in analysing the data so the raw data must be properly documented which complete detail. Data must be given in the form of table with rows and columns and each raw representing one particular transaction.
Proper tool must be provided to Analysts in order to make conclusions.
Analysts need various products in order to work properly. They also need to take care of their asset. Most of the time they have no idea how to take care of those valuable assets. Here Big Data professional can come handy and help them.
For the betterment of the organisation IT professional must work in tandem with Data Analysts and provide them with full support.
Making money from Big Data is a challenge. Here Data analytics come handy. Data analytics can be of different background which include data science, data mining, web analytics or even statistics. IT professional have to work in tandem with Data Analyst in order to get something meaningful from the huge quantity of data. One of the major complain of Data Analysts is that they don't get enough support from their IT team. This is a major deterrent in their work. Other major problem Data Analyst face is the quality of Data given to them. They are poorly documented and they have to spend huge amount of time in reformatting those data. IT professional must understand the need of Data Analyst and must prepare data according to their need so that they can use their time in analysing the data instead of reformatting it.
What Data Analysts need..
Data analyst need all common type of data group together so that they can come with some conclusion. Like transaction happening in a retail shop must contain data for whole day so that they can come out with a conclusion what customer are buying, how much they are willing to pay and what the shop must have to attract more customer.
Raw Data must be complete with full details.
All data are important. Previous data always comes as a handy for getting a conclusion. So no data should be deleted and maximum data should be put in use. The more the data the better the conclusion.
Data should be fed to Analysts on time.
In order to come on a particular conclusion is a time consuming activity. So Data analysts must be supplied raw data well in advance not at last moment.
Analysts need lot of space to store the data.
Analysts always want to save data that can come handy in future. They don't want to destroy valuable data due to lack of space.
Current data which is complete, correct and consistent should be supplied to analysts.
Data analysts must spend all there time in analysing the data so the raw data must be properly documented which complete detail. Data must be given in the form of table with rows and columns and each raw representing one particular transaction.
Proper tool must be provided to Analysts in order to make conclusions.
Analysts need various products in order to work properly. They also need to take care of their asset. Most of the time they have no idea how to take care of those valuable assets. Here Big Data professional can come handy and help them.
For the betterment of the organisation IT professional must work in tandem with Data Analysts and provide them with full support.
Really nice blog post.provided a helpful information.I hope that you will post more updates like this
ReplyDeleteHadoop admin Online Course Hyderabad
Your blogs and every other content are thus interesting and helpful it makes me return back again
ReplyDeleteBig Data Hadoop Admin Training
RPA Training in Chennai
RPA Training