Question

Data analytics

Answer 1

Data Analytics:

Data Analytics in short(DA) is a process which involves scrutinising large amount of data in order to ascertain conclusion,patterns about what information these data possess with the help of softwares and modern systems.

DA methods can help a organisation/imdustries to improve significantly in terms of its revenues,popularity,efficiency,customer base etc. by analysing data,finding out market trends,previous records and stats which will make them enhance their performance globally with resprct to their rivals.

DA can be of two forms Quantitative DA and Qualitative DA.In Quantitative DA, numerical datas are analysed which involves stats and figures whereas Qualitative DA involves comprehending contents of non-numerical data such as video,audio,texts,phrases etc.

In DA first data are collected from different sources may be data warehouses,databases and informations are identified and then flaws,error or duplicates are removed from datas then with the help of tools and softwares an analytical model is framed for the data.

its aapplication involves commercial industries,healthcare,travel etc.

Data analysis:

data analysis is a process of analysing data like data analytics which divides the whole data set into smaller data sets for scrutinising,raw data are obtained and transformed into a information useful for decision making process.

Data is coliected to answer queries,disapprove theories,test hypothesis by data scientists and engineers.

data analysis involves several processes:

1)first of all which data are required for what purpose is identified first by considering different parameters for the analysis

2)collection of data is done from different sources may include online sources,satellites,etc.

3)Data are then organised ina specific manner for analysis

4)Data cleaning is done i.e. removing errors,flaws,duplicate datas by using specialised tools and softwares.

5)now data is analysed to comprehend the information contained in a data ,if further cleaning is required it can be done in this stage.

6)Now an model is formed to analyse this data,this model includes algorithm,mathematical formulas to identify relationships among the data.

7)Then an applcation is used which will take data as input and generate output.

Its application includes Gaming industries,healthcare industries,Energy management.