During the process of Descriptive Analytics data is sliced into smaller chunks and then appropriate information about, what has already happened, from those data chunks is extracted. The process of Data Analytics can be classified into four types.ĭifferent type of Data Analytics are as follows: 1.1.1 Descriptive Analyticsĭescriptive Analytics explains what has already happened and it is the simplest form of Data Analytics. With the trends and the information gained, the organizations can then make a better decisions. Now we understand that Data Analytics can be coined as a process of observing the data in order to draw meaningful and logical insight into the data and the information / trend contained in that data. Thus through Data Analysis businesses can optimize their Supply-Chain Process and do a predication of Demand- Supply Chain. Also the data about the defects can be obtained and then analysed for questions like ‘number of defects for each plant / machine / per day etc’. Using the proper Data Analysis technique and tool, the operations head can perform an analysis for every item produced on each machine.
DATA ANALYSIS WITH EXCEL PROJECTS HOW TO
The crucial step is really understanding the kinds of questions one need to ask and how to think about data in hand.Įxample: The Operations Head of a multinational Computer Hardware Production organization has a requirement to analyse production data and identify the defect patterns across all its manufacturing plants across the globe.
DATA ANALYSIS WITH EXCEL PROJECTS CODE
And that tool might be something that is very commonly used like MS Excel, which is a really powerful tool that a lot of people use to Analyse data Or maybe it’s a bit more specialized like writing some R code or Python or something like that and then manipulating the data in that language. Once the data is gathered, the next requirement is of some sort of tool to go and manipulate that data, work with that data, clean up and then start to analyse that data.
So one have all this data from all these types of places. One have got sensors, and this so-called Internet of things is out there. Now-a-days we live in a connected world, where there are devices running, that are emitting data all the time, in real time. So one needs to go and get it out from there. It could be a simple as files some text files, or some documents or increasingly commonly if you working in a large organization, data is more likely to be in somewhere like a database. Data comes in all sorts of shapes and sizes and all different places.
The first step in the whole process of Data analysis is ‘ Getting the Data’. The best thing that one can do with data is just understand what they have and start asking questions and just start exploring and from the results or observations one can make incredible like ,for businesses and organizations, help them drive improvements and address the problems are trying to solve. But actually it’s really about the working with the data. In general people have this idea that it’s all about building Machine learning models and predictive stuff. Data Analysis is mostly about exploring data.
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