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The 5 Stages to Successful Data Analytics

Fancy yourself in a career as a data analyst? Are you an aspiring IT technician or ready to branch out into a new career? This article explains the 5 stages you need to go through to successfully analyse any piece of data.

Like any other computer science, data analysis requires a standard set of laws and rules. This means that taking a measured, consistent approach to the data likens you to a laboratory scientist, approaching plant matter to determine its origins using a microscope. The only difference is in how metaphorical the microscope is.

Analyse Any Data in 5 Stages

There are set ways of gathering, examining, and interpreting data. If you can repeat the process the same way each time, you will be searching for data analyst jobs in no time.

Stage 1 Finding Out What You Need to Monitor

Any data analysis happens because you have a problem. You are trying to solve that problem, and to do it you need to determine which data sets you need to study to get the answer. The first stage in data analysis is therefore defining which data you need to answer your question so you can start using software systems to collect what you specifically need to know about.

Step 2 – Data Collection

Next up, you need to figure out a way to collect that data and organise it into a workable format. First and foremost here is complying with data collection policies within your region. There is a fine line between gathering anonymous facts from site visitors and using an AI to mine data to aid with machine learning.

Step 3 Clean up the Raw Data

When you search for specific functions in software programs, it is the equivalent of casting a giant net out and gathering all the data related to what you need to know. You catch the facts you need, but you also catch 5 articles based on the original information, all the related studies, social media opinions, misinformation, and more. How do you clean it? Delete the doublers, look at the dataset and strip it of bad sources, and so on. Microsoft have a helpful guide on this stage in Excel.

Step 4 The Analysis Stage

This is when you have a neat dataset and all the relevant information in front of you to start analysing what the facts and figures mean. There are several complex techniques that software developers use to do this. Learn them, play around with them, and find which types best suit your research style. Then it is all a matter of having fun.

Step 5 – Evaluation, Delivery, and Strategies for Improvement.

The final step in the data analysis process should always be a final evaluation. You look at the work and see how you could have improved your skills. You look at the numbers and you find a way to present them in visually interesting ways. Lastly, you feed all this back to your employer while simultaneously advising them on solutions and future prevention strategies.

Analyse your Online Data to Boost Performance

The goal of any online data research is that it should form a strategy which helps solve or answer the initial question. Approach it logically and always present further problems as new opportunities.

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