Data Analytics

Anunobi ifechukwu Written by Anunobi ifechukwu · 2 min read >

Data analytics, what is  data analytics? 

Data analytics everyone talks about it but what exactly is it data analytics perhaps you have  heard that data analytics is the next big thing for business. Well, that’s what I learnt today in Mr. Bongo’s class. I am going to cover five key points to give you a better understanding of what it is to be a data analyst. These companies are collecting loads of data all the time but in its rule form this data doesn’t actually mean anything this is where data analytics comes in data analytics is the process of analyzing raw data so that we can pull out insights which are useful to companies these insights are super important to drive smart business decisions what the data analyst does is they take all this complex jigsaw of data they take it out and they make it into something which you can really use having in the data the data analyst can then pass these insights on so that the company can then make the most informed decisions. How is data analytics used in the real world so the fact is data is everywhere so it actually has an infinite amount of uses across all kinds of businesses and organizations globally speaking data analytics is used to make faster and Better Business decisions. To reduce overall business costs and to develop new and innovative products and services. In most specific terms data analytics might be used to do the following 

  • to predict future sales or purchasing behaviors 
  • for security purposes to help and protect against fraud 
  • to analyze the effectiveness of marketing campaigns 
  • to boost customer acquisition retention 
  •  to increase supply chain efficiency 

so this gives us a little bit of an overview of what data analytics can be used for in the real world.

So unless you’re probably interested in the roles and responsibilities that you’ll have in the field based on some real job ads here are some typical roles and responsibilities that you’ll have to undertake as a data analyst 

  • manage the delivery of user satisfaction surveys and report on results using data visualization software
  • Work with business line owners to develop requirements to find success metrics manage and execute analytical projects and evaluate results
  •  monitor practices processes and systems to identify opportunities for improvement 
  • Monitor practices processes and systems to identify opportunities for improvement translate important questions into concrete analytical tasks 
  • Gather new data to answer client questions collecting and organizing data from multiple sources 
  • design build test and maintain back-end code

So now we looked at data analytics as a role we are now going to go into the process of data analysis so now we are going to outline the five main steps a data analysts would take when approaching new project step one define the questions that 

  • you want to answer you need to answer why you are  conducting this analysis and what questions and answers you need to find at this stage
  •  you will take a clearly defined problem and then you will make a hypothesis or research question that you can go on and answer 
  • you will then need to identify what types of data you need but importantly where it will come from for instance a business problem might be that customers aren’t subscribing to a paid membership once that free trial ends your key question can then be what kind of strategies can the business implement to retain their customer base step two would be to collect this data with a clear question in mind you’re ready to start collecting that data 
  • data analysts will usually gather data from primary sources or internal data that the company already has such as CRM software or e-mail marketing tools 
  • they may tend to secondary or external sources such as open data sources so this can include data from government portals tools like Google trends but also data from international organizations like the World Health Organization 

so step three you need to clean scrub that data once you’ve got that data you need to prepare it and ready it for analysis your original data might include duplicates and nominees all missing data which could distort how the data is interpreted these all need to be removed .

So far this is what I really understood from our class Data analytics. I hope you enjoyed my blog.

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